MO2.R13.4

SENTINEL-1 AND TANDEM-X INSAR COHERENCE FOR MONITORING FORESTS USING DEEP LEARNING

Paola Rizzoli, Ricardo dal Molin, Daniel Carcereri, José-Luis Bueso-Bello, German Aerospace Center DLR, Germany
Session:
MO2.R13: How Can Multi-Temporal InSAR Coherence Benefit Your Application? Reports from Recent Findings in Various Applications Oral
Track:
Community-Contributed Sessions
Location:
Room 105
Presentation Time:
Mon, 17 Jul, 16:21 - 16:33 Pacific Time (UTC -7)
Session Chair:
Alexander Jacob, EURAC Research, Italy
Session Manager:
Ayoti Banerjee
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Session MO2.R13
MO2.R13.1: SAR2CUBE - AN OPEN FRAMEWORK FOR AN EFFICIENT SETUP OF SAR IMAGERY IN ANALYSIS READY DATA CUBES
Michele Claus, Alexander Jacob, EURAC Research, Italy; Giuseppe Centolanza, DARES Technology, Spain; Juan M. Lopez-Sanchez, University of Alicante, Spain
MO2.R13.2: C- AND X-BAND REPEAT-PASS COHERENCE FOR CROP-TYPE MAPPING AND MONITORING
Arturo Villarroya-Carpio, Mario Busquier, Juan Lopez-Sanchez, University of Alicante, Spain; Marcus Engdahl, European Space Research Institute (ESA), Italy
MO2.R13.3: SENTINEL-1 INSAR COHERENCE AS AN INDICATOR OF MONITORING FARMING ACTIVITIES
Manuel Huber, Vineet Kumar, Susan Steele-Dunne, TU Delft, Netherlands; Björn Rommen, European Space Agency, Netherlands
MO2.R13.4: SENTINEL-1 AND TANDEM-X INSAR COHERENCE FOR MONITORING FORESTS USING DEEP LEARNING
Paola Rizzoli, Ricardo dal Molin, Daniel Carcereri, José-Luis Bueso-Bello, German Aerospace Center DLR, Germany
MO2.R13.5: L-BAND VS C-BAND INTERFEROMETRIC TEMPORAL COHERENCE FOR FOREST PARAMETERS MAPPING
Chiara Telli, Sapienza University, Italy; Marco Lavalle, NASA Jet Propulsion Laboratory, California Institute of Technology, United States; Nazzareno Pierdicca, Sapienza University, Italy
Resources
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