Mapping Flood Extent and Frequency from Sentinel-1 Imagery during the Extremely Warm Winter of 2020 in Boreal Floodplains and Forests
The current study presents a methodology for water mapping from Sentinel-1 (S1) data and a flood extent analysis of the three largest floodplains in Estonia. The automatic processing scheme of S1 data was set up for the mapping of open-water flooding (OWF) and flooding under vegetation (FUV). The ex...
Main Authors: | Liis Sipelgas, Age Aavaste, Rivo Uiboupin |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-12-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/13/23/4949 |
Similar Items
-
STURM-Flood: a curated dataset for deep learning-based flood extent mapping leveraging Sentinel-1 and Sentinel-2 imagery
by: Nicla Notarangelo, et al.
Published: (2025-02-01) -
Flood Mapping in Vegetated Areas Using an Unsupervised Clustering Approach on Sentinel-1 and -2 Imagery
by: Lisa Landuyt, et al.
Published: (2020-11-01) -
Floodsar: Automatic mapping of river flooding extent from multitemporal SAR imagery
by: Tomasz Berezowski, et al.
Published: (2024-05-01) -
An Adaptive Thresholding Approach toward Rapid Flood Coverage Extraction from Sentinel-1 SAR Imagery
by: Shujie Chen, et al.
Published: (2021-12-01) -
Application of Sentinel-1 SAR Imagery for Flood Detection and Monitoring, Case Study of Floods in Vrgorac Region during November and December 2020
by: Mladen Viher
Published: (2021-01-01)