2020 IEEE International Geoscience and Remote Sensing Symposium

September 26 - October 2, 2020 • Virtual Symposium

2020 IEEE International Geoscience and Remote Sensing Symposium

September 26 - October 2, 2020 • Virtual Symposium

WE2.R11: Remote Sensing for Crop Monitoring, Mapping and Classification III

Wed, 30 Sep, 14:30 - 16:30 (UTC)
Wed, 30 Sep, 22:30 - 00:30 China Standard Time (UTC +8)
Wed, 30 Sep, 16:30 - 18:30 Central Europe Summer Time (UTC +2)
Wed, 30 Sep, 07:30 - 09:30 Pacific Daylight Time (UTC -7)
Session Co-Chairs: Pang-Wei Liu, NASA Goddard Space Flight Center and Dipankar Mandal, Indian Institute of Technology Bombay
Session Managers: Cecilia Verónica Campos Cerón and Genc Hoxha
Track: Land Applications
14:30-14:40 (UTC)
22:30-22:40 (UTC +8)
16:30-16:40 (UTC +2)
07:30-07:40 (UTC -7)

WE2.R11.1: MAPPING RICE PLANTING AREA USING MULTI-TEMPORAL QUAD-POL RADARSAT-2 DATASETS AND RANDOM FOREST ALGORITHM
Ze He, Shihua Li, Pengfei Zhai, Yuchuan Deng, University of Electronic Science and Technology of China, China
14:40-14:50 (UTC)
22:40-22:50 (UTC +8)
16:40-16:50 (UTC +2)
07:40-07:50 (UTC -7)

WE2.R11.2: SCOPE, EXTENT, AND CHALLENGES OF AN AUTOMATED GLOBAL CROP CLASSIFICATION MODEL
Sukanya Randhawa, Manikandan Padmanaban, UmaMaheswari Devi, IBM Research India, India
14:50-15:00 (UTC)
22:50-23:00 (UTC +8)
16:50-17:00 (UTC +2)
07:50-08:00 (UTC -7)

WE2.R11.3: ASSESSMENT OF CLOUD COVER IN SENTINEL-2 DATA USING RANDOM FOREST CLASSIFIER
Petteri Nevavuori, Mtech Digital Solutions Oy, Finland; Tarmo Lipping, Nathaniel Narra, Petri Linna, Tampere University, Finland
15:00-15:10 (UTC)
23:00-23:10 (UTC +8)
17:00-17:10 (UTC +2)
08:00-08:10 (UTC -7)

WE2.R11.4: USE OF REMOTE SENSING SATELLITE IMAGES IN RICE AREA MONITORING SYSTEM OF BANGLADESH
Kazi A Kalpoma, Rumman Ali, Ashiqur Rahman, Ashraful Islam, Ahsanullah University of Science and Technology, Bangladesh
15:10-15:20 (UTC)
23:10-23:20 (UTC +8)
17:10-17:20 (UTC +2)
08:10-08:20 (UTC -7)

WE2.R11.5: AUTUMN CROP MAPPING BASED ON DEEP LEARNING METHOD DRIVEN BY HISTORICAL LABELLED DATASET
Shuang Zhu, Beijing Polytechnic College, China; Jinshui Zhang, Beijing Normal University, China; Guanyuan Shuai, Michigan State University, United States; Hongli Liu, Feng Zhang, Beijing Normal University, China; Zheng Dong, Beijing Vocational Transportation College, China
15:20-15:30 (UTC)
23:20-23:30 (UTC +8)
17:20-17:30 (UTC +2)
08:20-08:30 (UTC -7)

WE2.R11.6: DEVELOP LARGE-AREA AUTUMN CROP TYPE PRODUCT USING A DEEP LEARNING STRATEGY
Qing Xu, Jinshui Zhang, Feng Zhang, Beijing Normal University, China; Shuang Zhu, Beijing Polytechnic College, China
15:30-15:40 (UTC)
23:30-23:40 (UTC +8)
17:30-17:40 (UTC +2)
08:30-08:40 (UTC -7)

WE2.R11.7: SOIL NUTRIENTS PREDICTION USING REMOTE SENSING DATA IN WESTERN INDIA: AN EVALUATION OF MACHINE LEARNING MODELS
Gunkirat Kaur, Indian Institute of Information Technology Delhi, India; Kamal Das, Jagabondhu Hazra, IBM Research India, India
15:40-15:50 (UTC)
23:40-23:50 (UTC +8)
17:40-17:50 (UTC +2)
08:40-08:50 (UTC -7)

WE2.R11.8: USE NIGHT TIME LIGHT REMOTE SENSING TO DISCOVER DRAGON FRUIT PLANTATIONS IN VIETNAM
Ruirui Wang, Beijing Forestry University, China; Wei Shi, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China; Huiping Jiang, Aerospace Information Research Institute, Chinese Academy of Sciences, China
15:50-16:00 (UTC)
23:50-00:00 (UTC +8)
17:50-18:00 (UTC +2)
08:50-09:00 (UTC -7)

WE2.R11.9: YIELD AND COMMERCIAL CANE SUGAR ESTIMATION FOR SUGARCANE IN THAILAND - A CASE STUDY
Ranjini B Guruprasad, Kalyan Dasgupta, IBM Research India, India; Klanarong Sriroth, Panyawat Chattanrassamee, Mitr Phol, Thailand; Noppadon Khiripet, National Science and Technology Development Agency (NSTDA), Thailand
16:00-16:10 (UTC)
00:00-00:10 (UTC +8)
18:00-18:10 (UTC +2)
09:00-09:10 (UTC -7)

WE2.R11.10: Joint estimation of grassland leaf area index and leaf chlorophyll content from unmanned aerial vehicle hyperspectral data
Xiaohua Zhu, Chuanrong Li, Lingli Tang, Qian Yang, Yongguang Zhao, Aerospace Information Research Institute, Chinese Academy of Sciences, China