IGARSS 2026 || Washington, D.C. || 9

THP2.PG: Global Food-and-Water Security-support Analysis Datasets at 10-30m resolution using Remote Sensing Embedded Data and AI models on the Cloud

Thursday, 13 August, 15:00 - 16:15

Location: Poster Area G

Session Type: Poster

Track: Community Contributed Themes

Poster Area G

THP2.PG.2: NATIONAL-SCALE WITHIN-SEASON CROP IDENTIFICATION FROM SENTINEL-2 IMAGERY

Haijun Li, Xiao-Peng Song, Bernard Adusei, University of Maryland, College Park, United States; Peter Potapov, World Resources Institute, United States; Matthew Hansen, University of Maryland, College Park, United States; Feng Gao, USDA-ARS Hydrology and Remote Sensing Laboratory, United States

Poster Area G

THP2.PG.3: A DUAL-STREAM FRAMEWORK FOR AGRICULTURAL ANALYSIS USING SENTINEL-2 AND MODIS DATA

Amit Kumar Singh, Sapienza University of Rome, Italy, Italy

Poster Area G

THP2.PG.4: QUANTIFYING THE CONTRIBUTION OF WELL-FACILITATED FARMLAND CONSTRUCTION TO CROP PRODUCTIVITY AND ITS DRIVING FACTORS USING REMOTE SENSING AND MACHINE LEARNING MODELS

Wenjiao Shi, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China; Ziwei Xu, Beijing Normal University, China

Poster Area G

THP2.PG.6: VISUAL TEMPORAL REASONING FOR CROP IDENTIFICATION IN REMOTELY SENSED DATA

Ioan Cristian Leancu, Anglia Ruskin University, United Kingdom; Corneliu-Nicolae Florea, University Politehnica Bucharest, Romania; Mihai Ivanovici, AI4AGRI Center, Transilvania University, Romania

Poster Area G

THP2.PG.10: Dual-Branch Encoder Network with Temporal Difference for Rice Mapping Using SAR Time Series

Juan Bai, WuHan University, China; Lingli Zhao, Wuhan University, China; Yonglei Chang, East China University of Technology, China; Lei Shi, Jie Yang, WuHan University, China

Poster Area G

THP2.PG.11: Continental Mapping of Mesic Ecosystem Using Machine Learning: Effects of Training Dataset Size and Spatial Autocorrelation

JUAN CAMILO ROJAS LUCERO, Boise State University, United States