Average data for Whole Indus from year 1971 to 1980 for the month of December in ASCII format. It is an Aphrodite data with 0.25 resolution in x and y direction. The APHRODITE project develops state-of-the-art daily precipitation datasets with high-resolution grids. The datasets are created primarily with data obtained from a rain-gauge-observation network.

Average data for Whole Indus from year 1981 to 1990 for the month of May in ASCII format. It is an Aphrodite data with 0.25 resolution in x and y direction. The APHRODITE project develops state-of-the-art daily precipitation datasets with high-resolution grids. The datasets are created primarily with data obtained from a rain-gauge-observation network.

River(polygon) dataset of Kritipur Municipality for the Geo-visualization on emergency response in case of earthquake disaster.

Average data for Whole Indus from year 2001 to 2007 for the month of April in ASCII format. It is an Aphrodite data with 0.25 resolution in x and y direction. he APHRODITE project develops state-of-the-art daily precipitation datasets with high-resolution grids. The datasets are created primarily with data obtained from a rain-gauge-observation network.

Digital point dataset of location of Airports of Hindu Kush Himalayan (HKH) Region. This dataset is basic vector layer derived from ESRI Map & Data in 2001.

Digital grid dataset of monthly mean temperature (July) for the period of 1950-2000 of Hindu Kush Himalayan (HKH) Region. The dataset is derived from WorldClim (http://www.worldclim.org/), and major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet. Monthly mean temperature data set consists of 12 raster files, one for each month, showing mean values derived from monthly temperature readings. The data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid.

Average data for Whole Indus from year 1981 to 1990 for the month of July in ASCII format. It is an Aphrodite data with 0.25 resolution in x and y direction. The APHRODITE project develops state-of-the-art daily precipitation datasets with high-resolution grids. The datasets are created primarily with data obtained from a rain-gauge-observation network.

Digital grid data of Mean Precipitation of September for Hindu Kush Himalayan (HKH) Region. This dataset is acquired from USGS.

Average data for Whole Indus from year 1981 to 1990 for the month of January in ASCII format. It is an Aphrodite data with 0.25 resolution in x and y direction. The APHRODITE project develops state-of-the-art daily precipitation datasets with high-resolution grids. The datasets are created primarily with data obtained from a rain-gauge-observation network.

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.