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Understanding Geospatial Data in Development - Assignment Example

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The coastline of Bangladesh is endowed with a confluence of sediments in the low altitude alluvial and delta plains from the Ganges and Brahmaputra rivers. This area has a large population of over 140 million people and has recently been identified as the most risky place in the…
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Understanding Geospatial Data in Development
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A band ratio approach can be used by diving band 5 by band 2 in order to separate the water line from the clouds. The rate of change of the coastline can be calculated for transects greater than 16000 and generated at intervals of 50 m along the coastline and the main islands. This can be done using the End point Rate technique in the Digital Shoreline Analysis System in ArcGIS. Bangladesh is located at the mouth of Brahmaputra and Ganges which are the two largest rivers in the world flowing from the Himalayas.

A large part of the country is located in the Bengal basin which is an extensive geosyncline and has a large population of about 14.2 million people. Most people live in the low lying plains floodplains and delta plains which are usually very vulnerable to flooding during the monsoon season (Alesheikh et al, 2007). As a result, Bangladesh is normally considered as one of the most risky countries in the world due to exposure to the effects of climate change and sea level rises. The coastline of Bangladesh covers an area of about 47,201square kilometers and this region is inhabited by about 46 million people.

River Ganges drains about 1114000 square kilometers of catchment area and the River Brahmaputra drains 935000 square kilometers of catchment area and these supplies billions of tonnes of sediments every year in the Bengal basin. This rapid increase in sedimentation results into a very rapid accretion in the estuaries (Goodbred, 2003). In other sections of the coastline where rapid erosion is experienced due to strong tidal currents and strong waves action, rapid subsidence can be noted with a recession of about 3-4 km of the shoreline from its original position.

If we compare the Landsat images between 1973 and 2000, the recession rate of the shoreline and the time frame can be established (Benny, 2000). By comparing the satellite images

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