TU3.R15.6

GENERATING HOURLY 70-M LAND SURFACE TEMPERATURE FROM GOES-R OBSERVATIONS: A COMPARISON OF STATISTICAL DOWNSCALING AND DEEP LEARNING METHODS

Yue Chang, Yinxia Cao, Qihao Weng, The Hong Kong Polytechnic University, Hong Kong SAR of China

Session:
TU3.R15: Sustainable Development Goals through Image Analysis and Data Fusion of Earth Observation Data Oral

Track:
Community-Contributed Sessions

Location:
Mercury Hall

Presentation Time:
Tue, 9 Jul, 15:50 - 16:04

Session Co-Chairs:
Ujjwal Verma, and Silvia Liberata Ullo, University of Sannio
Presentation
Discussion
Resources
No resources available.
Session TU3.R15
TU3.R15.1: A DATA-DRIVEN APPROACH FOR ESTIMATING REGIONAL FOOD FLOWS FUSING EARTH OBSERVATION AND GEOSPATIAL DATA
Claudia Paris, Manuka Khan, Marco Cattaneo, Yue Dou, Department of Natural Resources, ITC, Netherlands
TU3.R15.2: HYBRID GSA-CNN METHOD FOR HYPERSPECTRAL PANSHARPENING
Giuseppe Guarino, Matteo Ciotola, Giovanni Poggi, University of Naples Federico II, Italy; Gemine Vivone, National Research Council, Italy; Giuseppe Scarpa, University Parthenope of Naples, Italy
TU3.R15.3: MineNet-CD: Global Mining Change Detection Dataset
Weikang Yu, Samiran Das, Aldino Rizaldy, Helmholtz-Zentrum Dresden-Rossendorf, Germany; Xiaokang Zhang, Wuhan University of Science and Technology, China; Richard Gloaguen, Pedram Ghamisi, Helmholtz-Zentrum Dresden-Rossendorf, Germany
TU3.R15.4: LEARNING BUILDING ENERGY EFFICIENCY WITH SEMANTIC ATTRIBUTES
Zhaiyu Chen, Ziqi Gu, Yilei Shi, Xiao Xiang Zhu, Technical University of Munich, Germany
TU3.R15.5: IMPROVED DETECTION OF SMALL-SCALE FOREST FIRES IN THE MEDITERRANEAN REGION FROM SENTINEL-1 AND SENTINEL-2 TIME SERIES
Chiara Aquino, Maria Vincenza Chiriacò, Manuela Balzarolo, CMCC Foundation - Euro-Mediterranean Center on Climate Change, Italy
TU3.R15.6: GENERATING HOURLY 70-M LAND SURFACE TEMPERATURE FROM GOES-R OBSERVATIONS: A COMPARISON OF STATISTICAL DOWNSCALING AND DEEP LEARNING METHODS
Yue Chang, Yinxia Cao, Qihao Weng, The Hong Kong Polytechnic University, Hong Kong SAR of China
TU3.R15.7: USING REMOTE SENSING DATA IN THE CLOUD TO MONITOR CLIMATE CHANGE IN SENEGAL REGIONS BASED ON SEASONAL VARIABLES FROM 2000 TO 2020. AN OPPORTUNITY TO SUSTAINABLE POLICIES.
Cesar Alvarez, Salesian Polytechnic University, Ecuador; Ajit Govind, The International Centre for Agricultural Research in the Dry Areas, Egypt
Resources
No resources available.