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.

Digital point dataset of Mobile Tower in Central Karakoram National Park(CKNP) area, Pakistan. This dataset is compiled through GPS based field survey conducted in year 2008.

Digital point dataset of Gemstone Mine locations of Central Karakoram National Park(CKNP) area, Pakistan. This dataset is compiled through GPS based field survey conducted in year 2008.

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.

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.

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.

Average data for Whole Indus from year 1981 to 1990 for the month of June 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.