Synergetic use of Multi-sensor Time Series for the Derivation of Rice Seasonal Information

Autor: Holecz, Francesco (1), Barbieri, Massimo (1), Gatti, Luca (1), Collivignarelli, Francesco (1), Boschetti, Mirco (2), Stroppiana, Daniela (2), Busseto, Lorenzo (2), Fontanelli, Giacomo (2), Crema, Alberto (2), Nutini, Francesco (2), Confalonieri, Roberto (3), García Haro, Javier (4), Grau, Gonçal (4), Campos Taberner, Manuel (4), Karydas, Christos (5), Katsantonis, Dimitrios (6), Dramalis, Christos (6), Kalaitzidis, Argyris (6)

Publikováno v: Living Planet Symposium 2016, Prague, Czech Republic, 9/5/2016, 13/5/2016
info:cnr-pdr/source/autori:Holecz, Francesco (1); Barbieri, Massimo (1); Gatti, Luca (1); Collivignarelli, Francesco (1); Boschetti, Mirco (2); Stroppiana, Daniela (2); Busseto, Lorenzo (2); Fontanelli, Giacomo (2); Crema, Alberto (2); Nutini, Francesco (2); Confalonieri, Roberto (3); García Haro, Javier (4); Grau, Gonçal (4); Campos Taberner, Manuel (4); Karydas, Christos (5); Katsantonis, Dimitrios (6); Dramalis, Christos (6); Kalaitzidis, Argyris (6)/congresso_nome:Living Planet Symposium 2016/congresso_luogo:Prague, Czech Republic/congresso_data:9%2F5%2F2016, 13%2F5%2F2016/anno:2016/pagina_da:/pagina_a:/intervallo_pagine

In past works, it has been demonstrated over various agro-ecological zones, crop establishment methods and water management practices in South-East Asia that spaceborne Synthetic Aperture Radar (SAR) time-series combined with yield crop modeling offe

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=cnr_________::553fd7422bdee2e7b4cdca8b6b4b1f52
http://www.cnr.it/prodotto/i/364020