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THP2.PQ.1: COMPARISON OF TWO MODELING APPROACHES TO SIMULATE RICE PRODUCTION IN THE CAMARGUE REGION USING SENTINEL 2 DATA
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Dominique Courault; UMR 1114 EMMAH INRA, UAPV University of Avignon |
Valérie Demarez; Centre d'Etude Spatial de la BIOsphère (CESBIO) / University of Paul Sabatier |
Laure Hossard; INRA,UMR 951 Innovation |
Fabrice Flamain; INRA, université d'Avignon et des pays du Vaucluse |
Emile Ndikumana; IRSTEA, University of Montpellier |
Din Ho-Tong-Minh; IRSTEA, University of Montpellier |
Nicolas Baghdadi; IRSTEA, University of Montpellier |
Françoise Ruget; INRA, université d'Avignon et des pays du Vaucluse |
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THP2.PQ.2: COMPARISON RADAR VEGETATION INDEX (RVI) WITH CONVENTIONAL METHODS FOR PADDY RICE FIELD, LOTUS POND AND SOYBEAN
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Yasuharu Yamada; National Agriculture and Food Research Organization |
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THP2.PQ.3: EXPLOITING THE TEXTURAL INFORMATION OF UAV MULTISPECTRAL IMAGERY TO MONITOR NITROGEN STATUS IN RICE
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Hengbiao Zheng; Nanjing Agricultural University |
Meng Zhou; Nanjing Agricultural University |
Yan Zhu; Nanjing Agricultural University |
Tao Cheng; Nanjing Agricultural University |
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THP2.PQ.4: MACHINE LEARNING METHODOLOGIES FOR PADDY YIELD ESTIMATION IN INDIA: A CASE STUDY
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Ranjini B Guruprasad; IBM |
Kumar Saurav; IBM |
Sukanya Randhawa; IBM |
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THP2.PQ.5: A HEURISTIC EXPLORATION OF BRIDGING PHENOLOGY-BASED AND MACHINE LEARNING-BASED METHODS FOR PADDY RICE MAPPING WITH SENTINEL-2 IMAGES
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Chengkang Zhang; Wuhan University |
Hongyan Zhang; Wuhan University |
Yi Liu; NTNU-Norwegian University of Science and Technology |
Liangpei Zhang; Wuhan University |
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THP2.PQ.6: MULTI OUTPUT REGRESSIONS FOR ESTIMATING CANOLA BIOPHYSICAL PARAMETERS FROM POLSAR DATA
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Z.Meltem Sahin; Istanbul Technical University |
Esra Erten; Istanbul Technical University |
Gülsen Kaya; Istanbul Technical University |
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THP2.PQ.7: DRONE-BASED OPTICAL, THERMAL, AND 3D SENSING FOR DIAGNOSTIC INFORMATION IN SMART FARMING – SYSTEMS AND ALGORITHMS –
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Yoshio Inoue; University of Tokyo |
Masaki Yokoyama; Institute for Agro-Environmental Sciences, NARO (NIAES) |
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THP2.PQ.8: LINKING CLOUD COVER PATTERNS TO LAND SURFACE TEMPERATURE CHANGE IN LANDSAT 8 IMAGES
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Shifeng Li; Chinese Academy of Agricultural Sciences |
Zhihao Qin; Chinese Academy of Agricultural Sciences |
Wenhui Du; Chinese Academy of Agricultural Sciences |
Jinlong Fan; National Satellite Meteorological Center, China Meteorological Administration |
Shuhe Zhao; Nanjing University |
Offer Rozenstein; Agricultural Research Organization, Volcani Center |
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THP2.PQ.9: TEMPORAL DETECTION OF PESTICIDE RESIDUES IN TEA LEAVES USING HYPERSPECTRAL SENSING
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Jayantrao Mohite; Tata Consultancy Services |
Suryakant Sawant; Tata Consultancy Services |
Kailyanjeet Borah; Amalgamated Plantations Private Limited |
Srinivasu Pappula; Tata Consultancy Services |
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THP2.PQ.10: STABILITY ESTIMATION OF A SAMPLE SIZE FOR INTERANNUAL MONITORING USING MICRO SATELLITES
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Shinya Odagawa; Remote Sensing Technology Center of Japan |
Daisuke Seguchi; Remote Sensing Technology Center of Japan |
Toshio Okumura; Remote Sensing Technology Center of Japan |
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THP2.PQ.11: MULTISPECTRAL AND MODIFIED CAMERAS COMPARISON IN AGRICULTURAL MAPPING WITH UNMANNED AERIAL VEHICLE (UAV)
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Rodrigo Raupp Bosque; Universidade do Vale do Rio dos Sinos (UNISINOS) |
Leonardo Campos Inocencio; Universidade do Vale do Rio dos Sinos (UNISINOS) |
Maurício Roberto Veronez; Universidade do Vale do Rio dos Sinos (UNISINOS) |
Luiz Gonzaga da Silveira Jr.; Universidade do Vale do Rio dos Sinos (UNISINOS) |
Fabiane Bordin; Universidade do Vale do Rio dos Sinos (UNISINOS) |
Ademir Marques Jr.; Universidade do Vale do Rio dos Sinos (UNISINOS) |
Rafael Kenji Horota; Universidade do Vale do Rio dos Sinos (UNISINOS) |