Abdurahman Rejeb a , Alireza Abdullahi b , Karim Rejeb c , Horst Treiblmaier d,
- a Ngalaba njikwa na iwu, ngalaba nke Economics, Mahadum Rome Tor Vergata, Via Columbia, 2, Rome 00133, Italy
- b Ngalaba nchịkwa azụmahịa, ngalaba nchịkwa, Mahadum Kharazmi, 1599964511 Tehran, Iran
- c Ngalaba Sayensị nke Bizerte, Mahadum Carthage, Zarzouna, 7021 Bizerte, Tunisia
- d Ụlọ akwụkwọ nke International Management, Modul University Vienna, Am Kahlenberg 1, 1190 Vienna, Austria
Ozi edemede | ABSTRACT |
Keywords: drones UAV Ọrụ ubi Internet Ihe Akwụkwọ Nsọ | Drones, nke a na-akpọkwa ụgbọ elu ikuku na-adịghị mma (UAV), ahụla mmepe dị ịrịba ama n'ime iri afọ ndị na-adịbeghị anya. N'ọrụ ugbo, ha agbanweela usoro ọrụ ugbo site n'inye ndị ọrụ ugbo nnukwu ego nchekwa ego, mụbaa arụmọrụ arụmọrụ, yana uru ka mma. N'ime iri afọ gara aga, isiokwu nke ugbo drones nwere dọtara nlebara anya agụmakwụkwọ dị ịrịba ama. Ya mere, anyị na-eme nyocha zuru oke dabere na bibliometrics iji chịkọta ma hazie akwụkwọ agụmakwụkwọ dị ugbu a wee kpughee usoro nchọcha dị ugbu a na ebe dị egwu. Anyị tinye usoro bibliometric wee nyochaa akwụkwọ ndị gbara drones ọrụ ugbo gburugburu iji chịkọta na nyochaa nyocha gara aga. Nyocha anyị na-egosi na nghọta dịpụrụ adịpụ, ọrụ ugbo ziri ezi, mmụta miri emi, mmụta igwe, na ịntanetị nke ihe bụ isiokwu dị oke egwu metụtara drones ugbo. Nkọwa okwu ahụ nyocha na-ekpughe ụyọkọ nyocha isii sara mbara na akwụkwọ. Ọmụmụ ihe a bụ otu n'ime mbọ mbụ iji chịkọta nchọpụta drone na ọrụ ugbo ma tụọ ntụzịaka nyocha n'ọdịnihu. |
Okwu Mmalite
Agriculture na-anọchite anya isi nri nri ụwa (Friha et al., 2021), na ọ na-eche nnukwu nsogbu ihu n'ihi
mmụba na-achọ ngwaahịa nri, nchekwa nri, na nchegbu nchekwa yana oku maka nchekwa gburugburu ebe obibi, nchekwa mmiri, na
nkwado (Inue, 2020). A na-atụ anya na mmepe a ga-aga n'ihu ebe a na-eme atụmatụ na ọnụ ọgụgụ ndị bi n'ụwa ga-eru ijeri 9.7 na 2050
(2019). Ebe ọ bụ na ọrụ ugbo bụ ihe atụ kachasị ama nke oriri mmiri n'ụwa niile, a na-atụ anya na agụụ na mmiri chọrọ
oriri ga-abawanye nke ukwuu n'ọdịnihu a na-ahụ anya. Ọzọkwa, na-abawanye oriri nke fatịlaịza na pesticides
yana mmụba nke ọrụ ugbo nwere ike ibute ihe ịma aka gburugburu ebe obibi n'ọdịnihu. N'otu aka ahụ, ala ubi nwere oke, na
ọnụ ọgụgụ ndị ọrụ ugbo na-ebelata n'ụwa niile. Ihe ịma aka ndị a na-emesi mkpa ọ dị maka ụzọ ọrụ ugbo ọhụrụ na nke ga-adigide (Elaịja
et al., 2018; Friha et al., 2021; Inoue, 2020; Tzounis et al., 2017).
Achọpụtala itinye teknụzụ ọhụụ dị ka ihe ngwọta na-ekwe nkwa iji dozie nsogbu ndị a. Ọrụ ugbo mara mma (Brewster et al.,
2017; Tang et al., 2021) na ọrụ ugbo ziri ezi (Feng et al., 2019; Khanna & Kaur, 2019) apụtala n'ihi arụmụka dị otú ahụ. Nke
Nke gara aga bụ echiche izugbe maka ịnakwere teknụzụ nkwukọrịta ozi (ICT) na ihe ọhụrụ ndị ọzọ dị oke egwu na ọrụ ugbo iji bulie arụmọrụ na nrụpụta ọrụ (Haque et al., 2021). Nke ikpeazụ lekwasịrị anya na njikwa saịtị akọwapụtara nke ekewara ala ahụ
akụkụ dị n'otu, akụkụ nke ọ bụla na-enwetakwa ego ntinye ọrụ ugbo maka njikarịcha mkpụrụ osisi site na teknụzụ ọhụrụ (Feng et al., 2019; Khanna & Kaur, 2019). Teknụzụ ndị a ma ama nke dọtara uche ndị ọkà mmụta na ngalaba a gụnyere Wireless Sensor Networks (WSNs) (J. Zheng & Yang, 2018; Y. Zhou et al., 2016), Internet of Things (IoT) (Gill et al., 2017; Ọ et al., 2021; Liu et al., 2019),
Usoro ọgụgụ isi (AI), gụnyere mmụta igwe na mmụta miri emi (Liakos et al., 2018; Parsaeian et al., 2020; Shadrin et al.,
2019), teknụzụ kọmputa (Hsu et al., 2020; Jinbo et al., 2019; Zamora-Izquierdo et al., 2019), nnukwu data (Gill et al., 2017; Tantalaki
et al., 2019), na blockchain (PW Khan et al., 2020; Pincheira et al., 2021).
Na mgbakwunye na teknụzụ ndị a kpọtụrụ aha n'elu, a na-ahụta nhụta anya dị ka ngwá ọrụ teknụzụ nwere ikike dị elu iji melite
smart na nkenke ugbo. Satellites, ụgbọ elu mmadụ na-arụkọ ọrụ, na drones bụ teknụzụ na-ahụ maka ime anya (Tsouros et al., 2019).
Drones, nke a ma ama dị ka ụgbọ elu ụgbọ elu Unmanned (UAVs), Unmanned Aircraft Systems (UAS), na ụgbọ elu ndị na-anya ụgbọ elu, bụ nke
nnukwu mkpa dị ka ha nwere ọtụtụ uru ma e jiri ya tụnyere teknụzụ ndị ọzọ na-ahụ anya. Dịka ọmụmaatụ, drones nwere ike ibuga
onyogho dị elu na nke dị elu na ụbọchị ígwé ojii (Manfreda et al., 2018). Ọzọkwa, ha dị na mbufe ọsọ mebere ọzọ
uru (Radoglou-Grammatikis et al., 2020). E jiri ya tụnyere ụgbọ elu, drones na-akwụ ụgwọ nke ukwuu ma dị mfe ịtọlite na idobe ya (Tsouros et al., 2019). N'agbanyeghị na a na-ejikarị eme ihe maka ebumnuche agha, drones nwere ike ịba uru ọtụtụ ngwa ndị nkịtị, dịka ọmụmaatụ na njikwa usoro ọkọnọ (A. Rejeb, Rejeb, et al., 2021a), maka ebumnuche enyemaka mmadụ (A. Rejeb, Rejeb, et al., 2021c), ọrụ ugbo mara mma, nyocha na eserese, akwụkwọ ihe nketa ọdịnala, njikwa ọdachi, na nchekwa ọhịa na anụ ọhịa (Panday, Pratihast, et al., 2020). N'ọrụ ugbo, mpaghara ngwa ngwa dị iche iche nke drones dị ka enwere ike ijikọ ya na teknụzụ ọhụụ, ikike ịgbakọ, yana ihe mmetụta onboard iji kwado njikwa ihe ọkụkụ (dịka ọmụmaatụ, eserese, nleba anya, ogbugba mmiri n'ubi, nchọpụta osisi) (H. Huang et al., 2021) , Mbelata ọdachi, usoro ịdọ aka ná ntị mbụ, anụ ọhịa na nchekwa ọhịa iji kpọọ aha ole na ole (Negash et al., 2019). N'otu aka ahụ, enwere ike itinye drones n'ọtụtụ ọrụ ugbo, gụnyere ihe ọkụkụ na nleba anya uto, ntule mkpụrụ, ntule nrụgide mmiri, na ahịhịa, pesti, na nchọpụta ọrịa (Inoue, 2020; Panday, Pratihast, et al., 2020). Ọbụghị naanị na enwere ike iji drones maka nleba anya, nleba anya, na ebumnuche nchọpụta dabere na data mmetụta ha, kamakwa maka ịgbasa mmiri na nkenke ahịhịa, pesti, na njikwa ọrịa. N'ikwu ya n'ụzọ ọzọ, drones na-enwe ike ịfesa mmiri na ọgwụ na-egbu egbu n'ụzọ ziri ezi dabere na data gburugburu ebe obibi. A chịkọtara uru nke drones na ọrụ ugbo na Tebụl 1.
Isi uru nke drones na ọrụ ugbo.
Rite uru | Ntụaka(s) |
Meziwanye oge na ohere mkpebi nghọta | (Gago et al., 2015; Niu et al., 2020; Srivastava et al., 2020) |
Kwado ọrụ ugbo nkenke | (L. Deng et al., 2018; Kalischuk et al., 2019; Maimaitijiang et al., 2017) |
Nkewa na scouting nke ihe ubi | (Inoue, 2020; Kalischuk et al., 2019; Lopez- ' Granados et al., 2016; Maimaitijiang et al., 2017; Melville et al., 2019; Moharana & Dutta, 2016) |
Ojiji fatịlaịza | (L. Deng et al., 2018; Guan et al., 2019) |
Nleba anya nke oké ọkọchị | (Fawcett et al., 2020; Panday, Pratihast, et al., 2020; Su et al., 2018) |
Ntụle biomass | (Bendig et al., 2014) |
Ntụle mkpụrụ | (Inoue, 2020; Panday, Shrestha, et al., 2020; Tao et al., 2020) |
Mbelata ọdachi | (Negash et al., 2019) |
Nchekwa anụ ọhịa na igbo | (Negash et al., 2019; Panday, Pratihast, et al., 2020) |
Ntụle nke nrụgide mmiri | (Inoue, 2020; J. Su, Coombes, et al., 2018; L. Zhang et al., 2019) |
Ahịhịa, ahịhịa na ọrịa nchọpụta | (Gaˇsparovic et al., 2020; Inoue, 2020; J. Su, Liu, et al., 2018; X. Zhang et al., 2019) |
N'aka nke ọzọ, drones na-echekwa oke oke. Ntinye aka na-anya ụgbọelu, ike injin, nkwụsi ike na ntụkwasị obi, ịdịmma sensọ n'ihi ibu ọrụ
oke ibu, ụgwọ mmejuputa iwu na ụkpụrụ ụgbọ elu, so na ha (C. Zhang & Kovacs, 2012). Anyị na-atụnyere adịghị ike
nke atọ mobile remote sensing teknụzụ dị na Tebụl 2. Teknụzụ ndị ọzọ dịpụrụ adịpụ, dị ka sensọ ala, karịrị ihe ọmụmụ a lekwasịrị anya.
Mkpụmkpụ nke teknụzụ ekwentị dịpụrụ adịpụ dị iche iche.
Remote N'ịchọpụta teknụzụ | Nmepu | References |
Drone (UAV) | Ntinye aka pilot; onyonyo' àgwà (nkezi); ụgwọ mmejuputa iwu (nkezi); nkwụsi ike, imegharị ihe, na ntụkwasị obi; nhazi ọkwa; ike engine; oke ike isi mmalite (ogologo oge batrị); Ogologo oge ụgbọ elu nwere oke, nkukota na mwakpo cyber; oke ibu ibu; nnukwu datasets na nhazi data nwere oke ike; enweghị iwu; enweghị nka, ntinye dị elu ihe mgbochi iji nweta ugbo elu drones; | (Bacco et al., 2018; Dawaliby et al., 2020; Hardin & Hardin, 2010; Hardin & Jensen, 2011; Lagkas et al., 2018; Laliberte et al., 2007; Laliberte & Rango, 2011; Manfreda et al., 2018, 2018; Nebiker et al., 2008; Puri et al., 2017; Velusamy et al., 2022; C. Zhang & Kovacs, 2012) |
Satellite | mkpuchi satịlaịtị kwa oge, mkpebi nlegharị anya nwere oke; adịghị ike na nsogbu visibiliti (dịka ọmụmaatụ, igwe ojii); Enweghị na obere nnyefe ọsọ; nghazi na vignetting na-emetụta data oghere dị ọnụ ala nchịkọta; nnyefe data ngwa ngwa oge ịkwụsị ọrụ | (Aboutalebi et al., 2019; Cen et al., 2019; Chen et al., 2019; Nansen & Elliott, 2016; Panday, Pratihast, et al., 2020; Sai Vineeth et al., 2019) |
Aircraft | Ọnụ ego nnabata dị elu; nhazi mgbagwoju anya; ụgwọ mmezi; enweghị ntụkwasị obi ụgbọ elu, geometry nke ihe oyiyi; data na-abụghị mgbe niile inweta; enweghị mgbanwe; ihe mberede na-egbu egbu; data sensọ mgbanwe n'ihi vibrations; nsogbu georeferencing | (Armstrong et al., 2011; Atkinson et al., 2018; Barbedo & Koenigkan, 2018; Kovalev na Voroshilova 2020; Suomalainen et al., 2013; Thamm et al., 2013) |
Dị ka teknụzụ multidisciplinary na multipurpose na ọrụ ugbo, a nyochala drones site n'akụkụ dị iche iche. Dịka ọmụmaatụ, ndị ọkà mmụta enyochala ngwa drone na ọrụ ugbo (Kulbacki et al., 2018; Mogili & Deepak, 2018), ntinye aka ha na ọrụ ugbo ziri ezi (Puri et al., 2017; Tsouros et al., 2019), nkwado ha na ndị ọzọ. Teknụzụ ndị na-egbu egbu (Al-Thani et al., 2020; Dutta & Mitra, 2021; Nayyar et al., 2020; Saha et al., 2018), yana ohere nke ịkwalite ikike ịnyagharị na ikike nghọta (Bareth et al. , 2015; Suomalainen et al., 2014). Ebe nyocha na ngwa drone na ọrụ ugbo abawanyela (Khan et al., 2021)), ọ dị mkpa ichikota akwụkwọ ndị dị ugbu a wee kpughee usoro ọgụgụ isi ngalaba. Ọzọkwa, dị ka ubi teknụzụ dị elu na-enwe ọganihu na-aga n'ihu, ọ dị mkpa ka a na-eduzi nyocha a haziri ahazi iji chịkọta akwụkwọ ndị dị ugbu a ma chọpụta oghere nyocha dị mkpa. Iji
ụbọchị, enwere nyocha ole na ole na-atụle ngwa drone na mpaghara ọrụ ugbo. Dịka ọmụmaatụ, Mogili and Deepak (2018) nyochaa nkenke nkedrones pụtara maka nleba anya ihe ọkụkụ na ịgba ọgwụ pesticide. Inoue (2020) na-eduzi nyocha nke satịlaịtị na ojiji drone na nhụta anya na ọrụ ugbo. Onye edemede ahụ na-enyocha ihe ịma aka nkà na ụzụ nke ịnakwere ọrụ ugbo dị mma na onyinye nke satịlaịtị na drones dabere na nyocha ikpe na omume kacha mma. Tsouros et al. (2019) chịkọta ụdị drones dị iche iche na ngwa ha bụ isi na ọrụ ugbo, na-akọwapụta ụzọ dị iche iche nnweta data na nhazi. N'oge na-adịbeghị anya, Aslan et al. (2022) mere nyocha zuru oke nke ngwa UAV na ọrụ ugbo ma mesie mkpa ọ dị n'otu oge n'otu oge na maapụ maka UAV na griin haus. Diaz-Gonzalez et al. (2022) enyochala ọmụmụ nso nso a gbasara mmepụta mkpụrụ osisi dabere na usoro mmụta igwe dị iche iche na ime obodo
usoro mmetụta. Nchoputa ha gosiputara na UAV bara uru iji gosiputa ihe nleba anya ala na imeputa sistemu satịlaịtị n'ihe gbasara mkpebi oghere, oge ozi, na mgbanwe. Basiri et al. (2022) mere nyocha zuru oke nke ụzọ dị iche iche na ụzọ iji merie ihe ịma aka-atụmatụ ụzọ maka multi-rotor UAV n'ihe gbasara ọrụ ugbo ziri ezi. Ọzọkwa, Awais et al. (2022) chịkọtara ngwa nke data UAV remote sensing na ihe ọkụkụ iji tụọ ọkwa mmiri wee nye njikọ dị omimi nke ikike UAV anya maka ngwa nrụrụ aka. N'ikpeazụ, Aquilani et al. (2022) nyochara teknụzụ ọrụ ugbo prevision etinyere na sistemu anụ ụlọ ebe ịta nri wee wepụta na nhụta anya nke UAV nyere bara uru maka ntule biomass na njikwa igwe.
Ọzọkwa, agba mbọ iji UAV na nleba anya, nleba anya na ịchịkọta anụ ụlọ ka akọpụtala n'oge na-adịbeghị anya.
Ọ bụ ezie na nyocha ndị a na-enye nghọta ọhụrụ na nke dị mkpa, ọ dịghị nyocha zuru oke na nke ọhụrụ nke dabeere na bibliometrics nwere ike ịhụ na akwụkwọ ndị ahụ, nke na-enye nghọta doro anya. Ọzọkwa, ekwuru na mgbe mmepụta ndị ọkà mmụta na-etolite na ngalaba sayensị, ọ na-adị mkpa ka ndị na-eme nchọpụta were ụzọ nyochaa ọnụọgụgụ iji ghọta nhazi ihe ọmụma nke ngalaba (Rivera & Pizam, 2015). N'otu aka ahụ, Ferreira et al. (2014) rụrụ ụka na ka ngalaba nyocha na-etolite ma na-agbagwoju anya, ndị ọkà mmụta kwesịrị ịchọ ka oge ụfọdụ na-eme ka echiche nke ihe ọmụma na-emepụta na chịkọbara iji kpughee onyinye ọhụrụ, weghara omenala nyocha na usoro, chọpụta isiokwu ndị a na-amụ, na ịbanye n'ime usoro ihe ọmụma nke ubi na ntụziaka nyocha nwere ike. Ọ bụ ezie na Raparelli na Bajocco (2019) na-eduzi nyocha nke bibliometric iji nyochaa ngalaba ihe ọmụma nke ngwa drone na ọrụ ugbo na oke ohia, ọmụmụ ha na-atụle nyocha ndị ọkà mmụta bipụtara n'etiti 1995 na 2017, nke na-adịghị egosipụta ike nke mpaghara a na-agba ọsọ ọsọ. Ọzọkwa, ndị na-ede akwụkwọ anwaghị iji chọpụta onyinye ndị kacha emetụta n'ọhịa, na-achịkọta akwụkwọ, na nyochaa usoro ọgụgụ isi site na iji nchịkọta nchịkọta ọnụ. N'ihi ya, ọ dị mkpa ka a chịkọta akwụkwọ ndị ahụ iji kpughee ihe nyocha nke ugbu a, ihe ndị na-emekarị, na ebe ndị na-ekpo ọkụ.
Iji mejupụta oghere ihe ọmụma a, anyị na-eji usoro ọnụọgụ ọnụọgụ na ụzọ siri ike bibliometric nyochaa ọnọdụ nyocha ugbu a na njikọ nke drones na ọrụ ugbo. Anyị na-arụ ụka na ọmụmụ ihe ugbu a na-enye onyinye dị iche iche na akwụkwọ ndị dị ugbu a site n'inyocha nkà na ụzụ na-apụta nke a na-achọsi ike na ọrụ ugbo ka ọ na-enye ikike dị ukwuu iji gbanwee akụkụ dị iche iche na mpaghara a. A na-ahụta mkpa nyocha nke bibliometric nke drones ọrụ ugbo karịa ka e nyere ihe ọmụma gbasasịa na nke kewara ekewa na drones n'ime ọnọdụ ọrụ ugbo. N'otu aka ahụ, a chọrọ ka a na-achịkọta akwụkwọ ndị metụtara drones ọrụ ugbo n'usoro n'usoro, na-atụle ọmụmụ ihe kachasị emetụta nke na-ewu ntọala nke ubi nyocha a. Uru dị na nyocha ahụ gụnyekwara ịkọwapụta isi isiokwu nyocha nke nọchiri anya na akwụkwọ. N'ịtụle ikike mgbanwe nke teknụzụ, anyị na-ekwupụta na nyocha netwọkụ dị omimi na-enye nghọta ọhụụ site na ịchọpụta ọrụ ndị nwere mmetụta yana ikpughe isiokwu gbasara ikike drones nwere maka ọrụ ugbo.
Ya mere, anyị na-agba mbọ imezu ebumnuche nyocha ndị a:
- Nchọpụta akwụkwọ ndị nwere mmetụta na ntinye pụtara ìhè na ngwa drone na ngalaba ọrụ ugbo.
- Ịchịkọta akwụkwọ, njirimara nke ihe nyocha, na nkewa nke isi ihe ọmụmụ 'ụkpụrụ ọgụgụ isi' dabere na myirịta nke semantic site n'iji nchịkọta nkọwa.
- Nghọta nke evolushọn nke njikọ njikọ na netwọk okwu n'ime oge n'etiti mbipụta dị iche iche na mpaghara na njirimara nke ntụziaka nyocha n'ọdịnihu na isiokwu ọkụ.
A na-ahazi akwụkwọ ndị ọzọ dị ka ndị a: ngalaba 2 na-akọwapụta usoro na usoro nchịkọta data; Nkeji 3 na-enye nsonaazụ nke nyocha; na ngalaba 4 na-atụle nchoputa ahụ wee mechie site na ntinye nyocha, ihe ọ pụtara, na ntụzịaka n'ọdịnihu.
Usoro
N'ime nyocha nyocha a dị ugbu a, anyị na-eme nyocha bibliometric iji nyochaa ngwa drone na ọrụ ugbo. Usoro ọnụọgụgụ a na-ekpughe usoro ọgụgụ isi nke ngalaba ihe ọmụma (Arora & Chakraborty, 2021) na ọnọdụ dị ugbu a, isiokwu na-ekpo ọkụ, na ntụziaka nyocha n'ọdịnihu nke enwere ike nyochaa site na itinye usoro a (Kapoor et al., 2018; Mishra et al. , 2017; A. Rejeb, Rejeb, et al., 2021b; A. Rejeb et al., 2021d; MA Rejeb et al., 2020). N'ozuzu, nyocha nke bibliometric na-enyocha akwụkwọ ndị dị ugbu a iji chịkọta na kpughee usoro nzuzo nke nzikọrịta ozi ederede na mmalite nke ịdọ aka ná ntị dabere na ọnụ ọgụgụ na usoro mgbakọ na mwepụ, ọ na-emetụtakwa nnukwu data set (Pritchard, 1969; Small, 1999; Tahai & Rigsby). , 1998). Site n'iji bibliometrics, anyị na-achọ ịghọta nke ọma paradaịs dị ugbu a na ihe nyocha nke na-enye aka na ngalaba dabere na myirịta (Thelwall, 2008). Bibliometrics na-enye nghọta ọhụrụ site na ebumnobi ike ọnụọgụ nke usoro a (Casillas & Acedo, 2007). Ọtụtụ ndị ọkà mmụta eduzila ọmụmụ akwụkwọ bibliometric na ngalaba ndị metụtara ya, gụnyere ọrụ ugbo, nhụta anya, na mgbanwe dijitalụ (Armenta-Medina et al., 2020; Bouzembrak et al., 2019; A. Rejeb, Treiblmaier, et al., 2021; Wamba & Queiroz, 2021; Wang et al., 2019).
Nyocha ntụaka
Nnyocha ntụtu na-ekpughe nghọta dị iche iche n'ime ngalaba nyocha enyerela. Nke mbụ, ọ na-enyere aka ikpughe ndị na-ede akwụkwọ na akwụkwọ ndị kachasị emetụta na-enye aka na mpaghara nyocha nke enyere ma na-enwe mmetụta dị ukwuu (Gundolf & Filser, 2013). Nke abuo, enwere ike ikpughe ihe omuma ihe omuma na mmekorita n'etiti ndi odee. N'ikpeazụ, site na ịchọta njikọ dị n'etiti ọrụ ndị e zoro aka na ha na-arụ ọrụ, mmadụ nwere ike ịchọpụta mgbanwe na evolushọn nke ngalaba ihe ọmụma ka oge na-aga (Pournader)
et al., 2020). Ọnụọgụ ngụ dị elu nke akwụkwọ na-egosipụta mkpa ya na nnukwu ntinye aka na ngalaba nyocha (Baldi, 1998; Gundolf & Filser, 2013; Marinko, 1998). Ntụle akwụkwọ ngụsị akwụkwọ na-enyekwara aka ịchọpụta ọrụ ndị dị mkpa na soro ewu ewu na ọganihu ha n'oge.
Nyocha ngụkọ akwụkwọ
Ntụle okwu ọnụ bụ ụzọ bara uru iji nyochaa mmekọrịta dị n'etiti akwụkwọ ma gosipụta nhazi ọgụgụ isi nke ubi (Nerur et al., 2008). N'ikwu ya n'ụzọ ọzọ, site n'ịchọpụta akwụkwọ ndị a kacha akpọtụrụ na njikọ ha, usoro a na-ekewa akwụkwọ n'ime ụyọkọ nyocha dị iche iche ebe akwụkwọ ndị dị na ụyọkọ na-ekerịta echiche ndị yiri ya mgbe nile (McCain, 1990; Small, 1973). Ọ dị mkpa ikwu na myirịta ahụ apụtaghị na nchoputa nke akwụkwọ ndị ahụ bụ
na-ejikọta ọnụ ma kwenye na ibe ya; ebipụta bụ otu ụyọkọ n'ihi myirịta isiokwu, mana ha nwere ike inwe echiche na-emegiderịta onwe ha.
Nchịkọta data na nyocha
N'ịgbaso usoro nke White na Griffith (1981) tụpụtara, anyị mere nyocha zuru oke nke akwụkwọ akụkọ iji kpuchie ngalaba nyocha nke ngwa drone na ọrụ ugbo, na-agbaso usoro ise ndị a:
- Nzọụkwụ mbụ bụ nchịkọta data. Ahọpụtara Scopus ka ọ bụrụ otu n'ime ọdụ data zuru oke na ntụkwasị obi nwere nsonaazụ ahaziri ahazi. Ewetara meta-data nke akwụkwọ ndị metụtara ngwa drone niile na ọrụ ugbo. Mgbe ahụ, anyị nyochara isiokwu ndị ahọpụtara, wepụ isiokwu ndị na-adịghị na nyocha.
- Anyị nyochara akwụkwọ ndị ahụ wee chọpụta isi okwu ndị kachasị mkpa ejiri na mpaghara nyocha.
- N'iji nyocha ntụle, anyị nyochara njikọ dị n'etiti ndị odee na akwụkwọ iji kpughee usoro ngụ n'okpuru. Anyị chọpụtakwara ndị na-ede akwụkwọ na akwụkwọ ndị kacha nwee mmetụta na ntinye aka na mpaghara nke drones ugbo.
- Anyị mere nyocha ngụkọ iji chịkọta akwụkwọ ndị yiri ya ka ọ bụrụ ụyọkọ.
- N'ikpeazụ, anyị nyochara njikọ na njikọ dị n'etiti mba, ụlọ ọrụ, na akwụkwọ akụkọ iji gosi netwọk mmekọrịta.
Nchọpụta okwu ọchụchọ kwesịrị ekwesị
Anyị tinyere eriri ọchụchọ ndị a maka nchịkọta data: (drone* OR "ụgbọ elu na-enweghị mmadụ" MA ọ bụ uav* OR "sistemụ ụgbọ elu na-enweghị mmadụ” ma ọ bụ uas MA Ọ BỤ “ụgbọ elu ejiri akwọ ụgbọ mmiri”) NA ( ugbo ma obu ugbo ma obu onye oru ugbo ma obu onye oru ugbo). Emere ọchụchọ ahụ na Septemba 2021. Drones nwere ọtụtụ aha, gụnyere UAV, UAS, na ụgbọ elu na-anya ụgbọ elu (Sah et al., 2021). Achọpụtara okwu ọchụchọ ndị metụtara ọrụ ugbo dabere na ọmụmụ Abdollahi et al. (2021). N'ihi nke doro anya na nghọta, a na-enye kpọmkwem ajụjụ anyị ji mee ihe na Ihe Odide 1. N'ịgbaso usoro ihicha data, anyị mepụtara faịlụ ederede nke e mechara tinye n'ime BibExcel, ngwá ọrụ a na-ejikarị eme ihe na nchịkọta nchịkọta. Ngwá ọrụ a na-enyekwa mmemme dị mfe na ngwanrọ ndị ọzọ ma na-enye nnwere onwe dị ịrịba ama na njikwa data na nyocha. Ejiri ụdị VOSviewer 1.6.16 were were were anya nke uche hụ nchoputa wee mepụta netwọkụ bibliometric (Eck & Waltman, 2009). VOSviewer na-enye ụdị nhụta dị iche iche, ọkachasị maka nyocha maapụ bibliometric (Geng et al., 2020). Ọzọkwa, ọ na-enyere aka n'ịnye nsonaazụ anya doro anya nke na-enyere aka ịghọta nsonaazụ ya (Abdollahi et al., 2021). N'itinye eriri ọchụchọ dị ka ekwuru n'elu, anyị gbakọtara ma chekwaa akwụkwọ niile dị mkpa. Nsonaazụ ọchụchọ mbụ wetara mkpokọta akwụkwọ 5,085. Iji hụ na ịdị mma nke nlele ahọpụtara, ọ bụ naanị akwụkwọ akụkọ nyocha nke ndị ọgbọ ka a tụlere na nyocha ahụ, na-eme ka ewepụrụ ụdị akwụkwọ ndị ọzọ, dịka akwụkwọ, isiakwụkwọ, usoro ọgbakọ, na ndetu ndetu. N'oge usoro nyocha, a na-ehichapụ ihe na-adịghị mkpa (ya bụ, gafere oke ọrụ a), enweghị ọrụ (ya bụ, oyiri sitere na ndenye aha abụọ), na akwụkwọ ndị na-abụghị ndị Bekee. Usoro a mere ka ntinye akwụkwọ 4,700 na nyocha ikpeazụ.
Nchọpụta na mkparịta ụka
Iji malite, anyị tụlere ihe ndị na-emepe emepe na mbipụta mbipụta na akwụkwọ ugbu a banyere drones ugbo. E gosipụtara nkesa oge nyocha nke ndị ọkà mmụta na Fig. 1. Anyị na-ahụ mmụba ngwa ngwa na mbipụta site na afọ 2011 (akwụkwọ 30) gaa n'ihu; ya mere, anyị kpebiri kewaa oge nyocha n'ime ụzọ abụọ dị iche iche. Anyị na-ezo aka n'oge dị n'etiti 1990 na 2010 dị ka ọkwa nrụpụta, nke na-ebipụta ihe dị ka akwụkwọ asaa kwa afọ. A na-akpọ oge post-2010 ọkwa uto kemgbe nyocha na ngwa drone na ọrụ ugbo hụrụ nnukwu mmụba n'oge a. Mgbe 2010 gasịrị, ọnụ ọgụgụ na-arịwanye elu nke akwụkwọ na-akwado mmasị na-arịwanye elu n'etiti ndị nchọpụta, nke na-egosipụtakwa na etinyere drones na nhụta anya ma jiri ya mee ihe n'ọrụ ugbo (Deng et al., 2018; Maes & Steppe, 2019; Messina & Modica, 2020). ). Kpọmkwem, ọnụ ọgụgụ nke akwụkwọ bilitere site na 108 na 2013 ruo 498 na 2018 wee bịaruo ọnụ na 1,275 na 2020. E bipụtara ngụkọta nke isiokwu 935 n'etiti Jenụwarị na etiti Septemba 2021. N'ikpeazụ, anyị kpebiri ilekwasị anya nyocha anyị karịa na ọkwa uto. ebe ọ bụ na oge a na-egosipụta ụzọ aghụghọ kachasị ọhụrụ na nke dị mkpa nke drones ugbo.
Nyocha isiokwu
Ndị na-ede akwụkwọ isiokwu ndị na-ahọrọ maka mbipụta nwere mmetụta dị oke mkpa n'otú e si anọchi anya akwụkwọ ahụ na otú e si ezigara ya n'ime obodo ndị sayensị. Ha na-achọpụta isi isiokwu nke nyocha ahụ wee chọpụta na ọ nwere ike ịmalite ma ọ bụ daa (Day & Gastel, 1998.; Kim et al., 2016; Uddin et al., 2015). Nyocha mkpụrụokwu, ngwa iji kpughee usoro nyocha na ntụzịaka sara mbara, na-ezo aka na mkpokọta mkpụrụokwu nke akwụkwọ niile metụtara na ngalaba (Dixit & Jakhar, 2021). N'ime ọmụmụ ihe dị ugbu a, anyị kewara mkpụrụokwu agbakọtara n'ụdị abụọ (ya bụ, ruo n'afọ 2010 na 2011–2021) iji nyochaa isiokwu ndị kacha ewu ewu. Site n'ime nke a, anyị nwere ike ịchọta mkpụrụokwu dị oke mkpa na nhazi abụọ ahụ wee kwenye na anyị weghaara data niile dị mkpa. Maka setịpụrụ nke ọ bụla, a na-ewepụta mkpụrụokwu iri kacha elu na Tebụl 3. Anyị kpochapụrụ ndị na-ekwekọghị ekwekọ site na ijikọta mkpụrụokwu ndị yiri ya, dị ka "drone" na "drones" ma ọ bụ, n'otu aka ahụ, "Internet of Things" na "IoT."
Tebụlụ 3 na-egosi na "ụgbọ elu ikuku na-enweghị mmadụ" bụ isiokwu a na-ejikarị eme ihe ma e jiri ya tụnyere "drone" na "usoro ikuku na-adịghị mma" na oge abụọ ahụ. Ọzọkwa, “nhụta anya,” “ọrụ ugbo ziri ezi,” na “agriculture” bụ nke a họọrọ nke ọma n'oge abụọ a. N'ime oge mbụ, "ọrụ ugbo ziri ezi" họọrọ nke ise, ọ bụkwa nke abụọ n'ime oge nke abụọ, nke na-egosi otú drones na-esiwanyewanye mkpa n'inweta ọrụ ugbo ziri ezi ka ha nwere ike nyochaa,
nchọpụta, na omume atụmatụ ngwa ngwa, dị ọnụ ala, na mfe ịrụ ma e jiri ya tụnyere usoro ndị ọzọ dịpụrụ adịpụ na ala. Ọzọkwa, ha nwere ike fesa ọnụ ọgụgụ ntinye (dịka ọmụmaatụ, mmiri ma ọ bụ ọgwụ nje) mgbe achọrọ ya (Guo et al., 2020; Inoue, 2020; Panday, Pratihast, et al., 2020).
Ndepụta mkpụrụokwu a na-ejikarị eme ihe.
n'usoro | 1990-2010 | Nke ime | 2011-2021 | Nke ime |
1 | ikuku na-enweghị mmadụ ụgbọala | 28 | unmanned ugbo elu | 1628 |
2 | dịpụrụ adịpụ | 7 | nkenke agriculture | 489 |
3 | agriculture | 4 | dịpụrụ adịpụ | 399 |
4 | airborne | 4 | drone | 374 |
5 | nkenke agriculture | 4 | unmanned usoro ikuku | 271 |
6 | ikuku na-enweghị mmadụ | 4 | agriculture | 177 |
7 | hyperspectral mmetụta | 3 | mmụta miri emi | 151 |
8 | akwara akwara netwọk | 2 | igwe mmụta | 149 |
9 | ụgbọ elu kwụụrụ onwe ya | 2 | ahịhịa Index | 142 |
10 | kọfị | 2 | Ịntanetị nke ihe | 124 |
Ihe ọzọ na-adọrọ mmasị bụ ọnụnọ nke teknụzụ nkwado. Na ọkwa nke mbụ, "Hyperspectral Sensor" na "netwọk akwara artificial" (ANN) so na isi okwu iri. Onyonyo hyperspectral gbanwere onyonyo ọdịnala site n'ịchịkọta ọnụ ọgụgụ dị ukwuu nke onyonyo n'ogo dị iche iche. N'ime ime nke a, ihe mmetụta ahụ nwere ike ịnakọta ozi gbasara mbara igwe ka mma na nke dị iche iche ma e jiri ya tụnyere onyonyo multispectral, spectroscopy, na onyonyo RGB (Adao ˜ et al.,
2017). Ihe omume nke "ANN" na ọkwa mbụ na " mmụta miri emi" (DL) na "ịmụ igwe" (ML) na nke abụọ na-egosi na ọtụtụ n'ime ọrụ ndị e bipụtara lekwasịrị anya na nyocha nke ikike AI usoro maka drone- dabere ugbo. Ọ bụ ezie na drones nwere ike ife efe onwe ya, ha ka na-achọ itinye aka nke onye na-anya ụgbọ elu, nke pụtara na ọgụgụ isi ngwaọrụ dị ala. Agbanyeghị, enwere ike idozi nsogbu a n'ihi ọganihu nke usoro AI, nke nwere ike inye mmata ọnọdụ ọnọdụ ka mma na nkwado mkpebi kwụụrụ onwe ya. Ejiri AI, drones nwere ike zere esemokwu n'oge ịnyagharị, melite ala na njikwa ihe ọkụkụ (Inoue, 2020), ma belata ọrụ na nchekasị maka mmadụ (BK Sharma et al., 2019).
N'ihi mgbanwe ha na ike ha ijikwa ọnụ ọgụgụ buru ibu nke data na-enweghị isi, usoro AI bụ ụzọ kwesịrị ekwesị iji nyochaa data nke drones na-ebufe na usoro ndị ọzọ dịpụrụ adịpụ na nke dabeere na ala maka amụma na ime mkpebi (Ali et al., 2015; Afọ, 2020). Ọzọkwa, ọnụnọ nke "IoT" na oge nke abụọ na-egosi ọrụ ọ na-apụta na ọrụ ugbo. IoT na-agbanwegharị ọrụ ugbo site na ijikọ teknụzụ ndị ọzọ, gụnyere drones, ML, DL, WSNs na nnukwu data. Otu n'ime isi uru dị na mmejuputa IoT bụ ikike ya ijikọ ọrụ dị iche iche nke ọma na nke ọma (ịnweta data, nyocha data na nhazi, ime mkpebi, na mmejuputa) n'oge dị nso (Elijah et al., 2018; Feng et al. , 2019; Muangprathub et al., 2019). Ọzọkwa, a na-ewere drones dị ka ngwa ọrụ dị mma maka ijide data dị mkpa maka ịgbakọ ike na ihe ọkụkụ ahịhịa (Candiago et al., 2015). Fig. 2a na 2b na-egosi netwọk mmekọrịta ọnụ okwu maka oge abụọ ahụ.
Ndị ode akwụkwọ nwere mmetụta
N'akụkụ a, anyị na-ekpebi ndị na-ede akwụkwọ nwere mmetụta ma nyochaa otú netwọk ndị edemede nwere ike isi jiri anya nke uche hụ ma hazie akwụkwọ ndị dị ugbu a. Fig. 3 na-egosi nchikota oge nke ndị nyocha niile nwere ọnụ ọgụgụ kacha elu. Ọnụ ọgụgụ agba na-egosipụta mgbanwe amamihe nke afọ nke nhota ndị edemede. Anyị na-enyocha usoro nrụtụ aka nke ndị nchọpụta bụ ndị bipụtara ọmụmụ banyere drones ugbo site na iji ọnụ ụzọ nke opekempe 50 na akwụkwọ iri. pụọ
Ndị ode akwụkwọ 12,891, naanị 115 zutere ọnọdụ a. Tebụl 4 depụtara ndị ode akwụkwọ kacha nwee mmetụta iri, nke a na-ahazi site na ọnụ ọgụgụ kacha elu. Lopez- Granados F. na-eduga ndepụta ahụ na ntinye akwụkwọ 1,963, sochiri Zarco-Tejada PJ na ntinye akwụkwọ 1,909.
Ndepụta nke ndị odee kacha akpọtụrụ.
Ịnye | Author | ịma |
1 | Lopez-Granados 'F. | 1,963 |
2 | Zarco-Tejada PJ | 1,909 |
3 | Pena ˜ JM | 1,644 |
4 | Torres-S anwụ J. | 1,576 |
5 | Fereres E | 1,339 |
6 | Remondino F | 1,235 |
7 | Bolten A | 1,160 |
8 | Bareth G | 1,155 |
9 | Berni JA | 1,132 |
10 | nke Castro AI | 1,036 |
A bịa na mbipụta nke onye ọ bụla, akụkọ Zhang and Kovacs (2012) bụ ihe ọmụmụ a kacha akpọtụrụ na nke e bipụtara na Precision Agriculture. N'ebe a, ndị ode akwụkwọ nyochara ngwa UAS na ọrụ ugbo nke ọma. Nchoputa nke nyocha ha na-egosi na ọ dị mkpa ịkwalite nhazi ikpo okwu, mmepụta, nhazi nke georeferencing oyiyi, na ọrụ iweghachite ozi iji nye ndị ọrụ ugbo ngwaahịa njedebe a pụrụ ịdabere na ya. Na mgbakwunye, ha na-akwado itinye aka na onye ọrụ ubi nke ọma, ọkachasị na nhazi ubi, ijide onyonyo, yana nkọwa na nyocha data. N'ụzọ dị mkpa, ọmụmụ ihe a so na ndị mbụ gosipụtara mkpa UAV dị na nkewa ubi, nkewa ike, nha ọdịnaya kemịkal, nleba anya nhụsianya ahịhịa, na nyocha mmetụta fatịlaịza na uto osisi. Ihe ịma aka ndị metụtara teknụzụ na-agụnyekwa ụgwọ mgbochi, ikike ihe mmetụta, nkwụsi ike n'elu ikpo okwu na ntụkwasị obi, enweghị nhazi, yana usoro na-agbanwe agbanwe iji nyochaa oke data.
Nyocha ntụaka
Ntụle ntụaka na-anọchite anya ọmụmụ nke mmetụta nke akụkọ, n'agbanyeghị na ọ na-enwe ike ịgbasa (dịka ọmụmaatụ, nhụta okwu, nkọwa onwe onye) ka a na-ewere dị ka otu n'ime ọkọlọtọ ọkọlọtọ maka ntule mmetụta (Osareh, 1996; A. Rejeb et al., 2022; Sarli et al., 2010). Nhota ndị ahụ na-egosipụtakwa mkpa na ike dị mkpa nke onyinye akwụkwọ ndị ahụ na-enye akwụkwọ na otu isiokwu (R. Sharma et al., 2022). Anyị na-eduzi nyocha nke akwụkwọ iji chọpụta ihe ọmụmụ kacha emetụta na drones ugbo ma chịkọta ihe dị n'ime ya. Tebụl 5 na-egosi ndepụta nke akwụkwọ iri na ise kacha emetụta maka oge 1990–2010 na 2011–2021. Akụkọ ndị Berni et al. (2009)b na Austin (2010) bụ ndị a kacha kpọtụrụ aha n'oge 1990 na 2010, yana ngụ 831 na 498, n'otu n'otu. Berni et al. (2009) b gosiputara ikike i nweputa ngwaahịa ihe nleba anya n'onu ogugu site na UAV nke nwere helikopta nke nwere ihe ihe nleba anya di nma na nke di nkpa. N'iji ya tụnyere ihe mmetụta ikuku ikuku, usoro UAV dị ọnụ ala maka ọrụ ugbo na-enwe ike nweta nleba anya nha anya nke ihe ọkụkụ dị ndụ, ma ọ bụrụ na ọ kaghị mma. Ọnụ ego dị ọnụ ala na mgbanwe ọrụ, yana nnukwu spectral, spatial, na mkpebi nwa oge dị n'oge ntụgharị ngwa ngwa, na-eme ka UAV dabara adaba maka ngwa dị iche iche nke chọrọ njikwa oge dị mkpa, gụnyere nhazi oge ịgba mmiri, na ịkọ ugbo. Akwụkwọ sitere na Berni et al. (2009) b bụ nke a kpọtụrụ aha nke ọma n'ihi na ọ jikọtara usoro nku rotary na-enweghị mmadụ yana ihe mmetụta dijitalụ na thermal na usoro nhazi dị mkpa maka ngwa ọrụ ugbo. Mbipụta nke abụọ a kacha kpọtụrụ aha bụ akwụkwọ Austin (2010) dere, bụ onye tụlere UAV site na imewe, mmepe, na nleba anya mbugharị. N'ọrụ ugbo, UAV na-akwado nlekota ihe ọkụkụ site n'ịchọpụta ọrịa n'oge site na mgbanwe ụcha ihe ọkụkụ, na-eme ka ịgha mkpụrụ na ịfesa, na nlekota na ịkwọ ụgbọala.
Ọmụmụ nke Sullivan et al. (2007), Lumme et al. (2008), na Gokto ¨ ǧan et al. (2010) mechaa ndepụta nke isiokwu iri na ise kacha elu e zoro aka na ya. Edemede ndị a na-egosi mmepe nke sistemu UAV iji kwado ọrụ ugbo. Ha na-enye ihe ngwọta maka nsogbu dị iche iche, dị ka nlekota na nyocha ihe ọkụkụ, nlekota na njikwa ahịhịa, na nkwado mkpebi. Ha na-atụkwa aro ma kparịta ikike UAV nwere ịbawanye arụmọrụ nlele yana nyere ndị ọrụ ugbo aka n'ichepụta nke ọma ma dị irè.
akuku azum. Berni dere akwụkwọ abụọ (Berni et al., 2009b; Berni et al., 2009a), na-egosi mmetụta ya dị ukwuu na nyocha metụtara ọrụ ugbo. Akwụkwọ sitere na Zarco-Tejada et al. (2014) so na ọmụmụ ihe ọsụ ụzọ iji gosi mkpa ọ dị iji ihe onyonyo UAV dị ọnụ ala na nha osisi dị elu.
Ndepụta nke akwụkwọ ndị kacha akpọtụrụ.
n'usoro | Site na 1990 ruo 2010 | Site na 2011 ruo 2021 | ||
Akwụkwọ | Ntughari | Akwụkwọ | Ntughari | |
1 | (Berni et al., 2009b) | 831 | (C. Zhang na Kovacs, 2012) | 967 |
2 | (Austin, 2010) | 498 | (Nex & Remondino, 2014) | 893 |
3 | (Hunt et al., 2010) | 331 | (Floreano & Osisi, 2015) | 552 |
4 | (SR Herwitz et al., 2004) | 285 | (Hossein Motlagh et al., 2016) | 391 |
5 | (CCD Lelong et al., 2008) | 272 | (Shakhatreh et al., 2019) | 383 |
6 | (Berni et al., 2009b) | 250 | (Ma et al., 2017) | 373 |
7 | (Grenzdorffer ¨ et al., 2008) | 198 | (Bendig et al., 2014) | 360 |
8 | (Hrabar et al., 2005) | 175 | (Zarco-Tejada et al., 2014) | 347 |
9 | (Y. Huang et al., 2009) | 129 | (Ad˜ ao et al., 2017) | 335 |
10 | (Schmale III et al., 2008) | 119 | (Honkavaara et al., 2013a) | 331 |
11 | (Abd-Elrahman et al., 2005) | 79 | (Candiago et al., 2015) | 327 |
12 | (Techy et al., 2010) | 69 | (Xiang & Tian, 2011) | 307 |
13 | (Sullivan et al., 2007) | 51 | (Matese et al., 2015) | 303 |
14 | (Lumme et al., 2008) | 42 | (Gago et al., 2015) | 275 |
15 | (Gokto ¨ ǧan et al., 2010) | 40 | (Aasen et al., 2015a) | 269 |
N'ime oge nke abụọ (2011-2021), nyocha nke Zhang and Kovacs (2012) na Nex and Remondino (2014) mere ka ọ bụrụ akwụkwọ ndị a na-akpọkarị. Zhang and Kovacs (2012) na-arụ ụka na ọrụ ugbo ziri ezi nwere ike irite uru site na itinye usoro geospatial na sensọ, dị ka sistemụ ozi mpaghara, GPS, na nghọta dịpụrụ adịpụ, iji weghara ọdịiche dị n'ọhịa ma jikwaa ha site na iji usoro ọzọ. Dị ka onye na-agbanwe egwuregwu n'ọrụ ugbo ziri ezi, nnabata nke drones ewepụtala afọ ọhụrụ na nhụsianya dịpụrụ adịpụ, na-eme ka nlele ikuku dị mfe, na-ewere data uto ihe ọkụkụ, ọnọdụ ala, na mpaghara ịgba mmiri. Nyochaa nke Zhang and Kovacs (2012) bụ seminal ebe ọ na-enye nghọta na UAV site n'igosipụta ojiji na ihe ịma aka nke ngwaọrụ ndị a na nlekota gburugburu ebe obibi na nkenke ọrụ ugbo, dị ka ikpo okwu na njedebe igwefoto, ihe ịma aka nhazi data, ntinye aka ndị ọrụ ugbo, na ụkpụrụ ụgbọ elu. . Nke abụọ
Ihe ọmụmụ kacha ezo aka na Nex na Remondino (2014) tụlere ọnọdụ nka nke UAV maka ịdepụta, nhazi, na nyocha ihe oyiyi ụwa.
Ọrụ ha nyekwara nkọwapụta nke ọtụtụ nyiwe UAV, ngwa, na iji okwu, na-egosi ọganihu ọhụrụ na nhazi ihe oyiyi UAV. N'ọrụ ugbo, ndị ọrụ ugbo nwere ike iji UAV mee mkpebi ndị dị irè iji nweta ego na ichekwa oge, nweta ndekọ ngwa ngwa na nke ziri ezi nke mmebi, na ịtụ anya nsogbu ndị nwere ike ime. N'adịghị ka nyiwe ikuku ikuku, UAV nwere ike belata mmefu ọrụ ma belata ihe egwu dị n'inweta na ebe ndị siri ike ma ka na-echekwa ikike dị elu. Akwụkwọ ha chịkọtara uru dị iche iche nke UAV, ọkachasị n'ihe gbasara izi ezi na mkpebi.
N'ime akwụkwọ iri na atọ fọdụrụnụ a kpọtụrụ aha n'etiti 2011 na 2021, anyị chọpụtara nnukwu itinye uche na nyocha jikọtara na ngwa drone na ọrụ onyonyo (Bendig et al., 2014; Ma et al., 2017; Zarco-Tejada et al., 2014) , Agriculture ziri ezi (Candiago et al., 2015; Honkavaara et al., 2013a), viticulture ziri ezi (Matese et al., 2015), nyocha nrụgide mmiri (Gago et al., 2015), na nlekota ahịhịa (Aasen et al. , 2015 a). N'afọ ndị mbụ, ndị nchọpụta lekwasịrị anya
karịa na ịmepụta usoro dị ọnụ ala, dị arọ, na kpọmkwem UAV maka ọrụ ugbo; nnyocha ndị ọzọ na-adịbeghị anya lekwasịrị anya na nyocha nke ngwa UAV maka ọrụ ugbo na nyocha ubi. Na nchịkọta, nyocha a na-ekpughe na akwụkwọ ndị nwere mmetụta na-enyekarị nyocha nke ọmụmụ ihe mbụ iji nyochaa ọkwa sayensị na nkà na ụzụ nke UAV ugbu a ma mepụta usoro UAV iji kwado ọrụ ugbo. N'ụzọ na-akpali mmasị, anyị ahụghị ọmụmụ ihe na-arụ ọrụ nke ọma
usoro ma ọ bụ ọmụmụ ihe nkọwa, nke mejupụtara oghere ihe ọmụma dị ukwuu ma na-akpọ maka nyocha ọzọ na isiokwu a.
Ntụle ngụkọ
Dị ka Gmür (2006) si kwuo, nyocha ọnụ ọgụgụ na-achọpụta akwụkwọ ndị yiri ya ma na-achịkọta ha. Nyochaa nke ọma nke ụyọkọ nwere ike ikpughe ngalaba nyocha a na-ahụkarị n'etiti akwụkwọ. Anyị na-enyocha ntinye aka nke akwụkwọ ndị metụtara drones ọrụ ugbo iji kọwaa mpaghara isiokwu metụtara yana ịchọpụta usoro ọgụgụ isi nke akwụkwọ. N'ihe gbasara nke a, Small (1973) tụrụ aro ka e were nyocha coctation iji mụọ nyocha kacha emetụta na nke seminal.
n'ime ọzụzụ. Iji kpachie ntọala ahụ ka ọ bụrụ akụkọ kacha ọhụrụ (Goyal & Kumar, 2021), anyị na-edobe ọnụ ụzọ ngụkọ nke 25, nke pụtara na ọ ga-abụrịrị na edepụtala akụkọ abụọ ọnụ na ndepụta ntụaka nke akwụkwọ 25 ma ọ bụ karịa. E jikwa ụyọkọ opekempe 1 mee ụyọkọ ahụ na-enweghị usoro ọ bụla maka ijikọ obere ụyọkọ na ndị buru ibu. N'ihi ya, a na-emepụta ụyọkọ isii dabere na myirịta nke ọmụmụ na nhazi ọgụgụ isi ha. Tebụl 6 na-egosi ikesa akwụkwọ n'ụyọkọ ọ bụla.
Ụyọkọ 1: Ụyọkọ a nwere akwụkwọ iri na asatọ e bipụtara ka akwụkwọ ndị dị na ụyọkọ a na-atụle ọrụ drones na-akwado nlekota gburugburu ebe obibi, nlekọta ihe ọkụkụ, na nlekọta ahịhịa. Dịka ọmụmaatụ, Manfreda et al. (2018) na-enye nkọwa nke nyocha ugbu a na mmejuputa UAV na nlekota gburugburu ebe obibi ọrụ ugbo ma na-arụ ụka na nkà na ụzụ na-enye ikike dị egwu iji kwalite nlekota gburugburu ebe obibi na ibelata.
oghere dị n'etiti nleba anya n'ọhịa na ikuku ikuku na nghọta ime oghere. Enwere ike ime nke a site n'inye ikike ọhụrụ maka iweghachite nwa oge ka mma yana nghọta gbasara oghere n'ime nnukwu mpaghara n'ụzọ dị ọnụ ala. Ndị UAV nwere ike ịhụ gburugburu ebe obibi mgbe niile wee ziga data sitere na ndị nwere ọgụgụ isi, ndị etiti / ndị na-achịkọta ihe na-achịkwa sensọ iji chọpụta nsogbu ndị ga-emecha, dị ka enweghị ọrịa ma ọ bụ nchọpụta mmiri (Padua ' et al., 2017). Adao ˜ et al. (2017) kwuputa na UAV dị mma maka nyochaa ọnọdụ osisi site n'iweta oke data raw nke metụtara ọnọdụ mmiri, nleba anya biomass, na ntule ume. Enwere ike ibunye ihe mmetụta UAV ngwa ngwa na ọnọdụ gburugburu ebe obibi kwesịrị ekwesị iji kwe ka ijide data nhụta anya n'oge (Von Bueren et al., 2015). Site na UAV, ndị ọrụ ugbo na-enwe ike ịrụ ọrụ ugbo n'ime ụlọ site n'inwe nha site na ebe ọ bụla na oghere akụkụ atọ nke gburugburu ime ụlọ (dịka ọmụmaatụ, griin haus), si otú ahụ hụ na njikwa ihu igwe mpaghara na nlekota ihe ọkụkụ (Roldan et al). ., 2015). N'ihe gbasara nkenke
ọrụ ugbo, mkpebi njikwa ihe ọkụkụ na-eme ka data ihe ọkụkụ ziri ezi, nke a pụrụ ịdabere na ya na mkpebi oge kwesịrị ekwesị na nke oghere (Gebbers & Adamchuk, 2010; Gevaert et al., 2015; Maes & Steppe, 2019). N'ihi nke a, Agüera Vega et al. (2015) jiri usoro ihe mmetụta multispectral nke UAV na-agbanye iji nweta ihe oyiyi nke mkpụrụ osisi sunflower n'oge oge na-eto eto. N'otu aka ahụ, Huang et al. (2009) rịba ama na nhụta anya nke dabere na UAV nwere ike ime ka nha nke ihe ọkụkụ na ala sitere na data spectral anakọtara. Verger et al. (2014) mepụtara ma nwalee usoro maka atụle ntụnye mpaghara akwụkwọ ndụ akwụkwọ ndụ (GAI) site na nha ntụgharị uche UAV na ngwa ọrụ ugbo ziri ezi, na-elekwasị anya na ọka wit na ihe ọkụkụ rapeseed. Ya mere, drones na-enye ohere ọhụrụ maka iweghachite ozi steeti ihe ọkụkụ na nlegharị anya ugboro ugboro na mkpebi dị elu (Dong et al., 2019; Garzonio et al., 2017; H. Zheng et al., 2016).
Ịchịkọta akwụkwọ ndị nwere mmetụta na drones ọrụ ugbo.
Ụyọkọ | Isiokwu sara mbara | References |
1 | nlekota gburugburu ebe obibi, ihe ubi njikwa, njikwa ahihia | (Ad˜ ao et al., 2017; Agüera Vega et al., 2015; de Castro et al., 2018; Gomez-Cand 'na et al., 2014; YB Huang et al., 2013; Khanal et al., 2017; Lopez-Granados, '2011; Manfreda et al., 2018; P' adua et al., 2017; Pena ˜ et al., 2013; Perez-Ortiz et al., 2015; Rasmussen et al., 2013. 2016; Torres-S anchez et al., 2014; Torres-Sanchez, 'Lopez-Granados,' & Pena, ˜ 2015; Verger et al., 2014; Von Bueren et al., 2015; C. Zhang & Kovacs, 2012) |
2 | Ime phenotyping, mpụta atụmatụ, ihe ọkụkụ elu ụdị, agụta osisi | (Bendig et al., 2013, 2014; Geipel et al., 2014; Gnadinger ¨ & Schmidhalter, 2017; Haghighattalab et al., 2016; Holman et al., 2016; Jin et al., 2017; W. Li et al., 2016; Maimaitijiang et al., 2017; Sankaran et al., 2015; Schirmann et al., 2016; Shi et al., 2016; Yue et al., 2017; X. Zhou et al., 2017) |
3 | Ihe onyonyo thermal maka mmiri, multispectral imaging | (Baluja et al., 2012; Berni et al., 2009b; Berni et al., 2009a; Candiago et al., 2015; Gago et al., 2015; Gonzalez-Dugo et al., 2013, 2014; Grenzdorffer ¨ et al., 2008; Khaliq et al., 2019; Matese et al., 2015; Ribeiro-Gomes et al., 2017; Santesteban et al., 2017; Uto et al., 2013) |
4 | Ihe onyonyo hypersectral, spectral foto | (Aasen et al., 2015a; Bareth et al., 2015; Hakala et al., 2013; Honkavaara et al., 2013a; Lucieer et al., 2014; Saari et al., 2011; Suomalainen et al., 2014) |
5 | Ngwa 3D-Mapping | (Jimenez-Brenes et al., 2017; Nex & Remondino, 2014; Salami et al., 2014; Torres-S Anchez, Lopez- ' Granados, Serrano, et al., 2015; Zahawi et al., 2015; Zarco-Tejada et al., 2014) |
6 | nlekota oru ugbo | (SR Herwitz et al., 2004; Hunt et al., 2010; CCD Lelong et al., 2008; Primicerio et al., 2012; Xiang & Tian, 2011) |
Ọzọkwa, drones bara uru maka ọrụ ịma aka na ọrụ ugbo, gụnyere nkewa ahịhịa. Onyonyo nke ngwaọrụ ndị ahụ egosila na ọ bara uru maka ịchọpụta ahịhịa mbụ n'ọhịa (de Castro et al., 2018; Jim'enez-Brenes et al., 2017; Lam et al., 2021; Lopez-Granados 'et al., 2016; Rozenberg et al., 2021). N'okwu a, de Castro et al. (2018) kwuputa na nchikota nke ihe onyonyo UAV na ihe gbasara ihe onyonyo (OBIA) enyerela ndi oru aka imeri okwu nke ime ka nchoputa n’oge n’oge ihe ubi nke ahihia, nke bu nnukwu n’iru n’ime nyocha igbo. N'otu aka ahụ, Pena ˜ et al. (2013) rụtụ aka na iji ihe onyonyo dị elu dị elu sitere na UAV na njikọ usoro OBIA na-eme ka o kwe omume ịmepụta maapụ igbo n'oge ọka ọka n'oge nke enwere ike iji mee atụmatụ mmejuputa usoro nchịkwa ahihia n'oge, ọrụ karịrị ike nke satịlaịtị na ihe onyonyo ọdịnala ọdịnala. E jiri ya tụnyere nhazi ihe onyonyo ma ọ bụ algọridim nchọpụta ihe, usoro nhazi nke semantic na-arụ ọrụ nke ọma na ọrụ nkewa ahịhịa (J. Deng et al., 2020), si otú a na-enyere ndị ọrụ ugbo aka ịchọpụta ọnọdụ ubi, belata mfu, ma melite mkpụrụ n'oge oge na-eto eto (Ramesh). et al., 2020). Nkeji semantic mmụta dị omimi nwekwara ike ịnye nleta ziri ezi nke mkpuchi ahịhịa sitere na onyonyo ikuku dị elu (Ramesh et al., 2020; A. Zheng et al., 2022). N'agbanyeghị ikike ha nwere maka ime obodo
ịhụ nhazi ọkwa pikselụ, usoro nkewa semantic chọrọ ngụkọ dị egwu yana ebe nchekwa GPU dị elu (J. Deng et al., 2020).
Dabere na mmụta igwe na UAV, Perez-Ortiz et al. (2015) tụrụ aro ka usoro nkewa ahihia ga-esi wepụta usoro iji chịkwaa ahihia akọwapụtara na saịtị mgbe ndị ọrụ ugbo nakweere njikwa ahihia n'oge mmalite. N'ikpeazụ, Rasmussen et al. (2013) mere ka ọ pụta ìhè na drones na-enye nghọta na-adịghị ọnụ na nnukwu mgbanwe mkpebi oghere. N'ozuzu, akwụkwọ ndị dị na ụyọkọ a na-elekwasị anya n'ịchọgharị ike nke UAV iji kwado nhụta anya, nlekota ihe ọkụkụ, na nkewa ahịhịa. Achọkwu nyocha miri emi iji nwetakwuo nyocha ka ngwa drone na nlekota gburugburu ebe obibi, njikwa ihe ọkụkụ, na nkewa ahihia nwere ike isi nweta ọrụ ugbo na-adigide (Chamuah & Singh, 2019; Islam et al., 2021; Popescu et al., 2020; J Su, Liu, et al., 2018) ma leba anya okwu nchịkwa nke teknụzụ a na ngwa mkpuchi ihe ọkụkụ (Basnet & Bang, 2018; Chamuah & Singh, 2019, 2022; Meinen & Robinson, 2021). Ndị na-eme nchọpụta kwesịrị itinye uche na ịkwado nha UAV anakọtara na usoro nhazi nke ọma iji welie ogo kacha mma nke data edoziri (Manfreda et al., 2018). Ọzọkwa, mmepe nke algọridim kwesịrị ekwesị nke na-amata pikselụ na-egosipụta ahihia na onyonyo dijitalụ ma wepụ ihe ndabere adịghị mkpa n'oge eserese ahihia UAV (Gaˇsparovi'c et al., 2020; Hamylton et al., 2020; H. Huang et al. , 2018, 2020; Lopez-' Granados et al., 2016). A na-anabata nyocha agbakwunyere na nnabata nke usoro nkewa semantic na njirimara osisi, nhazi akwụkwọ, na nkewa ọrịa (Fuentes-Pacheco et al., 2019; Kerkech et al., 2020).
Ụyọkọ 2. Akwụkwọ ndị dị na ụyọkọ a lekwasịrị anya n'akụkụ dị iche iche nke drones ọrụ ugbo. Ejikọtara na phenotyping dịpụrụ adịpụ, Sankaran et al. (2015) enyochala ikike nke iji ihe ngosi ikuku dị ala, nke dị elu na UAV maka ngwa ngwa phenotyping nke ihe ọkụkụ n'ọhịa, ha na-arụ ụka na, ma e jiri ya tụnyere ikpo okwu na-ahụ maka ala, obere UAV nwere ihe mmetụta zuru oke na-enye ọtụtụ uru. , dị ka ọ dị mfe ịnweta ubi, data dị elu, nchịkọta data nke ọma,
nyocha ngwa ngwa nke ọnọdụ uto ubi, yana ụgwọ ọrụ dị ala. Otú ọ dị, ndị na-ede akwụkwọ kwukwara na ngwa dị irè nke UAV maka phenotyping ubi na-adabere na isi ihe abụọ dị mkpa, ya bụ, atụmatụ UAV (dịka, nchekwa, nkwụsi ike, ọnọdụ, nnwere onwe) na njirimara sensọ (dịka, mkpebi, ịdị arọ, spectral wavelengths, field). nke anya). Haghighattalab et al. (2016) tụpụtara pipeline nhazi onyonyo nke ọkara akpaaka iji weghachite data ọkwa-ibe sitere na onyonyo UAV wee mee ka usoro ọmụmụ ahụ dịkwuo elu. Holman et al. (2016) mepụtara elu
throughput field phenotyping system na pụta ìhè na UAV nwere ike ịnakọta àgwà, ụda olu, data phenotypic dabeere na ubi, yana na ngwaọrụ ahụ dị irè maka nnukwu mpaghara na gafee ebe dị iche iche.
Dị ka ntule mkpụrụ osisi bụ ozi dị oke mkpa dị oke mkpa, ọkachasị mgbe enwere ya n'oge, enwere ike maka UAV iji nye nha ubi niile wee nweta data dị elu nke ọma (Daakir et al., 2017; Demir et al., 2018 ; Enciso et al., 2019; Kulbacki et al., 2018; Pudelko et al., 2012). N'okwu a, Jin et al. (2017) jiri ohere onyonyo dị elu nwetara site na UAV n'ogo dị ala iji zụlite na nyochaa usoro maka ịkọ njupụta osisi ọka wit na ọkwa mmalite. Dị ka ndị na-ede akwụkwọ si kwuo, UAVs meriri njedebe nke usoro rover nke nwere igwefoto ma na-anọchite anya usoro na-adịghị emerụ ahụ iji chọpụta njupụta osisi na ihe ọkụkụ, na-ekwe ka ndị ọrụ ugbo nweta nnukwu mmepụta ihe dị mkpa maka phenotyping ubi n'adabereghị na traktị nke ala. Li et al. (2016) anakọtara narị narị onyonyo stereo nwere mkpebi dị oke elu site na iji sistemụ dabere na UAV iji tụọ oke ọka ọka, gụnyere oke mkpuchi na biomass dị n'elu ala. N'ikpeazụ, Yue et al. (2017) chọpụtara na ịdị elu ihe ọkụkụ ekpebisiri ike site na UAV nwere ike welie ntule biomass n'elu ala (AGB).
Ụzọ iji nyochaa uto ihe ọkụkụ bụ echiche nke ịmepụta ụdị elu ihe ọkụkụ (Bendig et al., 2014, 2015; Holman et al., 2016; Panday, Shrestha, et al., 2020; Sumesh et al., 2021). Ọtụtụ nchọpụta mere ka ọ pụta ìhè na ọ ga-ekwe omume nke onyonyo ewepụtara na UAV iji weghara ịdị elu osisi na nyochaa uto ha. Dịka ọmụmaatụ, Bendig et al. (2013) kọwara mmepe nke ụdị ihe ọkụkụ dị iche iche nke oge a na mkpebi dị oke elu nke na-erughị 0.05 m site na iji UAV. Ha bu n'obi ịchọpụta ihe ọkụkụ
mgbanwe uto na ndabere ya na ọgwụgwọ ihe ọkụkụ, cultivar, na nrụgide. Bendig et al. (2014) jiri UAV mee atụmatụ biomass dị ọhụrụ na nke akọrọ dabere na ịdị elu osisi ewepụtara site na ụdị ihe ọkụkụ wee chọpụta na, n'adịghị ka ikpo okwu ikuku na nyocha laser nke ụwa, ihe onyonyo dị elu sitere na UAV nwere ike ịbawanye izi ezi nke ịkpụzi ịdị elu osisi maka uto dị iche iche. ogbo. N'otu aka ahụ, Geipel et al. (2014) jiri UAV na nyocha ha nweta ihe onyonyo
ihe ndekọ data maka ọka ọka na-amịpụta amụma n'usoro uto atọ dị iche iche site na mmalite ruo n'etiti oge wee kwubie na nchikota nke ihe nlere anya na mbara igwe dabere na onyonyo ikuku na ụdị elu ihe ọkụkụ bụ usoro dabara adaba maka ịkọ mkpụrụ ọka n'etiti oge. N'ikpeazụ, Gnadinger ¨ na Schmidhalter (2017) nyochaa uru nke UAV na nkenke phenotyping na pụta ìhè na ojiji nke a technology nwere ike welie ugbo oru na-enyere ubi experimentation maka ozuzu na agronomic nzube. N'ozuzu, anyị na-ahụ na akwụkwọ ndị dị na ụyọkọ 2 na-elekwasị anya na uru bụ isi nke UAV n'ime ime obodo.
phenotyping, mpụta atụmatụ, ihe ubi n'elu ịṅomi, na osisi agụta. Ọmụmụ ihe n'ọdịnihu nwere ike igwu miri emi site n'ịmepụta ụzọ ọhụrụ maka phenotyping dịpụrụ adịpụ nke nwere ike ịmepụta ma kwalite nhazi nke data a na-ahụ anya (Barabaschi et al., 2016; Liebisch et al., 2015; Mochida et al., 2015; S. Zhou et al. ., 2021). Na mgbakwunye, arụmọrụ nke sensọ IoT etinyere na UAVs yana azụmaahịa dị n'etiti ọnụ ahịa ha, ọrụ ha, na nkenke nke nleba anya mkpụrụ kwesịrị ka enyocha ya na
ọdịnihu (Ju & Son, 2018a, 2018b; Xie & Yang, 2020; Yue et al., 2018). N'ikpeazụ, ọ dị mkpa ịmepụta usoro nhazi ihe oyiyi dị mma nke nwere ike ịmepụta ozi a pụrụ ịdabere na ya, mee ka ọ dị mma na mmepụta ugbo, ma belata ọrụ ịgụ akwụkwọ ntuziaka nke ndị ọrụ ugbo (RU Khan et al., 2021; Koh et al., 2021; Lin & Guo, 2020; C. Zhang et al., 2020).
Ụyọkọ 3. Mbipụta ndị dị na ụyọkọ a na-atụle ụdị dị iche iche nke usoro onyogho maka nhụta anya nke akụrụngwa ugbo eji na nyiwe UAV. N'akụkụ a, ihe ngosi okpomọkụ na-enye ohere nlekota nke okpomọkụ dị elu iji gbochie mmebi ihe ọkụkụ na ịchọpụta nrụgide ụkọ mmiri ozuzo n'oge (Awais et al., 2022; García-Tejero et al., 2018; Sankaran et al., 2015; Santesteban et al., 2017; Yeom, 2021). Baluja et al. (2012) kwusiri ike na iji igwefoto multispectral na thermal na-abanye n'ụgbọ mmiri
UAV nyeere ndị nyocha aka inweta onyonyo dị elu wee chọpụta ọkwa mmiri vine. Nke a nwere ike ịba uru iji mepụta ụdị nhazi oge mmiri dị ọhụrụ site na iji data nhụta anya (Baluja et al., 2012). N'ihi na
ikike ibu oke nke UAV, Ribeiro-Gomes et al. (2017) tụlere ntinye nke igwefoto ọkụ na-adịghị mma n'ime UAVS iji chọpụta nrụgide mmiri na osisi, nke na-eme ka ụdị UAV dị irè ma dị irè karịa omenala satịlaịtị dabeere na anya anya na UAV nke nwere igwefoto okpomọkụ jụrụ oyi. Dị ka ndị odee si kwuo, igwefoto okpomọkụ na-adịghị mma dị ọkụ karịa igwefoto jụrụ oyi, na-achọ nhazi kwesịrị ekwesị. Gonzalez-Dugo et al. (2014) gosiri na ihe onyonyo okpomọkụ na-emepụta maapụ mbara ala nke ihe mmetụta nrụgide mmiri ihe ọkụkụ maka ịlele ọnọdụ mmiri na ịkọwa nrụgide mmiri n'etiti na n'ime ubi mkpụrụ osisi citrus. Gonzalez-Dugo et al. (2013) na Santesteban et al. (2017) nyochara iji ihe onyonyo okpomọkụ UAV dị elu iji tụọ ọnọdụ mgbanwe mmiri nke ubi mkpụrụ osisi na ubi-vine.
Ihe onyonyo onyonyo nwere ike inye nnukwu data ma e jiri ya tụnyere onyonyo RGB ọdịnala (Red, Green na Blue) (Ad˜ ao et al., 2017; Navia et al., 2016). Ihe omuma a di iche iche, tinyere data gbasara ohere, nwere ike inye aka na nhazi, nkewa, amuma, amuma, na ebumnuche nchọpụta (Berni et al., 2009b). Dị ka Candiago et al. (2015), UAVbased multispectral imaging nwere ike inye aka n'ụzọ dị ukwuu na ntule ihe ọkụkụ na kpọmkwem ọrụ ugbo dị ka ihe a pụrụ ịdabere na ya na nke ọma. Ọzọkwa,
Khaliq et al. (2019) mere ntụnyere n'etiti satịlaịtị na UAVbased multispectral imaging. Onyonyo ndị dabere na UAV rụpụtara ka ọ bụrụ nke ziri ezi n'ịkọwa mgbanwe ubi vine yana maapụ ike maka ịnọchite anya ahịhịa ahịhịa. Na nkenke, akụkọ dị na ụyọkọ a na-atụle ntinye nke thermal and multispectral sensọ n'ime UAV ọrụ ugbo. N'ihi ya, a chọrọ nyocha ọzọ iji ghọta otú e nwere ike isi jikọta ihe ngosi thermal na multispectral na AI
usoro (dịka ọmụmaatụ, mmụta miri emi) iji chọpụta nrụgide osisi (Ampatzidis et al., 2020; Ampatzidis & Partel, 2019; Jung et al., 2021; Santesteban et al., 2017; Syeda et al., 2021). Nghọta ndị dị otú ahụ ga-enyere aka hụ na nchọpụta nke ọma na nke ziri ezi yana nlekota nke uto osisi, nchekasị, na phenology (Buters et al., 2019; Cao et al., 2020; Neupane & BaysalGurel, 2021; L. Zhou et al., 2020).
Ụyọkọ 4. Ụyọkọ a nwere akwụkwọ asaa na-agbagharị gburugburu ọrụ dị oke mkpa nke onyonyo spectral na ihe ngosi hyperspectral n'ịkwado omume ọrụ ugbo. Ihuenyo hyperspectral eguzobewo onwe ya dị ka usoro ntụgharị uche dịpụrụ adịpụ nke na-eme ka ọnụọgụ ọnụọgụgụ nke usoro ụwa (Schaepman et al., 2009) . Iji mee ka ọ dịkwuo mma, ọ na-enyere aka ịchọpụta ihe ndị dị n'elu, ọnụ ọgụgụ nke (ndị ikwu) mkpokọta, na ọrụ nke elu akụrụngwa n'ike-n'ike
n'ime pikselụ agwakọtara (Kirsch et al., 2018; Zhao et al., 2022). N'ikwu ya n'ụzọ ọzọ, mkpebi dị elu dị elu nke sistemu hyperspectral na-enye na-enyere aka nleba anya ziri ezi nke akụkụ dị iche iche, dị ka ihe anaghị eri anụ ma ọ bụ ọdịnaya mmiri akwụkwọ (Suomalainen et al., 2014). Ndị nchọpụta nọ na ụyọkọ a nyochara akụkụ dị iche iche nke usoro ndị dị otú ahụ. N'etiti ndị ọzọ, Aasen et al. (2015b) nyere ụzọ pụrụ iche maka inweta ozi hyperspectral akụkụ atọ site na fechaa.
Igwefoto foto ejiri na UAV maka nlekota ahịhịa. Lucieer et al. (2014) tụlere nhazi, mmepe, na ọrụ ikuku nke UAS hyperspectral novel yana nhazi, nyocha, na nkọwa nke data oyiyi gbakọtara na ya. N'ikpeazụ, Honkavaara et al. (2013b) mepụtara usoro nhazi zuru oke maka onyonyo onyonyo dabere na FabryPerot interferometer wee gosipụta ojiji ya na usoro atụmatụ atụmatụ biomass maka ọrụ ugbo ziri ezi. Ụzọ ndị nwere ike ime n'ọdịnihu maka ụyọkọ a dị ugbu a gụnyere imesi ike mkpa ọ dị maka mmelite teknụzụ na teknụzụ sensọ (Aasen et al., 2015b) yana mkpa maka itinye na ịkwalite teknụzụ nkwado, kpọmkwem nnukwu data na nyocha (Ang & Seng, 2021; Radoglou). -Grammatikis et al., 2020; Shakoor et al., 2019). Nke ikpeazụ a na-esite na data na-eto eto mgbe niile site na sensọ dị iche iche etinyere na ọrụ ugbo mara mma (C. Li & Niu, 2020; A. Rejeb et al., 2022; Y. Su & Wang, 2021).
Ụyọkọ 5. Mbipụta ndị dị na ụyọkọ a nyochara ngwa 3Dmapping dabere na drones. Iji drones maka eserese 3D nwere ike ibelata ọrụ ubi dị mgbagwoju anya yana ịbawanye arụmọrụ nke ukwuu (Torres-Sanchez 'et al., 2015). Isiokwu ise dị na ụyọkọ ahụ lekwasịrị anya na ngwa nlekota ihe ọkụkụ. Dịka ọmụmaatụ, iji nweta data akụkụ atọ gbasara ebe mkpuchi, ịdị elu osisi na olu okpueze, Torres-Sanchez ' et al. (2015) jiri teknụzụ UAV mepụta ụdị elu dijitalụ wee bịaruo nso nyocha ihe onyonyo dabere na ihe (OBIA). Ọzọkwa, Zarco-Tejada et al. (2014) ọnụ ọgụgụ osisi dị elu site na ijikọ teknụzụ UAV na ụzọ nrụgharị foto akụkụ atọ. Jim'enez-Brenes Lopez-Granados, De Castro, et al. (2017) gosiputara usoro ohuru maka otutu oge, nlekota oru 3D nke otutu osisi oliv site na ijikota teknụzụ UAV na usoro OBIA di elu. Ụzọ na-atọ ụtọ maka ọrụ ga-eme n'ọdịnihu na ụyọkọ a gụnyere ma ọ bụ imeziwanye ugbu a
usoro (Zarco-Tejada et al., 2014) maka ebumnuche imepụta elu dijitalụ (Ajayi et al., 2017; Jaud et al., 2016), dị ka OBIA (de Castro et al., 2018, 2020; Ventura et al. , 2018), na nwughari foto ma ọ bụ ịmepụta ụzọ ọhụrụ (Díaz-Varela et al., 2015; Torres-S'anchez et al., 2015).
Ụyọkọ 6. Ụyọkọ a na-atụle ọrụ nke drones na nlekota oru ugbo. UAV nwere ike imeju ma merie adịghị ike nke satịlaịtị na onyonyo ụgbọ elu. Dịka ọmụmaatụ, ha nwere ike ịnye mkpebi dị elu na nso nsonye onyonyo oge na obere mmanụ ọkụ ma ọ bụ ihe ịma aka ịnya ụgbọ elu, na-ebute nleba anya mgbe niile na ezigbo oge na nkwalite n'ime mkpebi (S. Herwitz et al., 2004). Ihe enyemaka ọzọ dị mkpa nke UAV bụ ikike ha ịnye data akọwapụtara saịtị maka ọrụ ugbo ziri ezi ma ọ bụ ọrụ ubi akọwapụtara saịtị dị ka mkpebi ha dị elu, data zuru ezu gbasara ụdị dị iche iche na-enyere ndị ọrụ ugbo aka kewaa ala ahụ n'ime akụkụ otu ma mesoo ha ya (Hunt et al. , 2010; CC Lelong et al., 2008; Primicerio et al., 2012). Ụdị onyunyo ọrụ ugbo dabere na UAV nwere ike ịkwado nlekota nchekwa nri na ime mkpebi (SR Herwitz et al., 2004). Iji kwalite nyocha na onyunyo ọrụ ugbo, ọ bụghị naanị nkwalite na sensọ, UAVs, na teknụzụ ndị ọzọ metụtara ya na nkwukọrịta ha na ụzọ mbufe data dị mkpa (Ewing et al., 2020; Shuai et al., 2019), kamakwa ijikọ drones dị iche iche. teknụzụ maka ịkwalite ọrụ dị iche iche n'ihe metụtara ọrụ ugbo mara mma, dị ka nlekota, onyunyo ọrụ ugbo, na ime mkpebi, bụ mpaghara nyocha dị elu (Alsamhi et al., 2021; Popescu et al., 2020; Vuran et al., 2018). N'akụkụ a, IoT, WSNs na nnukwu data na-enye ike mmekọ na-atọ ụtọ (van der Merwe et al., 2020). Ọnụ ego mmejuputa iwu, nchekwa ego, nrụpụta ike, na nchekwa data so na mpaghara enyochabeghị maka njikọ dị otú ahụ (Masroor et al., 2021).
Mba na ụlọ akwụkwọ agụmakwụkwọ
Nzọụkwụ ikpeazụ gụnyere nyocha nke mba si na njikọ agụmakwụkwọ nke ndị edemede. Site na nyocha a, anyị chọrọ ịghọta nke ọma nkesa mpaghara nke ndị ọkà mmụta na-enye aka na ngwa nke drones na ọrụ ugbo. Ọ bụ ihe kwesịrị ịrịba ama ịhụ ụdị dị iche iche nke mba na ụlọ akwụkwọ agụmakwụkwọ. Site n'echiche obodo, USA, China, India, na Ịtali nọ n'ọkwa n'elu ndepụta n'ihe gbasara ọnụ ọgụgụ akwụkwọ (Table 7). Nke ugbu a
nyocha banyere drones ọrụ ugbo gbadoro ụkwụ na North America na mba Eshia, ọkachasị n'ihi itinye aka ha dị elu na ngwa ọrụ ugbo ziri ezi. Dịka ọmụmaatụ, na USA, a na-eme atụmatụ ahịa nke drones ugbo na 841.9 nde USD n'afọ 2020, na-aza ihe dịka 30% nke oke ahịa ahịa ụwa (ReportLinker, 2021). N'ịkwado dị ka akụ na ụba kasị ukwuu n'ụwa, a na-ebu amụma na China ga-eru n'ahịa ahịa dị ihe dị ka ijeri USD 2.6 n'afọ 2027. Obodo a na-achọsi ike maka drones ọrụ ugbo iji merie nsogbu mmepụta ihe ma nweta mkpụrụ dị mma, nkwụsị ọrụ, na ntinye mmepụta dị nta. Agbanyeghị, nnabata nke teknụzụ na China bụkwa ihe na-ebutekwa ya site na ihe ndị dị ka ọnụ ọgụgụ ndị mmadụ na mkpa ọ dị imelite ma melite usoro nlekọta ihe ọkụkụ dị ugbu a.
Mba kacha arụpụta ihe na mahadum/ụlọ ọrụ na-enye aka
nyocha metụtara ugbo ugbo drone.
n'usoro | mba |
1 | USA |
2 | China |
3 | India |
4 | Italy |
5 | Spain |
6 | Germany |
7 | Brazil |
8 | Australia |
9 | Japan |
10 | United Kingdom |
n'usoro | Ụlọ akwụkwọ mahadum / Ụlọ ọrụ |
1 | Academylọ akwụkwọ sayensị China |
2 | Ministry of Agriculture of People's Republic of China |
3 | Nnukwu Council of Scientific Investigations |
4 | Mahadum Texas A&M |
5 | Ụlọ ọrụ ugbo nke China |
6 | Ọrụ nyocha ọrụ ugbo USDA |
7 | CSIC - Ụlọ ọrụ nke Agricultura Sostenible IAS |
8 | Purdue University |
9 | Researchlọ Ọrụ Nyocha Mba |
10 | Mahadum Ndị Ọrụ Ugbo na South China |
Site na mahadum na nhazi nhazi, ụlọ akwụkwọ sayensị Chinese kacha elu na ndepụta n'ihe gbasara ọnụ ọgụgụ akwụkwọ, ndị Ministry of Agriculture of the People's Republic of China na Consejo Superior de Investigaciones Científicas sochiri ya. Ụlọ akwụkwọ sayensị nke China bụ ndị odee Liao Xiaohan na Li Jun nọchitere anya ya; Han Wenting na-anọchite anya Ministri Ọrụ Ugbo nke Republic of China; na Consejo Superior de Investigaciones Científicas nọchitere anya Lopez-Granados, 'F. na Pena, ˜ Josse María S. Site na USA, mahadum dị ka Texas A&M University na Purdue University chọtara ha.
kwuo. The mahadum nwere ọnụ ọgụgụ kasị elu nke akwụkwọ na njikọ ha na-egosi na fig. 4. Ọzọkwa, ndepụta a gụnyere ụlọ ọrụ dị ka Consiglio Nazionale delle Ricerche na Consejo Superior de Investigaciones Científicas na-arụsi ọrụ ike na nchọpụta sayensị, ma ọ bụghị ụlọ akwụkwọ agụmakwụkwọ. .
Nhọrọ anyị gụnyere akwụkwọ akụkọ dị iche iche, gụnyere ihe fọrọ nke nta ka ọ bụrụ data niile dịnụ. Dị ka e gosiri na Tebụl 8, Remote Sensing nwere isiokwu 258 nọ n'elu, na-esote Journal of Intelligent and Robotic Systems: Theory and Applications with 126 na Kọmputa na Electronics na Agriculture nwere isiokwu 98. Ọ bụ ezie na Sensing Remote na-elekwasịkarị anya na ngwa na mmepe nke drones, Kọmputa na Electronics na Agriculture na-ekpuchi ọganihu na ngwaike kọmputa, ngwanrọ, ngwá electronic, na usoro nchịkwa na ọrụ ugbo. Ebe ndị na-agafe agafe, dị ka IEEE Robotics na Automation Letters nwere akwụkwọ 87 na IEEE Access nwere akwụkwọ 34, bụkwa ụlọ ahịa mbụ n'ọhịa. Ụlọ ọrụ iri na ise kachasị elu ejirila akwụkwọ 959 nyere aka na akwụkwọ ahụ, nke bụ ihe dịka 20.40% nke akwụkwọ niile. Ntụle nkọwa nke akwụkwọ akụkọ na-enyere anyị aka inyocha mkpa na myirịta dị n'etiti akwụkwọ. Nchịkọta nchịkọta akụkọ na-enye ụyọkọ atọ, dị ka egosiri na Fig. 5. Ụyọkọ na-acha uhie uhie nwere akwụkwọ akụkọ dị ka Remote Sensing, Kọmputa na Electronics na Agriculture, Sensors,
na International Journal of Remote Sensing. Ụlọ ahịa ndị a niile bụ akwụkwọ akụkọ a ma ama nke ukwuu n'akụkụ nhụta anya na ọrụ ugbo ziri ezi. Ụyọkọ akwụkwọ ndụ akwụkwọ ndụ nwere akwụkwọ akụkọ na-emekọ ihe gbasara robotik, dị ka Journal of Intelligent and Robotic Systems: Theory and Applications, IEEE Robotics and Automation Letters, IEEE Access, and Drones. Ụlọ ahịa ndị a na-ebipụtakarị akwụkwọ na akpaaka ma bara uru maka ndị injinia ọrụ ugbo. Emebere ụyọkọ ikpeazụ site na akwụkwọ akụkọ metụtara agronomy na injinịa ugbo, dị ka Agronomy na International Journal of Agricultural and Biological Engineering.
Akwụkwọ akụkọ 15 kacha elu na nyocha metụtara drone metụtara ugbo.
n'usoro | Akwụkwọ akụkọ | Gụọ |
1 | Remensing mmetụta | 258 |
2 | Akwụkwọ akụkọ nke Intelligent na Robotic Systems: Theory and ngwa | 126 |
3 | Kọmputa na Eletrọnịkị na Agriculture | 98 |
4 | Akwụkwọ ozi IEEE Robotics na akpaaka | 87 |
5 | sensọ | 73 |
6 | Akwụkwọ akụkọ mba ụwa nke nhụta anya | 42 |
7 | Nkenke Agriculture | 41 |
8 | drones | 40 |
9 | Agụmakwụkwọ | 34 |
10 | Nweta IEEE | 34 |
11 | Akwụkwọ akụkọ International nke Advanced Robotic Systems | 31 |
12 | Akwụkwọ akụkọ International nke Agricultural and Biological Engineering | 25 |
13 | KWA ONYE | 25 |
14 | Akwụkwọ akụkọ nke Field Robotics | 23 |
15 | Biosystems Engineering | 23 |
mmechi
Summary
N'ime ọmụmụ ihe a, anyị chịkọtara ma nyochaa nyocha dị ugbu a na drones ugbo. N'itinye usoro dị iche iche bibliometric n'ọrụ, anyị gbalịsiri ike inweta nghọta ka mma maka nhazi ọgụgụ isi nke nyocha metụtara drone. Na nchikota, nyochaa anyị na-enye ọtụtụ onyinye site n'ịchọpụta na ikwurịta okwu ndị dị na akwụkwọ, na-ekpughe ụyọkọ ihe ọmụma mgbe ha na-emepụta obodo ndị yiri ya na mpaghara nke drones, na-akọwapụta nchọpụta mbụ, na-atụ aro ntụziaka nyocha n'ọdịnihu. N'okpuru ebe a, anyị na-akọwapụta isi ihe nchoputa nke nyocha banyere mmepe nke drones ugbo:
• Akwụkwọ akụkọ n'ozuzu etoola ngwa ngwa ma dọta mmasị dị ukwuu n'ime afọ iri gara aga, dị ka e gosiri site na ịrị elu nke ọnụ ọgụgụ nke isiokwu mgbe 2012. Ọ bụ ezie na ubi ihe ọmụma a ka na-enweta ntozu ya zuru oke (Barrientos et al., 2011; Maes). & Steppe, 2019), ọtụtụ ajụjụ ka azabeghị. Dịka ọmụmaatụ, ịba uru nke drones na ọrụ ugbo ime ụlọ ka na-emeghe maka arụmụka (Aslan et al., 2022; Krul et al., 2021; Rold'an et al., 2015). Mgbagwoju anya nke ihe nkiri na ọnọdụ onyonyo dị iche iche (dịka ọmụmaatụ, onyinyo na ọkụ) nwere ike bute ọdịiche dị na klaasị dị elu (Yao et al., 2019). Ọbụlagodi na usoro nyocha ndị mechara, a mara ndị nyocha aka ikpebi atụmatụ ụgbọ elu kacha mma dabere na ọnọdụ dị iche iche yana ogo onyonyo achọrọ (Soares et al., 2021; Tu et al.,
2020).
• Anyị na-achọpụta na ubi ahụ enweela ọganihu site na ịmepụta usoro UAV dị mma iji tinye usoro AI, dị ka mmụta igwe na mmụta miri emi na nhazi nke drones ugbo (Bah et al., 2018; Kitano et al., 2019; Maimaitijiang et al. , 2020; Mazzia et al., 2020; Tetila et al., 2020).
• Nnyocha na drones ọrụ ugbo tụlere n'ụzọ dịpụrụ adịpụ site n'ịchọgharị ike nke teknụzụ na nlekota gburugburu ebe obibi, njikwa ihe ọkụkụ, na njikwa ahihia (ụyọkọ 1) yana phenotyping dịpụrụ adịpụ ma na-emepụta atụmatụ (ụyọkọ 2). Otu ihe ọmụmụ nwere mmetụta na drones ugbo gụnyere Austin (2010), Berni et al. (2009) a, Herwitz et al. (2004), Nex na Remondino (2014), na Zhang and Kovacs (2012). Ọmụmụ ihe ndị a mepụtara ndabere echiche nke nyocha metụtara drone n'ihe gbasara ọrụ ugbo.
• N'ihe metụtara usoro ahụ, anyị chọpụtara na ọtụtụ n'ime nyocha ndị e mere ruo ugbu a bụ nke usoro nhazi, echiche, ma ọ bụ ọmụmụ nyocha dabere (Inoue, 2020; Nex & Remondino, 2014; Per'erez-Ortiz et al. , 2015; Yao et al., 2019). Anyị na-ahụkwa na enweghị usoro ndị gbara ọkpụrụkpụ, qualitative na nke ọmụmụ ihe na-arụ ọrụ n'ịchọpụta drones ọrụ ugbo.
• N'oge na-adịbeghị anya, isiokwu ndị metụtara ọrụ ugbo ziri ezi, usoro AI, viticulture ziri ezi, na nyocha nrụgide mmiri adọtawo nlebara anya dị ukwuu (Espinoza et al., 2017; Gomez-Cand 'on ' et al., 2016; Matese et al., 2015; Matese & Di Gennaro, 2018, 2021; Z. Zhou et al., 2021). Nyochaa nke ọma nke ụyọkọ nyocha n'ime oge abụọ dị iche iche, 1990–2010 na 2011–2021, na-ekpughe ọganihu nke nhazi ọgụgụ isi ngalaba. Oge site na 1990 ruo 2010 mejupụtara iwulite echiche etiti na echiche nke drones, nke pụtara ìhè site na mkparịta ụka nke imewe, mmepe na mmejuputa UAV. N'ime oge nke abụọ, nyocha nyocha na-agbasawanye na ọmụmụ ihe mbụ, na-eme mgbalị iji mee ka UAV jiri okwu na-arụ ọrụ ugbo. Anyị hụkwara ọtụtụ ọmụmụ nke na-ekwu maka ngwa drone na ọrụ onyonyo na ọrụ ugbo ziri ezi.
n'usoro | Akwụkwọ akụkọ | Gụọ |
1 | Remensing mmetụta | 258 |
2 | Akwụkwọ akụkọ nke Intelligent na Robotic Systems: Theory and | 126 |
ngwa | ||
3 | Kọmputa na Eletrọnịkị na Agriculture | 98 |
4 | Akwụkwọ ozi IEEE Robotics na akpaaka | 87 |
5 | sensọ | 73 |
6 | Akwụkwọ akụkọ mba ụwa nke nhụta anya | 42 |
7 | Nkenke Agriculture | 41 |
8 | drones | 40 |
9 | Agụmakwụkwọ | 34 |
10 | Nweta IEEE | 34 |
11 | Akwụkwọ akụkọ International nke Advanced Robotic Systems | 31 |
12 | Akwụkwọ akụkọ International nke Agricultural and Biological Engineering | 25 |
13 | KWA ONYE | 25 |
14 | Akwụkwọ akụkọ nke Field Robotics | 23 |
15 | Biosystems Engineering | 22 |
pụtara
Ewere ndị ọkà mmụta, ndị ọrụ ugbo, ndị ọkachamara n'ihe gbasara ọrụ ugbo, ndị na-ahụ maka ihe ọkụkụ, na ndị na-emepụta usoro UAV chepụtara ma duzie nlebanya nke bibliometric anyị. Maka ndị odee mara nke ọma, nke a bụ otu n'ime nyocha izizi nke mebere nyocha nke bibliometric miri emi.
ngwa drone n'ọrụ ugbo. Anyị emeela nyocha zuru oke nke otu ihe ọmụma a, na-eji ntụle na nyocha nke akwụkwọ. Mgbalị anyị iji kọwaa usoro ọgụgụ isi nke nyocha drone na-enyekwa nghọta ọhụrụ maka ndị gụrụ akwụkwọ. Nleba anya nke ọma nke mkpụrụokwu ndị e ji mee ihe n'oge na-ekpughe ebe ndị na-ekpo ọkụ na ebe nyocha dị na akwụkwọ ndị metụtara drone. Ọzọkwa, anyị na-enye ndepụta nke ihe ọmụmụ ndị a kapịrị ọnụ iji chọpụta ọrụ nyocha kachasị emetụta nke emechara n'ọhịa. Nchọpụta isiokwu na isiokwu nwere ike n'ihi ya nye mmalite siri ike iji kpughee ọtụtụ ụzọ maka ọmụmụ ihe n'ọdịnihu.
N'ụzọ dị mkpa, anyị kpughere ụyọkọ na-ekewa ọrụ ndị yiri ya wee kọwapụta na nsonaazụ ya. Ọmụmụ ihe nkewa na ụyọkọ na-enyere aka ịghọta usoro ọgụgụ isi nke nyocha UAV. N'ụzọ doro anya, anyị chọpụtara ụkọ ọmụmụ nke na-enyocha ihe nkuchi drones
na ihe mgbochi na ọrụ ugbo (lee Tebụl 9). Ndị na-eme nchọpụta n'ọdịnihu nwere ike ileba anya na oghere a nwere ike ime site n'ime nyocha dị omimi nke na-enyocha ihe ntinye drones na ọrụ ugbo dị iche iche na ọnọdụ ihu igwe. Ọzọkwa, nyocha dabere na nyocha gbasara ịdị irè nke drones kwesịrị iji ezigbo data sitere n'ọhịa kwadoo. Ọzọkwa, itinye aka na ndị ọrụ ugbo na ndị njikwa na nyocha agụmakwụkwọ ga-aba uru maka ma usoro mmụta na ọganihu bara uru nke nyocha drone. Anyị nwekwara ike ịchọpụta ndị nchọpụta a ma ama na onyinye ha, nke bara uru n'ihi na ịmara banyere ọrụ seminarị n'oge na-adịbeghị anya nwere ike inye ụfọdụ nduzi maka mgbalị agụmakwụkwọ n'ọdịnihu.
Isiokwu 9
Ihe mgbochi nnabata UAV.
Ihe mgbochi | Description |
Nche data | Nchekwa cyber bụ nnukwu ihe ịma aka maka mmejuputa Ihe ngwọta IoT (Masroor et al., 2021). |
Interoperability na mwekota | Teknụzụ dị iche iche dịka UAV, WSN, IoT, wdg. kwesịrị ejikọta ma nyefee data nke mụbaa ọkwa mgbagwoju anya (Alsamhi et al., 2021; Popescu et al., 2020; Vuran et al., 2018). |
Ọnụ mmejuputa | Nke a bụ kpọmkwem maka obere ndị ọrụ ugbo na maka iji teknụzụ dị iche iche na-emepe emepe ( Masroor et al., 2021). |
Ihe omuma nke oru na ọkachamara | Achọrọ ndị na-anya ụgbọ elu nwere nkà iji rụọ ọrụ UAV. Ọzọkwa, na-emejuputa atumatu dị iche iche ịkpụ-ọnụ teknụzụ chọrọ ndị ọrụ nwere nkà (YB Huang et al., 2013; Tsouros et al., 2019). |
Ike injin na ụgbọ elu Na oge | Enweghị ike ịwa drones ruo ogologo awa na mkpuchi nnukwu mpaghara (Hardin & Hardin, 2010; Laliberte et al., 2007). |
Nkwụsi ike, ntụkwasị obi, na imeghari | Drone anaghị eguzosi ike n'oge ọnọdụ ihu igwe ọjọọ (Hardin & Hardin, 2010; Laliberte et al., 2007). |
Ịkwụ ụgwọ njedebe na àgwà sensọ | Drones nwere ike ibu oke ibu na-eduga ike nke ibu ihe mmetụta dị ala (Nebiker et al., 2008). |
ụkpụrụ | Dị ka drones nwere ike ịdị ize ndụ yana, enwere ike ụkpụrụ na mpaghara ụfọdụ (Hardin & Jensen, 2011; Laliberte & Rango, 2011). |
Ihe ọmụma nke ndị ọrụ ugbo na mmasị | Dị ka teknụzụ ndị ọzọ dị egwu, drones '. mmejuputa iwu na-aga nke ọma chọrọ nka yana kwa sonye na ejighị n'aka (Fisher et al., 2009; Lambert et al., 2004; Stafford, 2000). |
Ebe ọ bụ na ọ dị mkpa ka a na-eji akụrụngwa dịnụ nke ọma na-eme ihe na-emepụta ihe, ndị ọrụ ugbo nwere ike iji drones mee ihe iji hụ na nyocha nke ubi ha ngwa ngwa, nke ziri ezi na nke dị ọnụ ala. Nkà na ụzụ ahụ nwere ike ịkwado ndị ọrụ ugbo iji chọpụta ọnọdụ ihe ọkụkụ ha ma chọpụta ọnọdụ mmiri, oge ntori, ahụhụ ụmụ ahụhụ na mkpa nri. Ikike nleba anya nke drones nwere ike inye ndị ọrụ ugbo data dị mkpa iji tụọ anya okwu n'oge mmalite ma mee ngwa ngwa dabara adaba. Otú ọ dị, uru nke nkà na ụzụ nwere ike ime naanị ma ọ bụrụ na edozi nsogbu ndị ahụ nke ọma. Na ìhè nke
nsogbu dị ugbu a gbasara nchekwa data, okwu teknụzụ sensọ (dịka, ntụkwasị obi ma ọ bụ izi ezi nke nha), mgbagwoju anya nke njikọta, yana ọnụ ahịa mmejuputa iwu dị ukwuu, ọmụmụ ihe n'ọdịnihu ga-enyochakwa ikike teknụzụ, akụ na ụba na arụmọrụ nke ijikọ drones ugbo na igbubi ndị ọzọ. teknụzụ ọhụrụ.
-agaghị emeli
Ọmụmụ ihe anyị nwere ọtụtụ adịghị ike. Nke mbụ, a na-ekpebi ihe nchoputa ahụ site na akwụkwọ ndị ahọpụtara maka nyocha ikpeazụ. Ọ na-esiri ike ijide ọmụmụ ihe niile dị mkpa metụtara drones ugbo, ọkachasị ndị edepụtaghị na nchekwa data Scopus. Ọzọkwa, usoro nchịkọta data na-ejedebe na ntọala nke isiokwu ọchụchọ, nke nwere ike ọ gaghị agụnye ma mee ka nchọpụta na-enweghị isi. Ya mere, ọmụmụ ihe ga-eme n'ọdịnihu kwesịrị itinyekwu uche na isi okwu nke nchịkọta data ime
nkwubi okwu a pụrụ ịdabere na ya. Mmachi ọzọ metụtara akwụkwọ ọhụrụ nwere ọnụ ọgụgụ dị ala. Nyocha bibliometric gbadoro ụkwụ na akwụkwọ ndị mbụ ka ha na-enweta ọtụtụ nhota n'ime afọ. Ọmụmụ ihe n'oge na-adịbeghị anya chọrọ oge ụfọdụ iji dọta uche na ikpokọta ntụaka. N'ihi ya, ọmụmụ ihe na-adịbeghị anya nke na-eweta mgbanwe ngbanwe agaghị abanye n'ọrụ iri kachasị mkpa. Mmachi a juru ebe niile na nyocha nke ngalaba nyocha na-apụta ngwa ngwa dị ka drones ọrụ ugbo. Dị ka anyị na-agakwuru Scopus iji mụọ akwụkwọ maka ọrụ a, ndị nchọpụta n'ọdịnihu nwere ike ịtụle dị iche iche
ọdụ data, dị ka Weebụ nke Sayensị na IEEE Xplore, iji gbasaa mbara igwe ma kwalite usoro nyocha.
Ọmụmụ ihe ọmụmụ bibliometric nwere ike ịtụle isi mmalite ihe ọmụma dị mkpa dị ka akwụkwọ ọgbakọ, isiakwụkwọ, na akwụkwọ iji wepụta nghọta ọhụụ. N'agbanyeghị eserese na nyocha akwụkwọ zuru ụwa ọnụ na drones ugbo, nchoputa anyị ekpugheghị ihe kpatara nsonaazụ ndị ọkà mmụta sitere na mahadum. Nke a na-emeghe ụzọ maka mpaghara nyocha nke ọma n'ịkọwa nke ọma ihe kpatara na mahadum ụfọdụ na-arụpụta ihe karịa ndị ọzọ ma a bịa n'ime nyocha gbasara ọrụ ugbo.
drones. Tụkwasị na nke ahụ, ọmụmụ ihe n'ọdịnihu nwere ike inye nghọta banyere ikike nke drones iji mee ka ọrụ ugbo dịkwuo elu n'ụzọ dị iche iche dị ka nlekota gburugburu ebe obibi, njikwa ihe ọkụkụ, na nkewa ahịhịa dị ka ọtụtụ ndị nchọpụta gosipụtara (Chamuah & Singh, 2019; Islam et al., 2021; Popescu et al., 2020; J. Su, Liu, et al., 2018b). Ebe ọ bụ na nyocha ederede agaghị ekwe omume n'ihi ọnụ ọgụgụ dị elu nke akwụkwọ ahọpụtara, ọ dị mkpa maka nyocha akwụkwọ nhazi usoro nke na-enyocha ihe ndị ahụ.
ụzọ nyocha ejiri na itinye aka na ndị ọrụ ugbo na ọmụmụ ihe mbụ. Na nkenke, nyocha anyị nke nyocha drone na-ekpughe njikọ a na-adịghị ahụ anya nke ahụ ihe ọmụma a. Nlebanya a na-enyere aka ikpughe mmekọrịta dị n'etiti akwụkwọ ma nyochaa nhazi ọgụgụ isi nke mpaghara nyocha. Ọ na-egosipụtakwa njikọ dị n'etiti akụkụ dị iche iche nke akwụkwọ, dị ka mkpụrụokwu ndị odee, njikọ, na mba.
Nkwuwapụta nke mmasị asọmpi
Ndị ode akwụkwọ na-ekwupụta na ha enweghị mmasị gbasara ego asọmpi ma ọ bụ mmekọrịta onwe onye nke gaara emetụta ọrụ a kọrọ na akwụkwọ a.
Odide Ntụkwasị 1
AKWỤKWỌ-ABS-KEY (((drone* MA ọ bụ "ụgbọ elu na-enweghị mmadụ" MA ọ bụ uav* ma ọ bụ "usoro ụgbọ elu na-enweghị mmadụ"” ma ọ bụ uas MA Ọ BỤ “ụgbọ elu ejiri akwọ ụgbọ mmiri”) NA ( ugbo ma obu ugbo ma obu onye oru ugbo ma obu onye oru ugbo))) NA (Ewepụ (PUBYEAR, 2022)) NA (OKWU-TO (ASỤSỤ, "Bekee")).
References
Aasen, H., Burkart, A., Bolten, A., Bareth, G., 2015. Na-emepụta 3D hyperspectral ozi na fechaa UAV foto igwefoto maka nlekota ahịhịa: si
nhazi igwefoto na mmesi obi ike. ISPRS J. Foto foto. Sens dịpụrụ adịpụ 108, 245–259. https://doi.org/10.1016/j.isprsjprs.2015.08.002.
Abd-Elrahman, A., Pearlstine, L., Percival, F., 2005. Mmepe nke ụkpụrụ amata algọridim maka nchọpụta nnụnụ na-akpaghị aka site na onyonyo ụgbọ elu na-enweghị mmadụ.
Nyocha. Ozi Ala. Sci. 65 (1), 37–45.
Abdollahi, A., Rejeb, K., Rejeb, A., Mostafa, MM, Zailani, S., 2021. Netwọk sensọ ikuku na ọrụ ugbo: nghọta sitere na nyocha bibliometric. Nkwado 13 (21),
12011.
Aboutalebi, M., Torres-Rua, AF, Kustas, WP, Nieto, H., Coopmans, C., McKee, M., Ntụle nke ụzọ dị iche iche maka nchọpụta onyinyo na elu-mkpebi ngwa anya imagery na nwale nke onyinyo mmetụta na mgbako. nke NDVI, na evapotranspiration. Irrig. Sci. 37 (3), 407–429. https://doi.org/10.1007/s00271-018-0613-9.
Adao, ˜ T., Hruˇska, J., Padua, 'L., Bessa, J., Peres, E., Morais, R., Sousa, JJ, 2017. Hyperspectral imaging: nyochaa na UAV dabeere sensọ, data nhazi na
ngwa maka ugbo na oke ohia. Nhụta anya 9 (11). https://doi.org/ 10.3390/rs9111110.
Agüera Vega, F., Ramírez, FC, Saiz, MP, Rosúa, FO, 2015. Ihe onyonyo nke otutu oge na-eji ụgbọ elu ikuku na-enweghị mmadụ maka nyochaa ihe ọkụkụ sunflower. Biosyst. Eng.
132, 19–27. https://doi.org/10.1016/j.biosystemseng.2015.01.008.
Ajayi, OG, Salubi, AA, Angbas, AF, Odigure, MG, 2017. Generation nke ziri ezi dijitalụ elevation ụdị si UAV nwetara ala pasent overlapping oyiyi. Int.
J. Sens dịpụrụ adịpụ 38 (8–10), 3113–3134. https://doi.org/10.1080/01431161.2017.1285085.
Ali, I., Greifeneder, F., Stamenkovic, J., Neumann, M., Notarnicola, C., 2015. Nyochaa nke igwe mmụta na-abịaru nso maka biomass na ala mmiri eweghachite si n'ime anya mmetụta data. Nhụta anya 7 (12), 16398–16421.
Alsamhi, SH, Afghah, F., Sahal, R., Hawbani, A., Al-qaness, MAA, Lee, B., Guizani, M., Green internet nke ihe na-eji UAV na netwọk B5G: Nyochaa ngwa
na atụmatụ. Mgbasa ozi. Hoc. Netwọk 117, 102505 https://doi.org/10.1016/j. adhoc.2021.102505.
Al-Thani, N., Albuainain, A., Alnaimi, F., Zorba, N., 2020. Drones maka nlekota anụ ụlọ atụrụ. Na: 20th IEEE Mediterranean Electrotechnical Conference. https://doi.
org/10.1109/MELECON48756.2020.9140588.
Ampatzidis, Y., Partel, V., 2019. UAV dabeere elu mmepụta phenotyping na citrus tinye n'ọrụ multispectral imaging na artificial ọgụgụ isi. Nhụta anya 11 (4), https://doi.org/10.3390/rs11040410.
Ampatzidis, Y., Partel, V., Costa, L., 2020. Agroview: Ngwa dabere na ígwé ojii iji hazie, nyocha na iji anya nke uche hụ data UAV anakọtara maka ngwa ọrụ ugbo ziri ezi na-eji ọgụgụ isi eme ihe. Kọmputa. Elektrọn. Agric. 174, 105457 https://doi. org/10.1016/j.compag.2020.105457.
Ang, K.-L.-M., Seng, JKP, 2021. Nnukwu data na mmụta igwe nwere ozi hyperspectral na ọrụ ugbo. Nweta IEEE 9, 36699–36718. https://doi.org/10.1109/
ACCESS.2021.3051196.
Aquilani, C., Confessore, A., Bozzi, R., Sirtori, F., Pugliese, C., 2022. Ntụleghachi: nkenke teknụzụ ugbo anụ ụlọ na usoro anụ ụlọ dabere na ala ịta ahịhịa. Animal 16 (1), https://doi.org/10.1016/j.animal.2021.100429.
Armenta-Medina, D., Ramirez-Delreal, TA, Villanueva-Vasquez, 'D., Mejia-Aguirre, C., Ọnọdụ na ozi dị elu na teknụzụ nkwukọrịta maka
imeziwanye arụpụta ọrụ ugbo: nyocha nke bibliometric. Agronomy 10 (12), Nkeji edemede 12. https://doi.org/10.3390/agronomy10121989.
Armstrong, I., Pirrone-Brusse, M., Smith, A., Jadud, M., 2011. Onye na-efe efe gator: kwupụta robotics ikuku na occam-π. Kọmun. Onye nhazi usoro. 2011, 329-340. https://doi. org/10.3233/978-1-60750-774-1-329.
Arora, SD, Chakraborty, A., 2021. Nchọpụta ọgụgụ isi nke omume mkpesa nke ndị ahịa (CCB): nyocha nke bibliometric. J. Business Res. 122, 60–74.
Aslan, MF, Durdu, A., Sabanci, K., Ropelewska, E., Gültekin, SS, 2022.
Nnyocha zuru oke nke ọmụmụ ihe na-adịbeghị anya na UAV maka ọrụ ugbo ziri ezi na mbara ubi na griin haus. Ngwa. Sci. 12 (3), 1047. https://doi.org/10.3390/
ngwa 12031047.
Atkinson, JA, Jackson, RJ, Bentley, AR, Ober, E., & Wells, DM (2018). Ubi Phenotyping maka Ọdịnihu. Na nyocha ihe ọkụkụ kwa afọ n'ịntanetị (p. 719-736). Jọn
Wiley & Ụmụ, Ltd. doi: 10.1002/9781119312994.apr0651.
Austin, R., 2010. Sistemụ ụgbọ elu anaghị akwụ ụgwọ: UAVS Design, Development and Deployment. Na: Sistemụ ụgbọ elu anaghị akwụ ụgwọ: UAVS Design, Development na
Nkwanye. John Wiley na ụmụ nwoke. https://doi.org/10.1002/9780470664797.
Awais, M., Li, W., Cheema, MJM, Zaman, QU, Shaheen, A., Aslam, B., Zhu, W., Ajmal, M., Faheem, M., Hussain, S., Nadeem, AA, Afzal, MM, Liu, C., 2022. UAVbased remote sensing in plant stress were using high-resolution thermal sensor for digital agriculture omume: a meta-nyochaa. Int. J. Environ. Sci. Teknụzụ https://doi.
org/10.1007/s13762-021-03801-5.
Bacco, M., Berton, A., Ferro, E., Gennaro, C., Gotta, A., Matteoli, S., Paonessa, F., Ruggeri, M., Virone, G., Zanella, A., 2018. Smart ugbo: Ohere, ihe ịma aka
na ndị na-emepụta teknụzụ. 2018 IoT kwụ ọtọ na. Nnọkọ nke Topical na Agriculture -Tuscany (IOT Tuscany) 1–6. https://doi.org/10.1109/IOTTUSCANY.2018.8373043.
Bah, MD, Hafiane, A., Canals, R., 2018. mmụta miri emi na akara data na-enweghị nlekọta maka nchọpụta ahihia na ihe ọkụkụ n'ahịrị na ihe oyiyi UAV. Mmetụta dị anya 10 (11), 1690.
https://doi.org/10.3390/rs10111690.
Baldi, S., 1998. Normative vesos social constructivist Filiks na oke nke ntụle: a netwọk-analytic nlereanya. M. Sociol. Mkpu. 63 (6), 829–846. https://doi.
org/10.2307/2657504.
Baluja, J., Diago, MP, Balda, P., Zorer, R., Meggio, F., Morales, F., Tardaguila, J., 2012. Ntụle nke ubi-vine mmiri ọnọdụ mgbanwe site thermal na multispectral
onyonyo site na iji ụgbọ elu na-enweghị mmadụ (UAV). Irrig. Sci. 30 (6), 511–522 . https://doi.org/10.1007/s00271-012-0382-9.
Barabaschi, D., Tondelli, A., Desiderio, F., Volante, A., Vaccino, P., Val`e, G., Cattivelli, L., Ọgbọ na-esote. Osisi Sci. 242, 3–13. https://doi.org/10.1016/j.
osisici.2015.07.010.
Barbedo, JGA, Koenigkan, LV, 2018. Echiche maka ojiji nke ikuku ikuku na-enweghị mmadụ iji nyochaa ehi. Outlook Agric. 47 (3), 214–222. https://doi.org/10.1177/0030727018781876.
Bareth, G., Aasen, H., Bendig, J., Gnyp, ML, Bolten, A., Jung, A., Michels, R., Soukkamaki, ¨ J., 2015. Obere arọ na UAV dabeere hyperspectral igwefoto zuru oke
maka nlekota ihe ubi: atụnyere Spectral na nha spectroradiometer mkpanaka. Photogrammetrie, Fernerkundung, Geoinformation 2015 (1), 69–79.
https://doi.org/10.1127/pfg/2015/0256.
Barrientos, A., Colorado, J., del Cerro, J., Martinez, A., Rossi, C., Sanz, D., Valente, J., Aerial remote sensing in agriculture: Ụzọ bara uru maka mkpuchi mpaghara.
na nhazi ụzọ maka ụgbọ mmiri nke obere ikuku robots. J. Field Rob. 28 (5), 667–689 . https://doi.org/10.1002/rob.20403.
Basiri, A., Mariani, V., Silano, G., Aatif, M., Iannelli, L., Glielmo, L., 2022. Nnyocha na ntinye nke usoro nhazi usoro maka multi-rotor UAV na nkenke.
ugbo. J. Navig. 75 (2), 364–383.
Basnet, B., Bang, J., 2018. Ọkachamara nke nkà mmụta ihe ọmụma na-arụ ọrụ ugbo: nyocha na usoro nhụta etinyere na nyocha data. J. Sen. 2018, 1–13.
Bendig, J., Bolten, A., Bareth, G., 2013. UAV dabeere imaging maka multi-oge, nnọọ elu mkpebi akuku elu ụdị iji nyochaa ihe ubi mgbanwe mgbanwe. Fotogrammetrie, Fernerkundung, Geoinformation 2013 (6), 551–562. https://doi. org/10.1127/1432-8364/2013/0200.
Bendig, J., Bolten, A., Bennertz, S., Broscheit, J., Eichfuss, S., Bareth, G., 2014. Na-eme atụmatụ biomass nke ọka bali na-eji akuku elu ụdị (CSMs) ewepụtara UAVbased RGB imaging. Mmetụta dị anya 6 (11), 10395–10412.
Bendig, J., Yu, K., Aasen, H., Bolten, A., Bennertz, S., Broscheit, J., Gnyp, ML, Bareth, G., 2015. Na-ejikọta UAV dị elu nke osisi sitere na elu ihe ọkụkụ. ụdị,
a na-ahụ anya, na nso akara ahịhịa infrared maka nlekota biomass na ọka bali. Int. J. Appl. Ụwa Obs. Geoinf. 39, 79–87. https://doi.org/10.1016/j.jag.2015.02.012.
Berni, JA, Zarco-Tejada, PJ, Sepulcre-Canto, 'G., Fereres, E., Villalobos, F., 2009a. Nrụpụta eserese na CWSI na ubi mkpụrụ osisi oliv na-eji mkpebi dị elu
onyonyo nhụta ihe na-ekpo ọkụ. gburugburu Sens. 113 (11), 2380–2388. https://doi.org/10.1016/j.rse.2009.06.018.
Berni, JA, Zarco-Tejada, PJ, Suarez, 'L., Fereres, E., 2009b. Ahụhụ dịpụrụ adịpụ nke thermal na warara eriri maka nlele ahịhịa sitere na ụgbọ ikuku na-enweghị onye. IEEE Trans. Geosci. Sens dịpụrụ adịpụ 47 (3), 722–738.
Bouzembrak, Y., Klüche, M., Gavai, A., Marvin, HJP, 2019. Ịntanetị nke Ihe na nchekwa nri: Nyocha akwụkwọ na nyocha nke bibliometric. Trends Food Sci. Teknụzụ 94,54–64. https://doi.org/10.1016/j.tifs.2019.11.002.
Brewster, C., Roussaki, I., Kalatzis, N., Doolin, K., Ellis, K., 2017. IoT na ọrụ ugbo: Ịmepụta onye na-anya ụgbọelu buru ibu na Europe. IEEE Kọmun. Mag. 55 (9), 26–33 .
Buters, TM, Belton, D., Cross, AT, 2019. Multi-sensor UAV nsochi nke onye seedlings na seedling obodo na millimeter ziri ezi. Drones 3 (4), 81.
https://doi.org/10.3390/drones3040081.
Candiago, S., Remondino, F., De Giglio, M., Dubbini, M., Gattelli, M., 2015. Na-enyocha ihe oyiyi multispectral na ahịhịa ahịhịa maka ngwa ọrụ ugbo ziri ezi sitere na onyonyo UAV. Mmetụta dị anya 7 (4), 4026–4047. https://doi.org/10.3390/rs70404026.
Cao, Y., Li, GL, Luo, YK, Pan, Q., Zhang, SY, 2020. Nleba anya nke ihe nrịbama uto beet shuga site na iji ihe nrịbama ahịhịa dị obosara (WDRVI) sitere na UAV.
ihe oyiyi multispectral. Kọmputa. Elektrọn. Agric. 171, 105331 https://doi.org/10.1016/j.compag.2020.105331.
Casillas, J., Acedo, F., 2007. Mgbanwe nke usoro ọgụgụ isi nke akwụkwọ azụmahịa ezinụlọ: ọmụmụ akwụkwọ bibliometric nke FBR. Azụmahịa Ezinụlọ Mkpu. 20 (2), 141–162.
Cen, H., Wan, L., Zhu, J., Li, Y., Li, X., Zhu, Y., Weng, H., Wu, W., Yin, W., Xu, C., Bao, Y., Feng, L., Shou, J., He, Y., 2019. Dynamic nlekota oru nke biomass nke osikapa n'okpuru
ọgwụgwọ nitrogen dị iche iche na-eji UAV dị fechaa nwere igwefoto ọnyocha ihe onyonyo nwere akụkụ abụọ. Ụzọ osisi 15 (1), 32. https://doi.org/10.1186/s13007-019-
0418-8.
Chamuah, A., Singh, R., 2019. Ịchekwa nkwado na ọrụ ugbo India site na UAV nkịtị: echiche ọhụrụ nwere ọrụ. SN ngwa. Sci. 2 (1), 106. https://
doi.org/10.1007/s42452-019-1901-6.
Chamuah, A., Singh, R., 2022. Ọchịchị na-ahụ maka ụgbọ elu ndị nkịtị na-adịghị mma (UAV) maka ngwa mkpuchi ihe ọkụkụ India. J. Ọkachamara
Teknụzụ 9, 100025 https://doi.org/10.1016/j.jrt.2022.100025.
Chen, A., Orlov-Levin, V., Meron, M., 2019. N'itinye onyonyo ikuku a na-ahụ anya nke ọwa dị elu nke mkpuchi ihe ọkụkụ na njikwa ogbugba mmiri n'ụzọ ziri ezi. Agric. Mmiri
Jikwaa. 216, 196–205. https://doi.org/10.1016/j.agwat.2019.02.017.
Daakir, M., Pierrot-Deseilligny, M., Bosser, P., Pichard, F., Thom, C., Rabot, Y., Martin, O., 2017. Dị fechaa UAV na on-board photogrammetry na singlefrequency GPS n'ọnọdu maka metrology ngwa. ISPRS J. Foto foto. Sens dịpụrụ adịpụ 127, 115–126. https://doi.org/10.1016/j.isprsjprs.2016.12.007.
Dawaliby, S., Aberkane, A., Bradai, A., 2020. IoT nke dabeere na Blockchain maka njikwa ọrụ drone kwụụrụ onwe ya. Na: Usoro nke 2nd ACM
Ọmụmụ MobiCom na Nkwukọrịta ikuku na-enyere aka na Drone maka 5G na gafere, p. 31–36. https://doi.org/10.1145/3414045.3415939.
Day, RA, Gastel, B., 1998. Otu esi ede ma bipụta akwụkwọ sayensị. Mahadum Mahadum Cambridge. de Castro, AI, Pena, ˜ JM, Torres-Sanchez, 'J., Jim'enez-Brenes, FM, ValenciaGredilla, F., Recasens, J., Lopez-Granados, 'F., 2020. Mapping cynodon dactylon infesting jiri usoro OBIA mkpebi akpaka kpuchie ihe ubi yana onyonyo UAV maka ezigbo viticulture. Nhụta anya 12 (1), 56. https://doi.org/10.3390/rs12010056.
de Castro, AI, Torres-S'anchez, J., Pena, ˜ JM, Jim'enez-Brenes, FM, Csillik, O., Lopez-'Granados, F., 2018. An akpaka random ọhịa-OBIA algọridim maka Maapụ mbụ igbo n'etiti na n'ime ahịrị ihe ọkụkụ site na iji onyonyo UAV. Nhụta anya 10 (2). https://doi.org/10.3390/rs10020285.
Demir, N., Sonmez, ¨ NK, Akar, T., Ünal, S., 2018. Ntụnye akpaaka nke ịdị elu osisi nke ọka wit genotypes Iji DSM ewepụtara na onyonyo UAV. Usoro 2 (7), 350. https://doi.org/10.3390/ecrs-2-05163.
Deng, J., Zhong, Z., Huang, H., Lan, Y., Han, Y., Zhang, Y., 2020. Netwọk nkewa semantic dị fechaa maka eserese ahihia ozugbo site na iji ụgbọ ala ikuku na-enweghị mmadụ. Ngwa. Sci. 10 (20), 7132. https://doi.org/10.3390/app10207132.
Deng, L., Mao, Z., Li, X., Hu, Z., Duan, F., Yan, Y., 2018. UAV dabeere multispectral remote sensing maka nkenke ugbo: ntụnyere n'etiti dị iche iche ese foto. ISPRS J. Foto foto. Sens dịpụrụ adịpụ 146, 124–136.
Diaz-Gonzalez, FA, Vuelvas, J., Correa, CA, Vallejo, VE, Patino, D., 2022. Igwe mmụta igwe na usoro nhụta anya nke etinyere iji tụọ ihe ngosi ala - nyochaa. Ecol. Ind. 135, 108517 https://doi.org/10.1016/j.ecolind.2021.108517.
Díaz-Varela, RA, De la Rosa, R., Leon, 'L., Zarco-Tejada, PJ, 2015. Ihe oyiyi UAV ikuku dị elu iji nyochaa oke okpueze osisi olive site na iji foto 3D.
nwughari: ngwa na ozuzu ule. Mmetụta dị anya 7 (4), 4213–4232. https://doi.org/10.3390/rs70404213.
Dixit, A., Jakhar, SK, 2021. Njikwa ikike ọdụ ụgbọ elu: nyocha na nyocha bibliometric. J. Ntugharị ikuku. Jikwaa. 91, 102010.
Dong, T., Shang, J., Liu, J., Qian, B., Jing, Q., Ma, B., Huffman, T., Geng, X., Sow, A., Shi, Y., Canisius, F., Jiao, X., Kovacs, JM, Walters, D., Cable, J., Wilson, J., 2019.
Iji onyonyo RapidEye chọpụta mgbanwe n'ime ubi nke uto na mkpụrụ na Ontario, Canada. Nkọwa nke Agric. 20 (6), 1231–1250. https://doi.org/10.1007/
s11119-019-09646-w.
Dutta, PK, Mitra, S., 2021. Ngwa nke drones ọrụ ugbo na iot ịghọta usoro inye nri n'oge COVID-19. Na: Choudhury, A., Biswas, A., Prateek, M.,
Chakrabarti, A. (Eds.), Agricultural Informatics: Automation Iji IoT na Machine Learning. Wiley, peeji nke 67–87. van Eck, N., Waltman, L., 2009. Nyocha ngwanrọ: VOSviewer, mmemme kọmputa maka nkewa bibliometric. Scientometrics 84 (2), 523–538. https://doi.org/10.1007/s11192-009-0146-3.
Elijah, O., Rahman, TA, Orikumhi, I., Leow, CY, Hindia, MN, 2018. Nleba anya nke Intanet nke Ihe (IoT) na nyocha data na ọrụ ugbo: uru na ihe ịma aka.
Ihe ịntanetị IEEE J. 5 (5), 3758–3773.
Enciso, J., Avila, CA, Jung, J., Elsayed-Farag, S., Chang, A., Yeom, J., Landivar, J., Maeda, M., Chavez, JC, 2019. Nkwado nke agronomic UAV na ubi
nha maka ụdị tomato. Kọmputa. Elektrọn. Agric. 158, 278–283. https://doi.org/10.1016/j.compag.2019.02.011.
Espinoza, CZ, Khot, LR, Sankaran, S., Jacoby, PW, 2017. High resolution multispectral and thermal remote sensing based based water stress assessment in
osisi vine agbanyere n'okpuru ala. Nhụta anya 9 (9), 961. https://doi.org/ 10.3390/rs9090961.
Ewing, J., Oommen, T., Jayakumar, P., Alger, R., 2020. Iji hyperspectral remote sensing maka gradation ala. Nhụta anya 12 (20), 3312. ttps://doi.org/10.3390/
rs12203312.
Fawcett, D., Panigada, C., Tagliabue, G., Boschetti, M., Celesti, M., Evdokimov, A., Biriukova, K., Colombo, R., Miglietta, F., Rascher, U., Anderson, K., 2020. Multiscale nyocha nke drone dabeere multispectral elu reflectance na ahịhịa indices na arụmọrụ ọnọdụ. Mmetụta dị anya 12 (3), 514.
Feng, X., Yan, F., Liu, X., 2019. Ọmụmụ teknụzụ nzikọrịta ozi ikuku na ịntanetị nke ihe maka ọrụ ugbo ziri ezi. Ikuku Pers. Kọmun. 108 (3),
1785-1802.
Ferreira, MP, Pinto, CF, Serra, FR, 2014. Azụmahịa na-akwụ ụgwọ tiori na nyocha azụmahịa mba ụwa: ọmụmụ akwụkwọ bibliometric karịrị afọ iri atọ. Scientometrics 98 (3), 1899–1922. https://doi.org/10.1007/s11192-013-1172-8.
Fisher, P., Abuzar, M., Rab, M., Best, F., Chandra, S., 2009. Ọganihu na ọrụ ugbo ziri ezi na ndịda ọwụwa anyanwụ Australia. I. usoro nlọghachị iji meomi
Ọdịiche dị n'ọgbara mkpụrụ ọka n'iji mkpụrụ paddock akụkọ ihe mere eme nke ndị ọrụ ugbo na ndenye ahịhịa dị iche iche emeziri nke ọma. Ihe ubi ahịhịa ndụ Sci. 60 (9), 844–858 .
Floreano, D., Osisi, RJ, 2015. Sayensị, teknụzụ na ọdịnihu nke obere drones kwụụrụ onwe ya. Ọdịdị 521 (7553), 460–466. https://doi.org/10.1038/nature14542.
Friha, O., Ferrag, MA, Shu, L., Maglaras, LA, Wang, X., 2021. Ịntanetị nke ihe maka ọdịnihu nke smart agriculture: nyocha zuru oke nke teknụzụ na-apụta. IEEE CAA J. Autom. Sinica 8 (4), 718–752.
Fuentes-Pacheco, J., Torres-Olivares, J., Roman-Rangel, E., Cervantes, S., JuarezLopez, P., Hermosillo-Valadez, J., Rendon-Mancha, 'JM, 2019. Fig osisi nkebi. site na onyonyo ikuku site na iji netwọọdụ ihe ngbanwe mgbanwe mgbanwe miri emi. Nhụta anya 11 (10), 1157. https://doi.org/10.3390/rs11101157.
Gago, J., Douthe, C., Coopman, RE, Gallego, PP, Ribas-Carbo, M., Flexas, J., Escalona, J., Medrano, H., 2015. Ihe ịma aka UAV iji nyochaa nrụgide mmiri maka
oru ugbo adigide. Agric. Onye njikwa mmiri. 153, 9–19. https://doi.org/10.1016/j. agwat.2015.01.020.
García-Tejero, IF, Rubio, AE, Vinuela, ˜ I., Hern' andez, A., Guti'errez-Gordillo, S., Rodríguez-Pleguezuelo, CR, Dur' an-Zuazo, VH, 2018. Thermal imaging na osisi
Ọkwa iji nyochaa ọnọdụ mmiri-ihe ọkụkụ na osisi almọnd (cv. Guara) n'okpuru atụmatụ ịgba mmiri na-enweghị ụkọ. Agric. Water Manager. 208, 176–186. https://doi.org/10.1016/j.
agwat.2018.06.002.
Garzonio, R., Di Mauro, B., Colombo, R., Cogliati, S., 2017. Ngosipụta ihu igwe na ihe nleba anya nke fluorescence nke suninduced na-eji obere hyperspectral UAS. Nhụta anya 9 (5), 472. https://doi.org/10.3390/rs9050472. Gaˇsparovi'c, M., Zrinjski, M., Barkovic, Đ., Radoˇcaj, D., 2020. Usoro akpaka maka
nkewa ahihia n'ubi oat dabere na onyonyo UAV. Kọmputa. Elektrọn. Agric.
Gebbers, R., Adamchuk, VI, 2010. Ọrụ ugbo nke ọma na nchekwa nri. Sayensị 327 (5967), 828-831. https://doi.org/10.1126/science.1183899.
Geipel, J., Link, J., Claupein, W., 2014. Ejikọtara ụdịdị dị iche iche na nhazi mbara igwe nke mkpụrụ ọka dabere na onyonyo ikuku na ụdị elu ihe ọkụkụ enwetara na sistemụ ụgbọ elu na-enweghị mmadụ. Mmetụta dị anya 6 (11), 10335–10355. https://doi.org/10.3390/rs61110335.
Geng, D., Feng, Y., Zhu, Q., 2020. Nhazi na-adịgide adịgide maka ndị ọrụ: nyocha akwụkwọ na nyocha bibliometric. Environ. Sci. Mmetọ. Res. 27 (24), 29824–29836. https://doi. org/10.1007/s11356-020-09283-1.
Gevaert, CM, Suomalainen, J., Tang, J., Kooistra, L., 2015. Ọgbọ nke spectraltemporal nzaghachi elu site na ijikọta multispectral satịlaịtị na hyperspectral
Onyonyo UAV maka ngwa ọrụ ugbo ziri ezi. IEEE J. Sel. N'elu. Ngwa. Ụwa Obs. Sens dịpụrụ adịpụ 8 (6), 3140–3146. ttps://doi.org/10.1109/JSTARS.2015.2406339.
Gill, SS, Chana, I., Buyya, R., 2017. IoT dabeere agriculture dị ka ígwé ojii na nnukwu dataservice: mmalite nke dijitalụ India. J. Org. na Kọmpụta Onye Ọrụ Ọgwụgwụ. (JOEUC) 29 (4),
1-23.
Gmür, M., 2006. Nchịkọta nchịkọta akụkọ na ịchọ ụlọ akwụkwọ kọleji na-adịghị ahụ anya: nyocha usoro. Scientometrics 57 (1), 27–57. https://doi.org/10.1023/
a: 1023619503005.
Gnadinger, ¨ F., Schmidhalter, U., 2017. Ọnụ ọgụgụ dijitalụ nke osisi ọka sitere n'ụgbọ ala ikuku na-adịghị mma (UAV). Nhụta anya 9 (6). Https://doi.org/10.3390/rs9060544.
Gokto ¨ ǧan, AH, Sukkarieh, S., Bryson, M., Randle, J., Lupton, T., Hung, C., 2010. Ụgbọ elu ikuku na-enweghị nku Rotary maka nleba anya ahịhịa mmiri na mmiri.
njikwa. J. Intell. Usoro Robotic: Theor. Ngwa. 57 (1–4), 467–484. https://doi. org/10.1007/s10846-009-9371-5.
Gomez-Cand 'on, 'D., De Castro, AI, Lopez-Granados,' F., 2014. N'ịtụle izi ezi nke mosaics si na unmanned aerial ugbo ala (UAV) oyiyi maka nkenke ọrụ ugbo nzube na ọka wit. Precis. Agric. 15 (1), 44–56. https://doi.org/10.1007/s11119-013-9335-4.
Gomez-Cand 'on, 'D., Virlet, N., Labb'e, S., Jolivot, A., Regnard, J.-L., 2016. Ubi phenotyping nke nrụgide mmiri na ọnụ ọgụgụ osisi site na foto UAV. : ọhụrụ nghọta maka
nweta thermal na calibration. Precis. Agric. 17 (6), 786–800 . https://doi.org/10.1007/s11119-016-9449-6.
Gonzalez-Dugo, V., Zarco-Tejada, PJ, Fereres, E., 2014. Ngwa na njedebe nke iji ihe ọkụkụ mmiri nrụgide index dị ka ihe na-egosi ụkọ mmiri na ubi mkpụrụ osisi citrus. Agric. Maka. Meteorol. 198–199, 94–104. https://doi.org/10.1016/j. agrformet.2014.08.003.
Gonzalez-Dugo, V., Zarco-Tejada, P., Nicolas, 'E., Nortes, PA, Alarcon, JJ, Intrigliolo, DS, Fereres, E., 2013. Iji elu mkpebi UAV thermal imagery ka
chọpụta mgbanwe dị na ọnọdụ mmiri nke ụdị osisi mkpụrụ ise dị n'ime ubi mkpụrụ osisi. Precis. Agric. 14 (6), 660–678. https://doi.org/10.1007/s11119-013-9322-9.
Goyal, K., Kumar, S., 2021. mmuta ego: Nleba anya n'usoro na nyocha nke bibliometric. Int. J. Ọmụmụ ndị ahịa 45 (1), 80–105. https://doi.org/10.1111/
ijcs.12605.
Grenzdorffer, ¨ GJ, Engel, A., Teicher, B., 2008. Ike fotogrammetric nke uavs dị ọnụ ala na ọhịa na ọrụ ugbo. Ebe nchekwa nke mba ụwa nke fotogrammetry, ihe nhụta anya na sayensị ozi gbasara ohere – ISPRS Archives 37, 1207–1213. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85039543258&partnerI D=40&md5=b4b2d639257e8ddb5a373d15959c4e1e.
Guan, S., Fukami, K., Matsunaka, H., Okami, M., Tanaka, R., Nakano, H., Sakai, T., Nakano, K., Ohdan, H., Takahashi, K., 2019. Ịtụle njikọ nke elu-mkpebi
NDVI nwere ọkwa ntinye fatịlaịza na mkpụrụ nke osikapa na ọka wit na-eji obere UAV. Mmetụta dị anya 11 (2), 112.
Gundolf, K., Filser, M., 2013. Nchọpụta njikwa na okpukperechi: nyocha nyocha. J. Ụgbọ ala. Ụkpụrụ 112 (1), 177–185.
Guo, Q., Zhu, Y., Tang, Y., Hou, C., He, Y., Zhuang, J., Zheng, Y., Luo, S., 2020. CFD simulation na nnwale nnwale nke oghere oghere. na nkesa oge nke
Ntugharị ikuku na-agbada nke quad-rotor agricultural UAV na hover. Kọmputa. Elektrọn. Agric. 172, 105343 https://doi.org/10.1016/j.compag.2020.105343.
Haghighattalab, A., Gonz' alez Perez, L., Mondal, S., Singh, D., Schinstock, D., Rutkoski, J., Ortiz-Monasterio, I., Singh, RP, Goodin, D. , Poland, J., 2016.
Ngwa nke ikuku ikuku na-enweghị mmadụ maka nnukwu mmepụta phenotyping nke nnukwu ebe a na-azụ ọka wit. Ụzọ ihe ọkụkụ 12 (1). https://doi.org/10.1186/s13007-
016-0134-6.
Hakala, T., Honkavaara, E., Saari, H., Makynen, ¨ J., Kaivosoja, J., Pesonen, L., & Pol ¨ onen, ¨I., 2013. Ihe onyonyo onyonyo sitere na UAV n'okpuru ọnọdụ ọkụ dị iche iche. . Na GG Bill R. (Ed.), International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences—ISPRS Archives (Mpịakọta 40, mbipụta 1W2, p. 189-194). International Society for Photogrammetry na Remote Sensing. https://www.scopus.com/inward/record.uri?eid=2-s2.0-848875632.
Hamylton, SM, Morris, RH, Carvalho, RC, Roder, N., Barlow, P., Mills, K., Wang, L.Ntụle usoro maka ịdepụta ahịhịa agwaetiti site na ikuku na-enweghị mmadụ
onyogho ụgbọ ala (UAV): nhazi ọkwa Pixel, nkọwa anya na ụzọ mmụta igwe. Int. J. Appl. Ụwa Obs. Geoinf. 89, 102085 https://doi.org/
10.1016/j.jag.2020.102085.
Haque, A., Islam, N., Samrat, NH, Dey, S., Ray, B., 2021. Ọrụ ugbo mara mma site n'aka onye ndu na Bangladesh: ohere, ohere, na gafere.
Ndagide 13 (8), 4511.
Hardin, PJ, Hardin, TJ, 2010. Ụgbọ ala ndị dịpụrụ adịpụ na-anya ụgbọ ala na nyocha gburugburu ebe obibi. Geography Kompas 4 (9), 1297–1311. ttps://doi.org/10.1111/j.1749-
8198.2010.00381.x.
Hardin, PJ, Jensen, RR, 2011. Ụgbọ ala ikuku na-adịghị ahụkebe dị obere na nhụta anya gburugburu ebe obibi: ihe ịma aka na ohere. GISci. Sens dịpụrụ adịpụ 48 (1), 99–111. https://doi.org/10.2747/1548-1603.48.1.99.
He, Y., Nie, P., Zhang, Q., Liu, F., 2021. Agricultural Internet of Things: Teknụzụ na ngwa, (1st ed. 2021 mbipụta). Springer.
Herwitz, SR, Johnson, LF, Dunagan, SE, Higgins, RG, Sullivan, DV, Zheng, J., Lobitz, BM, Leung, JG, Gallmeyer, BA, Aoyagi, M., Slye, RE, Brass, JA, 2004.
Onyonyo sitere na ụgbọ elu ikuku na-enweghị mmadụ: nlekota oru ugbo na nkwado mkpebi. Kọmputa. Elektrọn. Agric. 44 (1), 49–61. https://doi.org/10.1016/j.
compag.2004.02.006.
Holman, FH, Riche, AB, Michalski, A., Castle, M., Wooster, MJ, Hawkesford, MJ, High throughput field phenotyping nke osisi ọka wit na ọnụego uto n'ime ule ibé ubi na-eji UAV dabere na nghọta. Nhụta anya 8 (12). https://doi. org/10.3390/rs8121031.
Honkavaara, E., Saari, H., Kaivosoja, J., Pol ¨ onen, ¨ I., Hakala, T., Litkey, P., M¨akynen, J., Pesonen, L., 2013. Nhazi na ntule nke spectrometric, onyonyo stereoscopic anakọtara site na iji igwefoto ihe nlegharị anya UAV dị fechaa maka ọrụ ugbo ziri ezi. Nhụta anya 5 (10), 5006–5039. https://doi.org/10.3390/rs5105006.
Hossein Motlagh, N., Taleb, T., Arouk, O., 2016. Ịdị elu ụgbọ elu na-enweghị ndị mmadụ na-adabere na ịntanetị nke ọrụ ihe: nyocha zuru oke na echiche n'ọdịnihu. Ihe ịntanetị IEEE J. 3 (6), 899–922. https://doi.org/10.1109/JIOT.2016.2612119.
Hrabar, S., Sukhatme, GS, Corke, P., Usher, K., Roberts, J., 2005. Ngwakọta optic-flow na stereo dabeere navigation nke obodo ukwu canyons maka UAV. N'ime: 2005 IEEE/RSJ
Nzukọ Mba Nile na Robots na Sistemu nwere ọgụgụ isi, p. 3309–3316. https://doi.org/10.1109/IROS.2005.1544998.
Hsu, T.-C., Yang, H., Chung, Y.-C., Hsu, C.-H., 2020. A Creative IoT agriculture platform for Cloud fog computing. Na-akwado. Kọmputa. Inf. Sistemụ 28, 100285.
Huang, H., Deng, J., Lan, Y., Yang, A., Deng, X., Zhang, L., Gonzalez-Andujar, JL, 2018. A n'ụzọ zuru ezu convolutional netwọk maka nkewa ahihia nke ikuku ụgbọ ala na-enweghị mmadụ ( UAV) onyonyo. PLoS ONE 13 (4), e0196302.
Huang, H., Lan, Y., Yang, A., Zhang, Y., Wen, S., Deng, J., 2020. mmụta miri emi megide ihe dabere na ihe onyonyo onyonyo (OBIA) na eserese ahihia nke ihe onyonyo UAV. Int. J.
Sens dịpụrụ adịpụ 41 (9), 3446–3479. https://doi.org/10.1080/01431161.2019.1706112.
Huang, H., Yang, A., Tang, Y., Zhuang, J., Hou, C., Tan, Z., Dananjayan, S., He, Y., Guo, Q., Luo, S., 2021. Mgbanwe agba dị omimi maka onyonyo UAV na nlekota ihe ọkụkụ
na-eji ụdị mgbanwe semantic nyefe na nlebara anya mpaghara gaa na ụwa. Int. J. Appl. Ụwa Obs. Geoinf. 104, 102590 https://doi.org/10.1016/j.jag.2021.102590.
Huang, YB, Thomson, SJ, Hoffmann, WC, Lan, YB, Fritz, BK, 2013. Mmepe na atụmanya nke teknụzụ ụgbọ elu na-enweghị mmadụ maka mmepụta ugbo.
njikwa. Int. J. Agric. Biol. Eng. 6 (3), 1–10. https://doi.org/10.3965/j. ijabe.20130603.001.
Huang, Y., Hoffmann, WC, Lan, Y., Wu, W., Fritz, BK, 2009. Mmepe nke usoro ịgbasa maka ikpo okwu ụgbọ elu na-enweghị mmadụ. Ngwa. Eng. Agric. 25 (6), 803–809 .
Hunt Jr., ER, Dean Hively, W., Fujikawa, SJ, Linden, DS, Daughtry, CST, McCarty, GW, 2010. Nweta foto dijitalụ NIR-green-acha anụnụ anụnụ si na
ugbo elu na-adighi mmadu maka nlekota ihe ubi. Mmetụta dị anya 2 (1), 290–305. https://doi. org/10.3390/rs2010290. Inoue, Y., 2020. Satellite- na drone dabere na nhụta anya nke ihe ọkụkụ na ala maka ọrụ ugbo mara mma–ntụle. Ala Sci. Osisi Nutr. 66 (6), 798–810 . https://doi.org/10.1080/00380768.2020.1738899.
Islam, N., Rashid, MM, Pasandideh, F., Ray, B., Moore, S., Kadel, R., 2021. Nyochaa ngwa na teknụzụ nkwukọrịta maka Internet of Things (IoT) na
Ụgbọ ala ikuku na-enweghị mmadụ (UAV) dabere na ọrụ ugbo nwere amamihe na-adigide. Nkwado 13 (4), 1821. https://doi.org/10.3390/su13041821.
Jaud, M., Passot, S., Le Bivic, R., Delacourt, C., Grandjean, P., Le Dantec, N., 2016. Ịtụle izi ezi nke elu mkpebi dijitalụ elu ụdị gbakọọ site na.
PhotoScan® na MicMac® nọ n'ọnọdụ nyocha kacha mma. Nhụta anya 8 (6), https://doi.org/10.3390/rs8060465.
Jim'enez-Brenes, FM, Lopez-Granados, 'F., Castro, AI, Torres-S' anchez, J., Serrano, N., Pena, ˜ JM, 2017. Ịkọwapụta mmetụta kwachaa na-emetụta ihe owuwu osisi oliv na kwa afọ. ito eto site na iji ihe nlere anya 3D dabere na UAV. Ụzọ ihe ọkụkụ 13 (1). https://doi.org/10.1186/s13007-017-0205-3.
Jin, X., Liu, S., Baret, F., Hemerle, M., Comar, A., 2017. Atụmatụ njupụta nke osisi njupụta nke ọka wit a kụrụ na ntoputa si nnọọ ala elu UAV oyiyi. Sens dịpụrụ adịpụ.
Environ. 198, 105–114. https://doi.org/10.1016/j.rse.2017.06.007.
Jinbo, C., Xiangliang, C., Han-Chi, F., Lam, A., 2019. Usoro nlekota oru ugbo na-akwado site na igwe ojii. Kọmputa ụyọkọ. 22 (4), 8929–8938.
Ju, C., & Nwa, HI 2018a. Ntụle arụmọrụ nke ọtụtụ sistemụ UAV maka nhụta anya na ọrụ ugbo. Usoro ọmụmụ ihe gbasara ọhụụ Robotic na Action in Agriculture na IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, 21-26.
Ju, C., Nwa, HI, 2018b. Ọtụtụ usoro UAV maka ngwa ọrụ ugbo: njikwa, mmejuputa iwu na nyocha. Eletrọnịkị 7 (9), 162. https://doi.org/10.3390/
eletrọnịkị 7090162.
Jung, J., Maeda, M., Chang, A., Bhandari, M., Ashapure, A., Landivar-Bowles, J., 2021. Ikike nke ime anya na ọgụgụ isi dị ka ngwá ọrụ iji melite
resilience nke usoro mmepụta ugbo. Curr. Echiche. Biotechnol. 70, 15–22. https://doi.org/10.1016/j.copbio.2020.09.003.
Kalischuk, M., Paret, ML, Freeman, JH, Raj, D., Da Silva, S., Eubanks, S., Wiggins, DJ, Lollar, M., Marois, JJ, Mellinger, HC, Das, J. , 2019. Usoro nyocha ihe ọkụkụ emelitere nke ọma na-agbakwunye ụgbọ elu ikuku na-enweghị mmadụ–enyere aka onyonyo ihe ọkụkụ dị iche iche n'ime omume nlegharị anya nke ọma maka ọrịa gummy stem blight na anyụ. Osisi Dis. 103 (7), 1642–1650.
Kapoor, KK, Tamilmani, K., Rana, NP, Patil, P., Dwivedi, YK, Nerur, S., 2018. Ọganihu na nyocha mgbasa ozi mgbasa ozi: gara aga, ugbu a na ọdịnihu. gwa. Sistemụ N'ihu. 20
(3), 531-558.
Kerkech, M., Hafiane, A., Canals, R., 2020. VddNet: netwọk nchọpụta ọrịa vine dabere na onyonyo multispectral na maapụ miri emi. Nhụta anya 12 (20), 3305. https://doi. org/10.3390/rs12203305.
Khaliq, A., Comba, L., Biglia, A., Ricauda Aimonino, D., Chiaberge, M., nwoke nwere mmasị nwoke, P., 2019. Ntụle nke satịlaịtị na UAV dabeere multispectral oyiyi maka ubi-vine
ntule mgbanwe. Nhụta anya 11 (4). https://doi.org/10.3390/rs11040436.
Khan, PW, Byun, Y.-C., Park, N., 2020. IoT-blockchain nyeere kachasi provenance usoro maka nri ụlọ ọrụ 4.0 na-eji elu mmụta miri emi. Sensọ 20 (10), 2990.
Khan, RU, Khan, K., Albattah, W., Qamar, AM, Ullah, F., 2021. Nchọpụta dabere na onyonyo nke ọrịa osisi: site na igwe oge gboo mmụta gaa njem mmụta miri emi. Njikọ ikuku. Kọmpụta mkpanaka. 2021, 1–13.
Khan, S., Tufail, M., Khan, MT, Khan, ZA, Iqbal, J., Alam, M., Le, KNQ, 2021. A akwụkwọ ọgụgụ ọkara-elekọta kpuchie maka UAV dabeere akuku/ahịhịa nhazi. PLoS ONE 16 (5), e0251008.
Khanal, S., Fulton, J., Shearer, S., 2017. Nleba anya nke ugbu a na ngwa ngwa nke thermal remote sensing na nkenke ugbo. Kọmputa. Elektrọn.
Agric. 139, 22–32. https://doi.org/10.1016/j.compag.2017.05.001.
Khanna, A., Kaur, S., 2019. Evolution of Internet of Things (IoT) na mmetụta ya dị ịrịba ama na ngalaba nke Precision Agriculture. Kọmputa. Elektrọn. Agric. 157, 218–231 .
Kim, W., Khan, GF, Wood, J., Mahmood, MT, 2016. Nkwekọrịta ndị ọrụ maka ụlọ ọrụ na-adigide: nyocha isiokwu site na iji nyocha netwọk mmekọrịta na gbawara.
ụzọ nchọpụta. Ndagide 8 (7), 631.
Kirsch, M., Lorenz, S., Zimmermann, R., Tusa, L., Mockel, ¨ R., Hodl, ¨ P., Booysen, R., Khodadadzadeh, M., Gloaguen, R., 2018. Mmekọrịta nke terrestrial na drone-ebu
Ụzọ nghọta hyperspectral na fotogrammetric maka nyocha nkewa na nlekota oru Ngwuputa. Nhụta anya 10 (9), 1366. https://doi.org/10.3390/
rs10091366.
Kitano, BT, Mendes, CCT, Geus, AR, Oliveira, HC, Souza, JR, 2019. Ngụkọta ọka ọka site na iji mmụta miri emi na ihe oyiyi UAV. IEEE Geosci. Sens dịpụrụ adịpụ Lett. 1–5 https://doi.org/10.1109/LGRS.2019.2930549.
Koh, JCO, Spangenberg, G., Kant, S., 2021. igwe akpaaka mmụta maka highthroughput image dabeere osisi phenotyping. Nhụta anya 13 (5), 858. https://
doi.org/10.3390/rs13050858.
Kovalev, IV, Voroshilova, AA, 2020. Usoro teknụzụ ọgbara ọhụrụ na mmepe nke gburugburu ebe obibi nke ibu UAV. J. Phys. Conf. Ser. 1515 (5), 052068 https://doi. org/10.1088/1742-6596/1515/5/052068.
Krul, S., Pantos, C., Frangulea, M., Valente, J., 2021. Visual SLAM maka anụ ụlọ ime ụlọ na ọrụ ugbo na-eji obere drone nwere igwefoto monocular: ọmụmụ ihe omume.
Drones 5 (2), 41. https://doi.org/10.3390/drones5020041.
Kulbacki, M., Segen, J., Knie'c, W., Klempous, R., Kluwak, K., Nikodem, J., Kulbacka, J., Serester, A., 2018. Nnyocha nke drones maka akpaaka ọrụ ugbo. site na akuku ruo
owuwe ihe ubi. Na: INES 2018 - IEEE 22nd International Conference on Intelligent Engineering Systems, p. 000353-358. https://doi.org/10.1109/INES.2018.8523943.
Lagkas, T., Argyriou, V., Bibi, S., Sarigiannidis, P., 2018. UAV IoT framework echiche na ihe ịma aka: kwupụta ichebe drones dị ka "Ihe". Sensọ 18 (11), 4015. https://doi.org/10.3390/s18114015.
Laliberte, AS, Rango, A., 2011. Usoro nhazi onyonyo na nhazi ọkwa maka nyocha nke onyonyo sub-decimeter ejiri ụgbọ elu na-enweghị ụgbọ elu enwetara.
ọdụ ụgbọ mmiri. GISci. Sens dịpụrụ adịpụ 48 (1), 4–23. https://doi.org/10.2747/1548-1603.48.1.4.
Laliberte, AS, Rango, A., Herrick, JE, 2007. Ụgbọ ala ndị na-adịghị mma maka ịwapụta na nleba anya nke ọdụ ụgbọ ala: ntụnyere usoro abụọ. Usoro mmemme ọgbakọ kwa afọ ASPRS.
Lam, OHY, Dogotari, M., Prüm, M., Vithlani, HN, Roers, C., Melville, B., Zimmer, F., Becker, R., 2021. Ihe na-emepe emepe maka eserese ahihia n'ala ala ahịhịa.
iji ụgbọ elu ikuku na-enweghị mmadụ: Iji Rumex obtusifolius dịka ọmụmụ ihe. Euro. Sens J.Remote. 54 (sup1), 71–88. https://doi.org/10.1080/22797254.2020.1793687.
Lambert, DM, Lowenberg-DeBoer, J., Griffin, TW, Peone, J., Payne, T., Daberkow, SG, 2004. Nkuchi, uru, na ime ka mma iji nkenke data ugbo.
Akwụkwọ na-arụ ọrụ. Mahadum Purdue. https://doi.org/10.22004/ag.econ.28615.
Lelong, CCD, Burger, P., Jubelin, G., Roux, B., Labb'e, S., Baret, F., 2008. Ntụle ihe onyonyo ụgbọ elu na-enweghị mmadụ maka nleba anya ọnụọgụ ọka wit n'obere ala. Sensọ 8 (5), 3557–3585. https://doi.org/10.3390/s8053557.
Li, C., Niu, B., 2020. Nhazi nke ọrụ ugbo mara mma dabere na nnukwu data na ịntanetị nke ihe. Int. J. Nkesa. Sens. Netw. 16 (5) ttps://doi.org/10.1177/1550147720917065.
Li, W., Niu, Z., Chen, H., Li, D., Wu, M., Zhao, W., 2016. Ntụle dịpụrụ adịpụ nke elu mkpuchi elu na biomass dị n'elu ala nke ọka site na iji ihe onyonyo stereo dị elu sitere na usoro ikuku ụgbọ ala anaghị akwụ ụgwọ dị ọnụ ala. Ecol. 67, 637–648. https://doi.org/10.1016/j.ecolind.2016.03.036.
Liakos, KG, Busato, P., Moshou, D., Pearson, S., Bochtis, D., 2018. Igwe mmụta igwe na ọrụ ugbo: nyocha. Sensọ 18 (8), 2674.
Liebisch, F., Kirchgessner, N., Schneider, D., Walter, A., Hund, A., 2015. Remote, ikuku phenotyping nke àgwà ọka na mobile multi-sensor obibia. Ụzọ osisi 11 (1), 9. https://doi.org/10.1186/s13007-015-0048-8.
Lin, Z., Guo, W., 2020. Nchọpụta na ịgụta Sorghum panicle site na iji onyonyo ikuku na-enweghị mmadụ na mmụta miri emi. N'ihu. Osisi Sci. 11.
Liu, S., Guo, L., Webb, H., Ya, X., Chang, X., 2019. Ịntanetị nke ihe nlekota usoro nke ọgbara ọhụrụ eco-agriculture dabeere na ígwé ojii Mgbakọ. Nweta IEEE 7, 37050–37058.
Lopez-Granados, 'F., 2011. Nchọpụta ahihia maka njikwa ahihia nke saịtị akọwapụtara: eserese na ụzọ dị adị. Igbo Res. 51 (1), 1–11. https://doi.org/10.1111/j.1365-3180.2010.00829.x.
Lopez-Granados, 'F., Torres-Sanchez, 'J., De Castro, A.-I., Serrano-Perez, A., MesasCarrascosa, F.-J., Pena, ˜ J.-M. , 2016. Nleba anya n'oge nke ihe dabere na ahihia ahihia n'ime ahihia ahihia site na iji ihe onyonyo UAV di elu. Agron. Na-akwado. Dev. 36 (4), 1–12
Lopez-Granados, 'F., Torres-S' anchez, J., Serrano-P'erez, A., de Castro, AI, MesasCarrascosa, F.-J., Pena, ˜ J.-M., 2016. Maapụ ahihia nke oge mbụ na sunflower site na iji teknụzụ UAV: mgbanwe nke maapụ ọgwụgwọ ahịhịa megide oke ahịhịa. Precis. Agric. 17 (2), 183–199.
Lucieer, A., Malenovský, Z., Veness, T., Wallace, L., 2014. HyperUAS - imaging spectroscopy site na multirotor na-enweghị usoro ụgbọ elu. J. Field Rob. 31 (4),
571–590. https://doi.org/10.1002/rob.21508.
Lumme, J., Karjalainen, M., Kaartinen, H., Kukko, A., Hyyppa, ¨ J., Hyypp¨ a, H., Jaakkola, A., & Kleemola, J., 2008. Ihe nyocha laser nke ala ihe ubi ugbo. Na JJ
Chen J. Maas H–G. (Ed.), International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences—ISPRS Archives (Vol. 37, p. 563–566).
International Society for Photogrammetry na Remote Sensing. https://www.scopus .com/inward/record.uri?eid=2-s2.0-84919356328&partnerID=40&md5=574
b802131a99d16318ce619a01ca1bf.
Ma, L., Li, M., Ma, X., Cheng, L., Du, P., Liu, Y., 2017. Nlebanya nke nhazi ihe oyiyi mkpuchi ala dabere na ihe a na-achịkwa. ISPRS J. Foto foto. Sens dịpụrụ adịpụ 130,
277–293. https://doi.org/10.1016/j.isprsjprs.2017.06.001.
Maes, WH, Steppe, K., 2019. Echiche maka nhụta anya na ụgbọ ala ikuku na-enweghị mmadụ na ọrụ ugbo ziri ezi. Trends Osisi Sci. 24 (2), 152–164. https://doi.org/10.1016/j.tplants.2018.11.007.
Maimaitijiang, M., Ghulam, A., Sidike, P., Hartling, S., Maimaitiyiming, M., Peterson, K., Shavers, E., Fishman, J., Peterson, J., Kadam, S., Burken, J., Fritschi, F., 2017.
Sistemụ ikuku na-enweghị mmadụ (UAS) dabere na phenotyping nke soybean site na iji ngwakọta data ọtụtụ sensọ na igwe mmụta dị oke egwu. ISPRS J. Foto foto. Sens dịpụrụ adịpụ 134, 43–58. https://doi.org/10.1016/j.isprsjprs.2017.10.011. Maimaitijiang, M., Sagan, V., Sidike, P., Daloye, AM, Erkbol, H., Fritschi, FB, 2020.
Nyochaa ihe ubi site na iji satịlaịtị/UAV data fusion na igwe mmụta. Nhụta anya 12 (9), 1357. https://doi.org/10.3390/rs12091357.
Manfreda, S., McCabe, M., Miller, P., Lucas, R., Pajuelo Madrigal, V., Mallinis, G., Ben Dor, E., Helman, D., Estes, L., Ciraolo, G. ., Müllerova, 'J., Tauro, F., de Lima, M., de
Lima, J., Maltese, A., Frances, F., Caylor, K., Kohv, M., Perks, M., Ruiz-Perez, G., Su, Z., Vico, G., Toth , B., 2018. Na ojiji nke ikuku ikuku na-adịghị mma maka
nlekota gburugburu ebe obibi. Mmetụta dị anya 10 (4), 641.
Marinko, RA, 1998. Ntụta aka n’akwụkwọ akụkọ ọmụmụ ụmụ nwanyị na akwụkwọ nta akụkọ, 1989 na The Serials Librarian 35 (1–2), 29–44. https://doi.org/10.1300/J123v35n01_
03.
Masroor, R., Naeem, M., Ejaz, W., 2021. Njikwa akụrụngwa na netwọk ikuku na-enyere UAV aka: echiche njikarịcha. Netwọk Ad Hoc. 121, 102596 https://doi.org/10.1016/j.adhoc.2021.102596.
Matese, A., Di Gennaro, SF, 2018. Ngwa bara uru nke multisensor UAV n'elu ikpo okwu dabere na multispectral, thermal na RGB elu mkpebi oyiyi na nkenke.
viticulture. Ọrụ ugbo 8 (7), 116. https://doi.org/10.3390/agriculture8070116.
Matese, A., Di Gennaro, SF, 2021. Na-agafe NDVI omenala dị ka isi ihe na-eme ka ojiji nke UAV dị na viticulture ziri ezi. Sci. Nchikota 11 (1), 2721. https://doi.org/10.1038/s41598-021-81652-3.
Matese, A., Toscano, P., Di Gennaro, SF, Genesio, L., Vaccari, FP, Primicerio, J., Belli, C., Zaldei, A., Bianconi, R., Gioli, B., 2015 Intercomparison nke UAV, ụgbọ elu
yana ikpo okwu na-ahụ anya nke satịlaịtị maka viticulture ziri ezi. Nhụta anya 7 (3), 2971–2990. https://doi.org/10.3390/rs70302971.
Mazzia, V., Comba, L., Khaliq, A., Chiaberge, M., nwoke nwere mmasị nwoke, P., 2020. UAV na igwe mmụta dabere na nnụcha nke ahịhịa ahịhịa na-akwọ satịlaịtị maka nkenke.
ugbo. Sensọ 20 (9), 2530. https://doi.org/10.3390/s20092530.
McCain, KW, 1990. Ndị na-ese eserese na oghere ọgụgụ isi: nyocha teknụzụ. J. Am. Soc. Ozi. Sci. 41 (6), 433–443.
Meinen, BU, Robinson, DT, 2021. Nleba anya nbibi nke ugbo: na-enyocha USLE na WEPP n'oke oke mbuze n'iji data usoro oge UAV. Environ. Modell. Software 137, 104962. https://doi.org/10.1016/j.envsoft.2021.104962.
Melville, B., Lucieer, A., Aryal, J., 2019. Nhazi nke obodo ala ahịhịa juru na-eji hyperspectral Unmanned Aircraft System (UAS) Onyonyo na
Midlands Tasmania. Drones 3 (1), 5.
Messina, G., Modica, G., 2020. Ngwa nke UAV thermal imagery na nkenke ọrụ ugbo: steeti nka na echiche nyocha n'ọdịnihu. Nhụta anya 12 (9), https://doi.org/10.3390/rs12091491.
Mishra, D., Luo, Z., Jiang, S., Papadopoulos, T., Dubey, R., 2017. Ihe ọmụmụ akwụkwọ akụkọ banyere nnukwu data: echiche, ọnọdụ na ihe ịma aka. Njikwa Usoro azụmahịa. J. 23 (3),
555-573.
Mochida, K., Saisho, D., Hirayama, T., 2015. Mmezi ihe ubi site na iji datasets okirikiri ndụ enwetara n'okpuru ọnọdụ ubi. N'ihu. Osisi Sci. 6 https://doi.org/10.3389/
fpls.2015.00740.
Mogili, UM.R., Deepak, BBVL, 2018. Nyochaa na ngwa nke drone usoro na nkenke ugbo. Kọmpụta Procedia. Sci. 133, 502–509.
Moharana, S., Dutta, S., 2016. Mgbanwe nke oghere nke chlorophyll na nitrogen ọdịnaya nke osikapa sitere na ihe oyiyi hyperspectral. ISPRS J. Foto foto. Sens dịpụrụ adịpụ 122, 17–29.
Muangprathub, J., Boonnam, N., Kajornkasirat, S., Lekbangpong, N., Wanichsombat, A.,
Nillaor, P., 2019. IoT na nyocha data ọrụ ugbo maka ugbo smart. Kọmputa. Elektrọn. Agric. 156, 467–474 .
Nansen, C., Elliott, N., 2016. Nghọta dịpụrụ adịpụ na nlebara anya na entomology. Annu. Rev. Entomol. 61 (1), 139–158. https://doi.org/10.1146/annurev-ento010715-023834.
Navia, J., Mondragon, I., Patino, D., Colorado, J., 2016. Multispectral mapping in agriculture: terrain mosaic iji kwụụrụ quadcopter UAV. Int. Conf.
Sistemụ ụgbọ elu enweghị mmadụ. (ICUAS) 2016, 1351–1358. https://doi.org/10.1109/ ICUAS.2016.7502606.
Nayyar, A., Nguyen, B.-L., Nguyen, NG, 2020. Ịntanetị nke drone ihe (Iodt): n'ọdịnihu echiche nke smart drones. Adv. Ọgụgụ isi. Sistemụ Kọmputa. 1045, 563–580. https://doi.org/10.1007/978-981-15-0029-9_45.
Nebiker, S., Annen, A., Scherrer, M., Oesch, D., 2008. A ìhè-arọ multispectral sensọ maka micro UAV-ohere maka nnọọ elu mkpebi airborne remote sensing. Int. Arch. Foto. Sens dịpụrụ adịpụ Spat. Inf. Sci 37 (B1), 1193–1200.
Negash, L., Kim, H.-Y., Choi, H.-L., 2019. Emerging UAV ngwa na ugbo. Na: 2019 7th International Conference on Robot Intelligence Technology na
Ngwa (RiTA), p. 254–257. https://doi.org/10.1109/RITAPP.2019.8932853.
Nerur, SP, Rasheed, AA, Natarajan, V., 2008. Usoro ọgụgụ isi nke ngalaba njikwa usoro: onye na-ede akwụkwọ nchịkọta akụkọ. Atụmatụ. Jikwaa. J. 29 (3),
319-336.
Neupane, K., Baysal-Gurel, F., 2021. Nchọpụta na-akpaghị aka na nlekota nke ọrịa osisi na-eji ụgbọ ala ikuku na-enweghị mmadụ: nyocha. Mmetụta dị anya 13 (19), 3841. https://doi.org/10.3390/rs13193841.
Nex, F., Remondino, F., 2014. UAV maka ngwa maapụ 3D: nyocha. Ngwa. Geomatik 6 (1), 1–15. https://doi.org/10.1007/s12518-013-0120-x.
Niu, H., Hollenbeck, D., Zhao, T., Wang, D., Chen, Y., 2020. Ntụle Evapotranspiration na obere UAV na nkenke ugbo. Sensọ 20 (22), 6427. https://
doi.org/10.3390/s20226427.
Osareh, F., 1996. Bibliometrics, ntụle ntụaka na nyocha ọnụ ọgụgụ. Ntụleghachi nke Akwụkwọ I 46 (3), 149–158. https://doi.org/10.1515/libr.1996.46.3.149.
P′ adua, L., Vanko, J., Hruˇska, J., Ad˜ ao, T., Sousa, JJ, Peres, E., Morais, R., 2017. UAS, sensọ, na nhazi data na agroforestry: nyochaa kwupụta ngwa bara uru. Int. J. Sens dịpụrụ adịpụ 38 (8–10), 2349–2391. https://doi.org/10.1080/01431161.2017.1297548.
Panday, US, Pratihast, AK, Aryal, J., Kayasta, RB, 2020. Ntụleghachi na ngwọta data dabere na drone maka mkpụrụ ọka ọka. Drones 4 (3), 1–29. https://doi.org/10.3390/
drones 4030041.
Parsaeian, M., Shahabi, M., Hassanpour, H., 2020. Na-echepụta mmanụ na protein ọdịnaya nke mkpụrụ sesame site na iji nhazi ihe oyiyi na netwọk neural. J. Am. Mmanụ
Ndị Chemists' Soc. 97 (7), 691–702 .
Pena, ˜ JM, Torres-S′anchez, J., de Castro, AI, Kelly, M., Lopez-Granados, 'F., Suarez, O., Maapụ ahịhịa n'ubi ọka n'oge oge site na iji nyocha ihe dabere na ihe. nke
Onyonyo ụgbọ ala na-enweghị mmadụ (UAV). PLoS ONE 8 (10), e77151.
Perez-Ortiz, M., Pena, ˜ JM, Guti'errez, PA, Torres-S' anchez, J., Herv' as-Martínez, C.,
Lopez-Granados, 'F., 2015. Usoro a na-ahụ maka ọkara maka ịse ahihia na mkpụrụ osisi sunflower na-eji ụgbọ ala ikuku na-enweghị mmadụ na usoro nchọpụta ahịrị ihe ọkụkụ. Ngwa. Kọmputa dị nro. J. 37, 533–544. https://doi.org/10.1016/j.asoc.2015.08.027.
Pincheira, M., Vecchio, M., Giaffreda, R., Kanhere, SS, 2021. Ngwa IoT dị ọnụ ahịa dị ka isi mmalite data a pụrụ ịdabere na ya maka usoro nchịkwa mmiri nke dabeere na blockchain na ọrụ ugbo ziri ezi. Kọmputa. Elektrọn. Agric. 180, 105889.
Popescu, D., Stoican, F., Stamatescu, G., Ichim, L., Dragana, C., 2020. Advanced UAV–WSN usoro maka ọgụgụ isi nlekota oru na nkenke ugbo. Sensọ 20 (3), https://doi.org/10.3390/s20030817.
Pournader, M., Shi, Y., Seuring, S., Koh, SL, 2020. Ngwa Blockchain na ụdọ ọkọnọ, njem na ngwa agha: nyochaa nhazi nke akwụkwọ. Int. J. Prod. Res. 58 (7), 2063–2081.
Primicerio, J., Di Gennaro, SF, Fiorillo, E., Genesio, L., Lugato, E., Matese, A., Vaccari, FP, 2012. Ụgbọ ala ikuku na-enweghị onye na-agbanwe agbanwe maka ọrụ ugbo ziri ezi.
Precis. Agric. 13 (4), 517–523 . https://doi.org/10.1007/s11119-012-9257-6.
Pritchard, A., 1969. Akwụkwọ ndekọ ọnụ ọgụgụ ma ọ bụ akwụkwọ ọgụgụ. J. Akwụkwọ. 25 (4), 348–349 .
Pudelko, R., Stuczynski, T., Borzecka-Walker, M., 2012. Kwesịrị ekwesị nke ụgbọ elu ikuku na-adịghị mma (UAV) maka nyocha nke ubi nnwale na ihe ọkụkụ. Ọrụ ugbo 99 (4), 431–436.
Puri, V., Nayyar, A., Raja, L., 2017. Agriculture drones: ọganihu ọgbara ọhụrụ na ọrụ ugbo ziri ezi. J. Statis. Jikwaa. Sistemụ 20 (4), 507–518.
Radoglou-Grammatikis, P., Sarigiannidis, P., Lagkas, T., Moscholios, I., 2020. Mkpokọta ngwa UAV maka ezigbo ọrụ ugbo. Kọmputa. Netwọk 172,
107148 https://doi.org/10.1016/j.comnet.2020.107148.
Ramesh, KV, Rakesh, V., Prakasa Rao, EVS, 2020. Ngwa nke nnukwu nyocha data na ọgụgụ isi artificial na nyocha agronomic. Onye India J. Agron. 65 (4), 383–395.
Raparelli, E., Bajocco, S., 2019. Ntụle nke akwụkwọ nsọ maka iji ụgbọ ala ikuku na-enweghị mmadụ na ọmụmụ ihe gbasara ugbo na oke ohia. Int. J. Sens dịpụrụ adịpụ 40 (24),
9070-9083. https://doi.org/10.1080/01431161.2019.1569793.
Rasmussen, J., Nielsen, J., Garcia-Ruiz, F., Christensen, S., Streibig, JC, Lotz, B., 2013.
Enwere ike iji obere sistemu ụgbọ elu na-enweghị mmadụ (UAS) na nyocha ahịhịa. Igbo Res. 53 (4), 242–248 .
Rasmussen.
Ndị UAV nwere ntụkwasị obi zuru oke maka ịtụle atụmatụ nnwale? Euro. J. Agron. 74, 75–92. https://doi.org/10.1016/j.eja.2015.11.026.
Rejeb, A., Rejeb, K., Abdollahi, A., Zailani, S., Iranmanesh, M., Ghobakhloo, M., 2022. Dijitalụ n'agbụ ndị na-enye nri: nyochaa bibliometric na ụzọ isi ụzọ isi.
nyocha. Nkwado 14 (1), 83. https://doi.org/10.3390/su14010083.
Rejeb, A., Rejeb, K., Simske, SJ, Treiblmaier, H., 2021a. Drones maka njikwa usoro ọkọnọ na ngwa agha: nyocha na atụmatụ nyocha. Int. J. Logist. Res. Ngwa.
1-24. https://doi.org/10.1080/13675567.2021.1981273.
Rejeb, A., Rejeb, K., Simske, S., Treiblmaier, H., 2021b. Teknụzụ Blockchain na ngwa ngwa na njikwa usoro ọkọnọ: nyocha bibliometric. Ngwa ngwa 5 (4), 72.
https://doi.org/10.3390/logistics5040072.
Rejeb, A., Rejeb, K., Simske, S., Treiblmaier, H., 2021c. Drones ndị mmadụ: nyocha na atụmatụ nyocha. Ịntanetị nke Ihe 16, 100434. https://doi.org/10.1016/j.
iot.2021.100434.
Rejeb, A., Treiblmaier, H., Rejeb, K., Zailani, S., 2021d. Nchọpụta Blockchain na ahụike: nyocha bibliometric na usoro nyocha ugbu a. J. nke Data, Inf. na
Jikwaa. 3 (2), 109–124.
Rejeb, A., Simske, S., Rejeb, K., Treiblmaier, H., Zailani, S., 2020. Nchọpụta ịntanetị nke ihe na njikwa usoro ọkọnọ na ngwa agha: nyocha nke bibliometric. Ịntanetị
nke ihe 12, 100318.
ReportLinker, 2021. Global Agriculture Drones Market ga-eru ijeri US $15.2 site n'ime ụlọ akụkọ YearGlobeNewswire. https://www.globenewswire.com/news-release/2021/08/10/2277986/0/en/Global-Agriculture-Drones-Market-to-Reach-US-15-2-Billion-by-the- Afọ-2027.html.
Ribeiro-Gomes, K., Hernandez-L 'opez, 'D., Ortega, JF, Ballesteros, R., Poblete, T., Moreno, MA, 2017. Uncooled thermal igwefoto calibration na njikarịcha nke
Usoro fotogrammetry maka ngwa UAV na ọrụ ugbo. Sensọ (Switzerland) 17 (10). https://doi.org/10.3390/s17102173.
Rivera, MA, Pizam, A., 2015. Ọganihu na nyocha ile ọbịa: "Site na Rodney Dangerfield ruo Aretha Franklin". Int. J. Contempor. Ụlọ ọgwụ. Jikwaa. 27 (3),
362–378. https://doi.org/10.1108/IJCHM-03-2014-0146.
Roldan, 'JJ, Joossen, G., Sanz, D., Del Cerro, J., Barrientos, A., 2015. Mini-UAV dabeere sensory usoro maka ịlele gburugburu ebe obibi variables na greenhouses. Sensọ 15 (2), 3334–3350. https://doi.org/10.3390/s150203334.
Rozenberg, G., Kent, R., Blank, L., 2021. UAV-ọkwa ndị ahịa ejiri maka ịchọpụta na nyochaa usoro nkesa ahịhịa n'ubi yabasị azụmahịa. Precis. Agric. 22 (4), 1317–1332. https://doi.org/10.1007/s11119-021-09786-y.
Saari, H., Pellikka, I., Pesonen, L., Tuominen, S., Heikkila, ¨ J., Holmlund, C., Makynen, ¨ J., Ojala, K., Antila, T., 2011. A naghị eji mmadụ Ụgbọ ala (UAV) na-arụ usoro igwefoto spectral maka oke ọhịa na ngwa ọrụ ugbo. Gaba. SPIE – Int. Soc. Wepụ Eng. 8174 https://doi.org/10.1117/12.897585.
Sah, B., Gupta, R., Bani-Hani, D., 2021. Nyochaa ihe mgbochi iji mejuputa ngwa agha drone. Int. J. Logist. Res. Ngwa. 24 (6), 531–550. https://doi.org/10.1080/
13675567.2020.1782862.
Saha, AK, Saha, J., Ray, R., Sircar, S., Dutta, S., Chattopadhyay, SP, & Saha, HN, IOT dabeere na drone maka imeziwanye ihe ọkụkụ n'ubi ugbo. Na SH
N. Chakrabarti S. (Ed.), 2018 IEEE 8th Annual Computing and Communication Workshop and Communication, CCWC 2018 (Vols. 2018-January, p. 612-615). Ụlọ akwụkwọ
nke Eletriki na Eletrọnịkị Injinia Inc. doi: 10.1109/CCWC.2018.8301662.
Sai Vineeth, KV, Vara Prasad, YR, Dubey, SR, Venkataraman, H., 2019. LEDCOM: a akwụkwọ akụkọ na oru oma LED nkwurịta okwu dabeere na nkenke ugbo. IEEE Conf. Ozi. Kọmun. Teknụzụ 2019, 1–5. https://doi.org/10.1109/CICT48419.2019.9066177.
Salamí, E., Barrado, C., Pastọ, E., 2014. UAV ụgbọ elu nnwale etinyere n'ime ime nghọta nke vegetated ebe. Mmetụta dị anya 6 (11), 11051–11081. https://doi.org/10.3390/rs61111051.
Sankaran, S., Khot, LR, Espinoza, CZ, Jarolmasjed, S., Sathuvalli, VR, Vandemark, GJ, Miklas, PN, Carter, AH, Pumphrey, MO, Knowles, NRN, Pavek, MJ, 2015.
Sistemụ onyonyo ikuku dị ala, mkpebi dị elu maka eserese phenotyping na ubi ubi: nyocha. Euro. J. Agron. 70, 112–123 . https://doi.org/10.1016/j.
azụ.2015.07.004.
Santesteban, LG, Di Gennaro, SF, Herrero-Langreo, A., Miranda, C., Royo, JB, Matese, A., 2017. Igwe ọkụ dị elu nke dabeere na UAV iji tụọ anya
mgbanwe ozugbo na nke oge nke ọnọdụ mmiri osisi n'ime ubi-vine. Agric. Onye njikwa mmiri. 183, 49–59 . https://doi.org/10.1016/j.agwat.2016.08.026.
Sarli, CC, Dubinsky, EK, Holmes, KL, 2010. N'ofè ntụle nyocha: Nlereanya maka ntule nke nchọpụta mmetụta. J. Med. Ụlọ akwụkwọ Assoc. : JMLA 98 (1), 17–23. https://doi.org/10.3163/1536-5050.98.1.008.
Schaepman, ME, Ustin, SL, Plaza, AJ, Onye na-ese ihe, TH, Verrelst, J., Liang, S., 2009. Sayensị sistemu ụwa metụtara ihe onyonyo onyonyo—ntụle. gburugburu Sens. 113, S123–S137.
Schirmann, M., Giebel, A., Gleiniger, F., Pflanz, M., Lentschke, J., Dammer, K.-H., 2016. Nleba anya agronomic parameters nke oyi ọka wheat n'ubi na UAV dị ọnụ ala.
onyonyo. Nhụta anya 8 (9). https://doi.org/10.3390/rs8090706.
Schmale III, DG, Dingus, BR, Reinholtz, C., 2008. Mmepe na ntinye nke ụgbọ elu ikuku na-enweghị onye kwụụrụ onwe ya maka nlele anya ikuku dị n'elu.
ugbo ugbo. J. Field Rob. 25 (3), 133–147. https://doi.org/10.1002/rob.20232.
Shadrin, D., Menshchikov, A., Somov, A., Bornemann, G., Hauslage, J., Fedorov, M.,
Na-eme ka ọrụ ugbo dị mma site na nghọta agbakwunyere na ọgụgụ isi. IEEE Trans. Ngwá ọrụ. Meas. 69 (7), 4103–4113 .
Shakhatreh, H., Sawalmeh, AH, Al-Fuqaha, A., Dou, Z., Almaita, E., Khalil, I.,
Othman, NS, Khreishah, A., Guizani, M., 2019. Ụgbọ ala ikuku na-adịghị mma (UAV): nyocha gbasara ngwa obodo na isi ihe ịma aka nyocha. Nweta IEEE 7,
48572–48634. https://doi.org/10.1109/ACCESS.2019.2909530.
Shakoor, N., Northrup, D., Murray, S., Mockler, TC, 2019. Nnukwu data chụpụrụ agriculture: nnukwu data analytics na osisi ozuzu, genomics, na ojiji nke remote sensing.
teknụzụ iji kwalite mmepụta ihe ọkụkụ. Phenome Osisi J. 2 (1), 1–8.
Sharma, BK, Chandra, G., Mishra, VP, 2019. Ntụle ntụle na ntinye aka nke UAV na AI na nyocha nke Forensic. Na: Usoro - 2019 Amity International
Nzukọ na ọgụgụ isi Artificial. https://doi.org/10.1109/AICAI.2019.8701407.
Sharma, R., Shishodia, A., Gunasekaran, A., Min, H., Munim, ZH, 2022. Ọrụ nke ọgụgụ isi na-arụ ọrụ na njikwa usoro ọkọnọ: nhazi ókèala. Int. J.
Prod. Res. 1–24. https://doi.org/10.1080/00207543.2022.2029611.
Shi, Y., Thomasson, JA, Murray, SC, Pugh, NA, Rooney, WL, Shafian, S., Rajan, N., Rouze, G., Morgan, CLS, Neely, HL, Rana, A., Bagavathiannan , MV,
Henrickson, J., Bowden, E., Valasek, J., Olsenholler, J., Bishop, MP, Sheridan, R., Putman, EB, Popescu, S., Burks, T., Cope, D., Ibrahim, A., McCutchen, BF,
Baltensperger, DD, Avant, RV, Vidrine, M., Yang, C., Zhang, J., 2016. Ụgbọ ala ikuku na-adịghị mma maka phenotyping dị elu na nyocha agronomic. PLoS ONE
11 (7), e0159781.
Shuai, G., Martinez-Feria, RA, Zhang, J., Li, S., Price, R., Basso, B., 2019. Na-ejide ụdị ọka dị iche iche n'ofe mpaghara mkpụrụ-kwụsi ike site na iji ikuku ikuku na-adịghị mma.
Ụgbọ ala (UAV). Sensọ 19 (20), 4446. https://doi.org/10.3390/s19204446.
Obere, H., 1973. Co-citation na akwụkwọ sayensị: ihe ọhụrụ nke mmekọrịta dị n'etiti akwụkwọ abụọ. J. Am. Soc. Ozi. Sci. 24 (4), 265–269 .
Small, H., Rorvig, ME, Lunin, LF, 1999. Ịhụ sayensị anya site na nkewa okwu. J. Am. Soc. Ozi. Sci. 50 (9), 799–813 .
Soares, VHA, Ponti, MA, Gonçalves, RA, Campello, RJGB, 2021. Ngụkọta ehi n'ime ọhịa nwere ihe oyiyi ikuku geolocated na nnukwu ebe ịta nri. Kọmputa. Elektrọn. Agric. 189, 106354 https://doi.org/10.1016/j.compag.2021.106354.
Srivastava, K., Pandey, PC, Sharma, JK, 2020. Ụzọ maka njikarịcha ụzọ n'ime ngwa ọrụ ugbo ziri ezi site na iji UAV. Drones 4 (3), 58. https://doi.org/ 10.3390/drones4030058.
Stafford, JV, 2000. Na-arụ ọrụ ugbo nke ọma na narị afọ 21st. J. Agric. Eng. Res. 76 (3), 267–275.
Su, J., Coombes, M., Liu, C., Guo, L., Chen, W.-H., 2018. Ntụle ọka wit site na nhụta ihe onyonyo dịpụrụ adịpụ site na iji ụgbọ elu na-enweghị mmadụ. Na 2018 37th Chinese Control Conference (CCC).
Su, J., Liu, C., Coombes, M., Hu, X., Wang, C., Xu, X., Li, Q., Guo, L., Chen, W.-H., 2018. Nlebanya nchara na-acha odo odo nke ọka wit site n'ịmụta site na onyonyo ikuku UAV multispectral.
Kọmputa. Elektrọn. Agric. 155, 157–166 . https://doi.org/10.1016/j. compag.2018.10.017.
Su, Y., Wang, X., 2021. Innovation nke agricultural aku na uba management na usoro nke na-ewu smart agriculture site nnukwu data. Kọmpụta na-adịgide adịgide. Inf. Sistemụ 31, 100579 https://doi.org/10.1016/j.suscom.2021.100579.
Sullivan, DG, Fulton, JP, Shaw, JN, Bland, GL, 2007. Ịtụle uche nke ikuku infrared thermal na-adịghị ahụkebe iji chọpụta nrụgide mmiri na mkpuchi owu. Trans. ASABE 50 (6), 1955–1962.
Sumesh, KC, Ninsawat, S., Som-ard, J., 2021. Njikọta nke ahịhịa ahịhịa dabere na RGB, ihe nlere elu ihe ọkụkụ na usoro nyocha ihe onyonyo dabere na ihe maka nleba anya mkpụrụ okpete site na iji ụgbọ elu na-enweghị mmadụ. Kọmputa. Elektrọn. Agric. 180, 105903 https://doi.org/10.1016/j.compag.2020.105903.
Suomalainen, J., Anders, N., Iqbal, S., Franke, J., Wenting, P., Bartholomeus, H., Becker, R., Kooistra, L., 2013. A na-arọ nke hyperspectral maapụ usoro maka.
Ụgbọ ala ndị a na-ejighị mmadụ—mpụta nke mbụ. Na: 2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), p. 1–4. https://doi.org/10.1109/WHISPERS.2013.8080721.
Suomalainen, J., Anders, N., Iqbal, S., Roerink, G., Franke, J., Wenting, P., Hünniger, D., Bartholomeus, H., Becker, R., Kooistra, L., 2014. Igwe nlegharị anya dị fechaa
Sistemụ eserese eserese na yinye nhazi fotogrammetric maka ụgbọ ala na-enweghị mmadụ. Mmetụta dị anya 6 (11), 11013–11030. https://doi.org/10.3390/
rs61111013.
Syeda, IH, Alam, MM, Illahi, U., Su'ud, MM, 2021. Atụmatụ njikwa aga n'ihu na-eji nhazi onyonyo, UAV na AI na ọrụ ugbo: nyocha. Ụwa J. Eng. 18 (4),
579–589. https://doi.org/10.1108/WJE-09-2020-0459.
Tahai, A., Rigsby, JT, 1998. Nhazi ozi na-eji ntụaka iji nyochaa mmetụta akwụkwọ akụkọ na ndekọ ego. Inf. Usoro. Jikwaa. 34 (2–3), 341–359.
Tang, Y., Dananjayan, S., Hou, C., Guo, Q., Luo, S., He, Y., 2021. Nnyocha na netwọk 5G na mmetụta ya na ọrụ ugbo: ihe ịma aka na ohere. Kọmputa.
Elektrọn. Agric. 180, 105895 https://doi.org/10.1016/j.compag.2020.105895.
Tantalaki, N., Souravlas, S., Roumeliotis, M., 2019. Mkpebi na-akpata data na-eme n'ụzọ ziri ezi: ịrị elu nke nnukwu data na usoro ugbo. J. Agric. Ozi nri.
20 (4), 344-380.
Tao, H., Feng, H., Xu, L., Miao, M., Yang, G., Yang, X., Fan, L., 2020. Atụmatụ nke mkpụrụ na osisi elu oyi ọka wheat iji UAV- onyonyo hyperspectral dabere.
Sensọ 20 (4), 1231.
Techy, L., Schmale III, DG, Woolsey, CA, 2010. Nhazi aerobiological sampling nke a osisi pathogen n'ime ala ikuku na-eji abụọ kwụụrụ onwe na-enweghị igwe ugbo ala. J. Field Rob. 27 (3), 335–343. https://doi.org/10.1002/rob.20335.
Tetila, EC, Machado, BB, Astolfi, G., Belete, NAdS, Amorim, WP, Roel, AR, Pistori, H., 2020. Nchọpụta na nhazi nke pests soybean site na iji mmụta miri emi.
ya na onyonyo UAV. Kọmputa. Elektrọn. Agric. 179, 105836.
Thamm, H.-P., Menz, G., Becker, M., Kuria, DN, Misana, S., Kohn, D., 2013. Ojiji nke Uas maka nyochaa usoro ugbo na AN Wetland na Tanzania na- Na WetSeason maka ọrụ ugbo na-adịgide adịgide yana inye eziokwu ala maka data Terra-Sar X. N'ime: ISPRS - Ebe nchekwa ụwa nke fotogrammetry, ihe nhụta anya na sayensị ozi gbasara ohere, p. 401-406. https://doi.org/10.5194/isprsarchivesXL-1-W2-401-2013.
Thelwall, M., 2008. Bibliometrics ka webometrics. J. Ama. Sci. 34 (4), 605–621 .
Torres-Sanchez, 'J., Lopez-Granados, 'F., Pena, ˜ JM, 2015. Usoro na-akpaghị aka na-adabere na ihe maka njedebe kacha mma na onyonyo UAV: ngwa maka nchọpụta ahịhịa na ahịhịa ahịhịa. Kọmputa. Elektrọn. Agric. 114, 43–52 . https://doi.org/10.1016/j.compag.2015.03.019.
Torres-Sanchez, 'J., Lopez-Granados, 'F., Serrano, N., Arquero, O., Pena, ˜ JM, Hassan, QK, 2015. Nleba anya 3-D dị elu nke ubi-osisi na-arụ ọrụ ugbo. Teknụzụ ụgbọ elu na-enweghị mmadụ (UAV). PLoS ONE 10 (6), e0130479.
Torres-Sanchez, 'J., Pena, ˜ JM, de Castro, AI, Lopez-Granados, 'F., 2014. Multi-oge nke maapụ nke ntakiri ahịhịa na mmalite-oge ubi ọka wit na-eji ihe oyiyi si UAV. Kọmputa. Elektrọn. Agric. 103, 104–113. https://doi.org/10.1016/j. mkpọ.2014.02.009.
Tsouros, DC, Bibi, S., Sarigiannidis, PG, 2019. Nyochaa na ngwa UAV maka ọrụ ugbo ziri ezi. Ozi (Switzerland) 10 (11). https://doi.org/10.3390/info10110349.
Tu, Y.-H., Phinn, S., Johansen, K., Robson, A., Wu, D., 2020. Na-ebuli atụmatụ ụgbọ elu drone maka ịlele nhazi ihe ọkụkụ osisi horticultural. ISPRS J. Foto foto.
Sens dịpụrụ adịpụ 160, 83–96. https://doi.org/10.1016/j.isprsjprs.2019.12.006
Tzounis, A., Katsoulas, N., Bartzanas, T., Kittas, C., 2017. Ịntanetị nke ihe na ọrụ ugbo, ọganihu na-adịbeghị anya na ihe ịma aka n'ọdịnihu. Biosyst. Eng. 164, 31–48.
https://doi.org/10.1016/j.biosystemseng.2017.09.007.
Uddin, A., Singh, VK, Pinto, D., Olmos, I., 2015. Scientometric map nke sayensị kọmputa na Mexico. Scientometrics 105 (1), 97–114.
UN., 2019. Atụmanya ọnụ ọgụgụ ụwa 2019. https://population.un.org/wpp/ (Nweta na 15/04/2022).
Uto, K., Seki, H., Saito, G., Kosugi, Y., 2013. Njirimara nke osikapa osikapa site na UAVmounted miniature hyperspectral sensọ. IEEE J. Sel. N'elu. Ngwa. Ụwa Obs.
Sens dịpụrụ adịpụ 6 (2), 851–860. https://doi.org/10.1109/JSTARS.2013.2250921. van der Merwe, D., Burchfield, DR, Witt, TD, Ahịa, KP, Sharda, A., 2020. Drones na
ugbo. Adv. Agron. 162, 1–30.
Velusamy, P., Rajendran, S., Mahendran, RK, Naseer, S., Shafiq, M., Choi, J.-G., 2022.
Ụgbọ ala ikuku na-enweghị mmadụ (UAV) na ọrụ ugbo ziri ezi: ngwa na ihe ịma aka. Ike 15 (1), 217. https://doi.org/10.3390/en15010217.
Ventura, D., Bonifazi, A., Gravina, MF, Belluscio, A., Ardizzone, G., 2018. Maapụ na nhazi nke ebe obibi mmiri na-ahụ maka gburugburu ebe obibi site na iji ikuku ikuku na-adịghị mma.
Onyonyo ụgbọ ala (UAV) yana nyocha onyonyo dabere n'ihe (OBIA). Nhụta anya 10 (9), 1331. https://doi.org/10.3390/rs10091331.
Verger, A., Vigneau, N., Cheron, C., Gilliot, J.-M., Comar, A., Baret, F., 2014. Green mpaghara index sitere na ikuku ikuku na-enweghị mmadụ n'elu ọka wit na n'ike n'ike. . gburugburu Sens. 152, 654–664. https://doi.org/10.1016/j.rse.2014.06.006.
Von Bueren, SK, Burkart, A., Hueni, A., Rascher, U., Tuohy, MP, Yule, IJ, 2015. Na-ebuga ihe mmetụta anọ anya UAV dabeere na ala ahịhịa: ihe ịma aka na
oke. Biogeosciences 12 (1), 163–175. https://doi.org/10.5194/bg-12-163-2015.
Vuran, MC, Salam, A., Wong, R., Irmak, S., 2018. Ịntanetị nke n'okpuruala ihe na nkenke ugbo: ije na technology akụkụ. Netwọk Ad Hoc. 81,
160–173. https://doi.org/10.1016/j.adhoc.2018.07.017.
Wamba, SF, Queiroz, MM, 2021. Ọgụgụ isi na-arụ ọrụ dị ka ihe nzuzo nzuzo maka ahụike dijitalụ: nyocha nke bibliometric, nghọta, na ntụzịaka nyocha.
Ozi. Sistemụ N'ihu. 1–16.
Wang, L., Zhang, G., Wang, Z., Liu, J., Shang, J., Liang, L., 2019. Ntụle ihe omimi nke akwụkwọ nyocha nke ime ihe na-eme n'ime ime nleba anya n'ihe ọkụkụ: Ọmụmụ ihe na China. Nhụta anya 11 (7). https://doi.org/10.3390/rs11070809.
Ọcha, HD, Griffith, BC, 1981. Cocitation odee: Ntụle akwụkwọ nke nhazi ọgụgụ isi. J. Am. Soc. Ozi. Sci. 32 (3), 163–171.
Xiang, H., Tian, L., 2011. Mmepe nke a obere ọnụ ala ugbo ala n'ime ime mmetụta usoro dabere na kwụụrụ onwe unmaned aerial ugbo ala (UAV). Biosyst. Eng. 108 (2), 174–190. https://doi.org/10.1016/j.biosystemseng.2010.11.010.
Xie, C., Yang, C., 2020. A nyochaa na osisi elu-throughput phenotyping àgwà iji UAVbased sensọ. Kọmputa. Elektrọn. Agric. 178, 105731 https://doi.org/10.1016/j.
compag.2020.105731.
Yao, H., Qin, R., Chen, X., 2019. Ụgbọ ala na-enweghị mmadụ maka ngwa nhụta anya—nyocha. Nhụta anya 11 (12). https://doi.org/10.3390/
rs11121443.
Yeom, S., 2021. Na-akpụ akpụ ndị mmadụ na-esochi na egwu ụgha wepụ ya na infrared thermal imaging site na multirotor. Drones 5 (3), 65. https://doi.org/10.3390/drones5030065.
Yue, J., Feng, H., Jin, X., Yuan, H., Li, Z., Zhou, C., Yang, G., Tian, Q., 2018. Ntụle nke akuku parameters iji onyogho sitere na UAV-ndokwasa
ihe mmetụta ihe mmetụta hyperspectral na igwefoto dijitalụ nwere nkọwa dị elu. Nhụta anya 10 (7), 1138. https://doi.org/10.3390/rs10071138.
Yue, J., Yang, G., Li, C., Li, Z., Wang, Y., Feng, H., Xu, B., 2017. Atụmatụ nke oyi ọka wheat n'elu-ala biomass eji unmanned ikuku ugbo ala- onyonyo dabere
ihe mmetụta hyperspectral na ịdị elu akuku emelitere ụdị. Nhụta anya 9 (7). https://doi.org/10.3390/rs9070708.
Zahawi, RA, Dandois, JP, Holl, KD, Nadwodny, D., Reid, JL, Ellis, EC, 2015. N'iji ụgbọ ala ikuku na-adịghị arọ dị arọ na-adịghị ahụkebe iji nyochaa mgbake nke oke ọhịa. Biol.
Chekwa. 186, 287–295. https://doi.org/10.1016/j.biocon.2015.03.031. Zamora-Izquierdo, MA, Santa, J., Martínez, JA, Martínez, V., Skarmeta, AF, 2019.
Smart Farming IoT ikpo okwu dabere na ihu na igwe ojii. Biosyst. Eng. 177,
4-17.
Zarco-Tejada, PJ, Diaz-Varela, R., Angileri, V., Loudjani, P., 2014. Osisi dị elu quantification site na iji ihe oyiyi dị elu nke ukwuu enwetara site na ikuku ikuku na-adịghị mma.
ụgbọ ala (UAV) na ụzọ nrụpụta foto 3D akpaka. Euro. J. Agron. 55, 89–99 . https://doi.org/10.1016/j.eja.2014.01.004.
Zhang, C., Craine, WA, McGee, RJ, Vandemark, GJ, Davis, JB, Brown, J., Hulbert, SH, Sankaran, S., 2020. Ihe onyonyo dabere na phenotyping nke ifuru ike n'ubi oyi. Sensọ 20 (5), 1450. https://doi.org/10.3390/s20051450.
Zhang, C., Kovacs, JM, 2012. Ngwa nke obere ikuku ikuku na-enweghị mmadụ maka ọrụ ugbo ziri ezi: nyocha. Precis. Agric. 13 (6), 693–712 . https://doi.org/
10.1007/s11119-012-9274-5.
Zhang, L., Zhang, H., Niu, Y., Han, W., 2019. Maping maize mmiri nrụgide dabere na UAV multispectral remote sensing. Mmetụta dị anya 11 (6), 605.
Zhang, X., Han, L., Dong, Y., Shi, Y., Huang, W., Han, L., Gonz' alez-Moreno, P., Ma, H., Ye, H., Sobeih , T., 2019. A miri emi mmụta dabeere obibia maka akpaaka edo edo nchara
nchọpụta ọrịa sitere na onyonyo hyperspectral UAV dị elu. Mmetụta dị anya 11 (13), 1554.
Zhao, X., Zhang, J., Huang, Y., Tian, Y., Yuan, L., 2022. Nchọpụta na ịkpa ókè nke ọrịa na ahụhụ ahụhụ nke osisi tii na-eji hyperspectral imaging jikọtara na wavelet analysis. Kọmputa. Elektrọn. Agric. 193, 106717 https://doi.org/10.1016/j. compag.2022.106717.
Zheng, A., Wang, M., Li, C., Tang, J., Luo, B., 2022. Entropy eduzi adversarial ngalaba mmegharị maka ikuku semantic segmentation image. IEEE Trans. G
Zheng, H., Cheng, T., Yao, X., Deng, X., Tian, Y., Cao, W., Zhu, Y., 2016. Nchọpụta nke osikapa phenology site na usoro oge nyocha nke ala dabeere spectral. index data. Ihe ubi ubi Res. 198, 131–139. https://doi.org/10.1016/j.fcr.2016.08.027.
Zheng, J., Yang, W., 2018. Nhazi nke usoro mkpụrụ osisi nke ziri ezi nke na-adabere na ihe mmetụta ikuku. Int. J. Online Eng. 14 (05), 184 .
Zhou, L., Gu, X., Cheng, S., Yang, G., Shu, M., Sun, Q., 2020. Ntụle mgbanwe elu osisi nke ọka a na-etinye n'ime ya site na iji data UAV-LiDAR. Agriculture 10 (5), 146. https://
doi.org/10.3390/agriculture10050146.
Zhou, S., Chai, X., Yang, Z., Wang, H., Yang, C., Sun, T., 2021. Maize-IAS: Ngwanyo nyocha ihe oyiyi ọka ọka na-eji mmụta miri emi maka imepụta ihe ọkụkụ dị elu. . Ụzọ osisi 17 (1), 48. https://doi.org/10.1186/s13007-021-00747-0.
Zhou, X., Zheng, HB, Xu, XQ, He, JY, Ge, XK, Yao, X., Cheng, T., Zhu, Y., Cao, WX, Tian, YC, 2017. Na-ebu amụma mkpụrụ n'ime osikapa n'iji ahihia otutu oge
indices sitere na onyonyo multispectral na dijitalụ dabere na UAV. ISPRS J. Foto foto. Sens dịpụrụ adịpụ 130, 246–255. https://doi.org/10.1016/j.isprsjprs.2017.05.003.
Zhou, Y., Xie, Y., Shao, L., 2016. Ịme anwansị nke isi teknụzụ nke usoro nleba anya griin haus dabere na netwọk ihe mmetụta ikuku. Int. J. Online Eng. 12 (05),
43.
Zhou, Z., Majeed, Y., Diverres Naranjo, G., Gambacorta, EMT, 2021. Ntụle maka ihe ọkụkụ mmiri nrụgide na infrared thermal imagery na nkenke ugbo: nyocha.
na atụmanya ọdịnihu maka ngwa mmụta miri emi. Kọmputa. Elektrọn. Agric. 182, 106019 https://doi.org/10.1016/j.compag.2021.106019.