Flood inundation mapping-Kerala 2018; Harnessing the power of SAR, automatic threshold detection method and Google Earth Engine
Flood inundation maps provide valuable information towards flood risk preparedness,
management, communication, response, and mitigation at the time of disaster, and can be …
management, communication, response, and mitigation at the time of disaster, and can be …
A Near-Real-Time Flood Detection Method Based on Deep Learning and SAR Images
Owning to the nature of flood events, near-real-time flood detection and mapping is essential
for disaster prevention, relief, and mitigation. In recent years, the rapid advancement of deep …
for disaster prevention, relief, and mitigation. In recent years, the rapid advancement of deep …
Evaluation of floods and landslides triggered by a meteorological catastrophe (Ordu, Turkey, August 2018) using optical and radar data
This study explores the potential of photogrammetric datasets and remote sensing methods
for the assessment of a meteorological catastrophe that occurred in Ordu, Turkey in August …
for the assessment of a meteorological catastrophe that occurred in Ordu, Turkey in August …
Flood inundation mapping and monitoring using SAR data and its impact on Ramganga River in Ganga basin
Remote sensing–based flood inundation mapping and monitoring is very crucial input
before, during, and after floods. Ganga–Ramganga doab is one of the prolonged flood …
before, during, and after floods. Ganga–Ramganga doab is one of the prolonged flood …
Fast and automatic data-driven thresholding for inundation mapping with Sentinel-2 data
Satellite data offer the opportunity for monitoring the temporal flooding dynamics of seasonal
wetlands, a parameter that is essential for the ecosystem services these areas provide. This …
wetlands, a parameter that is essential for the ecosystem services these areas provide. This …
[HTML][HTML] Cloud-based large-scale data retrieval, mapping, and analysis for land monitoring applications with google earth engine (GEE)
Cloud-based computing systems are linked with analytical tools for large-scale flood
monitoring to solve these problems. Researchers want an exceptionally efficient and …
monitoring to solve these problems. Researchers want an exceptionally efficient and …
An adaptive thresholding approach toward rapid flood coverage extraction from Sentinel-1 SAR imagery
S Chen, W Huang, Y Chen, M Feng - Remote Sensing, 2021 - mdpi.com
Flood disasters have a huge effect on human life, the economy, and the ecosystem. Quickly
extracting the spatial extent of flooding is necessary for disaster analysis and rescue …
extracting the spatial extent of flooding is necessary for disaster analysis and rescue …
Flood extent mapping from time-series SAR images based on texture analysis and data fusion
M Ouled Sghaier, I Hammami, S Foucher, R Lepage - Remote Sensing, 2018 - mdpi.com
Nowadays, satellite images are considered as one of the most relevant sources of
information in the context of major disasters management. Their availability in extreme …
information in the context of major disasters management. Their availability in extreme …
Flood mapping using multi-source remotely sensed data and logistic regression in the heterogeneous mountainous regions in North Korea
J Lim, K Lee - Remote Sensing, 2018 - mdpi.com
Flooding is extremely dangerous when a river overflows to inundate an urban area. From
1995 to 2016, North Korea (NK) experienced extensive damage to life and property almost …
1995 to 2016, North Korea (NK) experienced extensive damage to life and property almost …
Fusion of Sentinel-1 data with Sentinel-2 products to overcome non-favourable atmospheric conditions for the delineation of inundation maps
I Manakos, GA Kordelas, K Marini - European Journal of Remote …, 2020 - Taylor & Francis
ABSTRACT 729Sentinel-1 data are an alternative for monitoring flooded inland surfaces
during cloudy periods. Supervised classification approaches with a single-trained model for …
during cloudy periods. Supervised classification approaches with a single-trained model for …