Geological Information System (GIS) is a technique which can make geotechnical investigation easy for engineering purpose. It helps the engineer to analyze the ground data before physical inspection of the site. The area of research is the Nagpur district of Maharashtra, India. The topographic sheet for Nagpur is 55K/16 and 55O/4 of 2010. The Major purpose of this research was to determine the bearing capacity map, Contour map, and total land cover/land use map for a different purpose. From the above map, it will be easier for engineers to decide the type of Foundation and the trend of development across the city. Earlier, there was no method to store bore log and soil data to the exact location of the borehole, but today with the help of the Geospatial technique, researchers can assign soil data with every borehole. Nowadays, urbanization is speedily taking place due to which proper utilization is necessary for land according to its strength and properties. In this research, the author wants to collect different satellite imageries of Nagpur city and bore logs comprising of geotechnical data. The predicted outcome should show the contour map, elevation map, changes in land use pattern, and bearing capacity across the city. These help the researcher and engineers who are working in the same area for future site selection.
Urban regions have grown and developed more quickly around the world. The amount of productive land is significantly reduced by the expansion of the urban perimeter. To ensure sustainable urban growth, research in urban sprawl analysis and land use land cover (LULC) change assessment is crucial. Bengaluru is one of the fastest growing metropolitan cities across the world, and its growth has a significant impact on neighbouring regions. Hence an attempt is made to evaluate the influence of urban sprawl on LULC in the Bengaluru rural district, which surrounds the Bengaluru urban region. In this study, temporal changes in LULC over two decades are assessed by employing remote sensed data and GIS tools. The study area is categorized into five LULC classes: settlement, waterbody, vegetation, agriculture, and barren land. Landsat images of two different timescales are classified using the supervised image classification technique in ERDAS software. The maximum likelihood technique is used for classifying the image, and the accuracy of the classified image is evaluated by accuracy assessment. The study revealed that urban sprawl significantly influenced the LULC classes study area.
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