Abstract Emerging technologies such as high-resolution Unmanned Aerial Vehicles (UAVs) surveys combined with object-based image analysis and field surveys could represent a reliable, precise and effective tool to support land management in agricul-tural systems. The technological advances of UAVs can also promote the detection and regular monitoring of invasive alien plants and agricultural weeds. The objective of the study has been to identify, map and monitor alien weed species in agricultural systems to provide an overview on the future applications and challenges of precision farming. In particular, we evaluated how UAV imagery can be used to assess the cov-er of Oxalis pes-caprae, present in a number of crops in Sardinia as an alien invasive weed, with negative direct and indirect effects on the affected crops. Our core assump-tion is that the most reliable species discrimination can be achieved by targeting flights during flowering to allow an easier detection due to species-specific spectral differ-ences. Therefore, O. pes-caprae infestation was acquired using RGB camera installed on board of a Phantom 4 pro. As a result, we presented the mapping of O. pes-caprae, highlighting the cost-effectiveness and replicability of this approach to detect the pres-ence of this alien weed in agricultural fields.

Detection and monitoring of alien weeds using Unmanned Aerial Vehicle in agricultural systems in Sardinia (Italy) / Vanessa, Lozano; Brundu, Giuseppe Antonio Domenic; Ghiani, Luca; Piccirilli, Davide Fernando; Sassu, Alberto; Tiloca, Maria Teresa; Ledda, Luigi; Gambella, Filippo. - 67:(2020), pp. 837-844. (Intervento presentato al convegno Innovative Biosystems Engineering for Sustainable Agriculture,Forestry and Food Production, nel 12-13 September 2019) [10.1007/978-3-030-39299-4_92].

Detection and monitoring of alien weeds using Unmanned Aerial Vehicle in agricultural systems in Sardinia (Italy)

Vanessa Lozano
Writing – Original Draft Preparation
;
Giuseppe Brundu
Supervision
;
Luca Ghiani
Formal Analysis
;
Davide Piccirilli
Conceptualization
;
Alberto Sassu
Formal Analysis
;
Maria Teresa Tiloca
Formal Analysis
;
Luigi Ledda
Writing – Review & Editing
;
Filippo Gambella
Supervision
2020-01-01

Abstract

Abstract Emerging technologies such as high-resolution Unmanned Aerial Vehicles (UAVs) surveys combined with object-based image analysis and field surveys could represent a reliable, precise and effective tool to support land management in agricul-tural systems. The technological advances of UAVs can also promote the detection and regular monitoring of invasive alien plants and agricultural weeds. The objective of the study has been to identify, map and monitor alien weed species in agricultural systems to provide an overview on the future applications and challenges of precision farming. In particular, we evaluated how UAV imagery can be used to assess the cov-er of Oxalis pes-caprae, present in a number of crops in Sardinia as an alien invasive weed, with negative direct and indirect effects on the affected crops. Our core assump-tion is that the most reliable species discrimination can be achieved by targeting flights during flowering to allow an easier detection due to species-specific spectral differ-ences. Therefore, O. pes-caprae infestation was acquired using RGB camera installed on board of a Phantom 4 pro. As a result, we presented the mapping of O. pes-caprae, highlighting the cost-effectiveness and replicability of this approach to detect the pres-ence of this alien weed in agricultural fields.
2020
9783030392994
Detection and monitoring of alien weeds using Unmanned Aerial Vehicle in agricultural systems in Sardinia (Italy) / Vanessa, Lozano; Brundu, Giuseppe Antonio Domenic; Ghiani, Luca; Piccirilli, Davide Fernando; Sassu, Alberto; Tiloca, Maria Teresa; Ledda, Luigi; Gambella, Filippo. - 67:(2020), pp. 837-844. (Intervento presentato al convegno Innovative Biosystems Engineering for Sustainable Agriculture,Forestry and Food Production, nel 12-13 September 2019) [10.1007/978-3-030-39299-4_92].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11388/232247
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