Digital polygon data of water areas location in Kathmandu valley, Nepal. This dataset is created using Topographic sheet data at scale of 25,000/50,000, of 1995 acquired from National Geographic Information Infrastructure Project (NGIIP), Dept. of Survey, Nepal and for emergency response planning in case of earthquake disaster.

Bangladesh is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.

Nepal is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.

Nepal is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.

Bangladesh is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.

Nepal is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.

Bangladesh is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.

Bangladesh is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.

Nepal is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.