A comparison between support vector machine and water Cloud model for estimating crop leaf area index

The water cloud model (WCM) can be inverted to estimate leaf area index (LAI) using the intensity of backscatter from synthetic aperture radar (SAR) sensors. Published studies have demonstrated that the WCM can accurately estimate LAI if the model is effectively calibrated. However, calibration of t...

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Detalles Bibliográficos

Autores principales:	Hosseini, Mehdi, McNairn, Heather, Mitchell, Scott, Robertson, Laura Dingle, Davidson, Andrew, Ahmadian, Nima, Bhattacharya, Avik, Borg, Erik, Conrad, Christopher, Dabrowska Zielinska, Katarzyna, De Abelleyra, Diego, Gurdak, Radoslaw, Kumar, Vineet, Kussul, Nataliia, Mandal, Dipankar, Rao, Y.S., Saliendra, Nicanor, Shelestov, Andrii, Spengler, Daniel, Veron, Santiago Ramón, Homayouni, Saeid, Becker Reshef, Inbal
Formato:	info:ar-repo/semantics/artículo
Lenguaje:	Inglés
Publicado:	MDPI 2022
Materias:	Leaf Area Index Remote Sensing Índice de Superficie Foliar Teledetección RADARSAT-2 Sentinel-1 Modelo de Nube de Agua Aprendizaje Automático Water Cloud Model Machine Learning
Acceso en línea:	http://hdl.handle.net/20.500.12123/13284 https://www.mdpi.com/2072-4292/13/7/1348 https://doi.org/10.3390/rs13071348