TH1.P6.4
ANALYSIS OF DEBRIS FLOW DISASTER DUE TO HEAVY RAIN BY CX-BAND MP RADAR DATA
Masahiro NISHIO, Kurume Institute of Technology, Japan
Session:
TH1.P6: RS for Natural Disaster Monitoring and Management: Floods Oral
Track:
Special Scientific Themes
Location:
Room P6
Presentation Time:
Thursday, 7 August, 08:45 - 09:00
Presentation
Discussion
Resources
No resources available.
Session TH1.P6
TH1.P6.4: THE POTENTIAL OF SMAP L4 SOIL MOISTURE PRODUCT IN IDENTIFYING FOREST FIRE RISKS
NA YANG, FENG XIANG, Ningbo University of Technology, China
TH1.P6.2: COMPARATIVE ANALYSIS OF OPEN-SOURCE SAR-BASED FLOOD DATASETS FOR ACCURATE FLOOD EXTENT DELINEATION USING DEEP LEARNING
Ira Karrel San Jose, Sesa Wiguna, Tohoku University, Japan; Marc Wieland, German Aerospace Center, Germany; Bruno Adriano, Erick Mas, Shunichi Koshimura, Tohoku University, Japan
TH1.P6.3: A FIRST EXTENSION OF THE ROBUST SATELLITE TECHNIQUE RST-FLOOD TO SENTINEL-2 DATA FOR THE MAPPING OF FLOODED AREAS: THE CASE OF THE EMILIA ROMAGNA (ITALY) 2023 EVENT
Valeria Satriano, Emanuele Ciancia, Nicola Pergola, National Research Council, Italy; Valerio Tramutoli, University of Basilicata, Italy
TH1.P6.5: ANALYSIS OF DEBRIS FLOW DISASTER DUE TO HEAVY RAIN BY CX-BAND MP RADAR DATA
Masahiro NISHIO, Kurume Institute of Technology, Japan
TH1.P6.4: MACHINE LEARNING MODEL-BASED LANDSLIDE SUSCEPTIBILITY ASSESSMENT FOR KEY SECTION OF SICHUAN-TIBET RAILWAY
Wenhuan Wu, Buyu Su, Beijing Research Institute of Uranium Geology, China; Haowei Mu, Nanjing University, China; Piyuan Yi, Ermao Suo, Pengfei Liu, Beijing Research Institute of Uranium Geology, China
Resources
No resources available.