Application of SAR remote sensing and crop modeling for operational rice crop monitoring in South and South East Asian Countries

Autor: Tri Deri Setiyono(1), Francesco Holecz(2), Nasreen I Khan(3), Massimo Barbieri(2), Aileen A Maunahan(4), Luca Gatti(2), Emma D Quicho(1), Sellaperumal Pazhanivelan(5), Manuel Campos-Taberner(6), Francesco Collivignarelli(2), Javier García Haro(6), Amornrat Intrman(7), Do Phuong(8), Mirco Boschetti(9), Prabhu Prasadini(10), Lorenzo Busetto(9), Vo Quang Minh(11), Vo Quoc Tuan(11)

Publikováno v: American Geophysical Union (AGU) Fall Meeting 2017, New Orleans, 11-15/12/2017
info:cnr-pdr/source/autori:Tri Deri Setiyono(1), Francesco Holecz(2), Nasreen I Khan(3), Massimo Barbieri(2), Aileen A Maunahan(4), Luca Gatti(2), Emma D Quicho(1), Sellaperumal Pazhanivelan(5), Manuel Campos-Taberner(6), Francesco Collivignarelli(2), Javier García Haro(6), Amornrat Intrman(7), Do Phuong(8), Mirco Boschetti(9), Prabhu Prasadini(10), Lorenzo Busetto(9), Vo Quang Minh(11) and Vo Quoc Tuan(11)/congresso_nome:American Geophysical Union (AGU) Fall Meeting 2017/congresso_luogo:New Orleans/congresso_data:11-15%2F12%2F2017/anno:2017/pagina_da:/pagina_a:/intervallo_pagine

This study uses multi-temporal SAR imagery, automated image processing, rule-based classification and field observations to classify rice in multiple locations in South and South Asian countries and assimilate the information into ORYZA Crop Growth S

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=cnr_________::8a0d443fe1088290e545201c6186f7d2
https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/237363