A platform for research: civil engineering, architecture and urbanism
Monitoring Onion Crops Using Multispectral Imagery from Unmanned Aerial Vehicle (UAV)
Precision agriculture (PA) can be considered as management strategy of spatial and temporal variability in fields using information and communications technologies with the aim to optimize profitability, sustainability, and protection of agro-ecological services. In the context of PA and with reference to a specific case study on onion crop, the present paper shows the monitoring of fields, using multispectral imagery acquired by UAVs, through the use of different VIs. Multitemporal surveys were carried out using a fixed-wing UAV, equipped with a multispectral camera Sequoia Parrot (R-G-RedEdge-NIR). UAV MS imagery were calibrated using a panel with known reflectance and verified with a spectroradiometer (Apogee Ps-300) on bare soil and vegetation. The results of the analysis of the three datasets showed a high correlation of GNDVI and NDVI with SAVI. The latter was chosen to analyze the vegetative vigor by applying the VI to onion crop’s masks extracted after segmentation and classification of the three images by a geographical object-based image classification (GEOBIA).
Monitoring Onion Crops Using Multispectral Imagery from Unmanned Aerial Vehicle (UAV)
Precision agriculture (PA) can be considered as management strategy of spatial and temporal variability in fields using information and communications technologies with the aim to optimize profitability, sustainability, and protection of agro-ecological services. In the context of PA and with reference to a specific case study on onion crop, the present paper shows the monitoring of fields, using multispectral imagery acquired by UAVs, through the use of different VIs. Multitemporal surveys were carried out using a fixed-wing UAV, equipped with a multispectral camera Sequoia Parrot (R-G-RedEdge-NIR). UAV MS imagery were calibrated using a panel with known reflectance and verified with a spectroradiometer (Apogee Ps-300) on bare soil and vegetation. The results of the analysis of the three datasets showed a high correlation of GNDVI and NDVI with SAVI. The latter was chosen to analyze the vegetative vigor by applying the VI to onion crop’s masks extracted after segmentation and classification of the three images by a geographical object-based image classification (GEOBIA).
Monitoring Onion Crops Using Multispectral Imagery from Unmanned Aerial Vehicle (UAV)
Smart Innovation, Systems and Technologies
Bevilacqua, Carmelina (editor) / Calabrò, Francesco (editor) / Della Spina, Lucia (editor) / Messina, Gaetano (author) / Fiozzo, Vincenzo (author) / Praticò, Salvatore (author) / Siciliani, Biagio (author) / Curcio, Antonio (author) / Di Fazio, Salvatore (author) / Modica, Giuseppe (author)
INTERNATIONAL SYMPOSIUM: New Metropolitan Perspectives ; 2020 ; Online, Italy
2020-09-01
10 pages
Article/Chapter (Book)
Electronic Resource
English
Bridge related damage quantification using unmanned aerial vehicle imagery
Wiley | 2016
|