Vol. 11, Special Issue 9 (2022)

Author(s):
Rutuja S Gadhave, Shubham A Gade and Sonal R Kalbande

Abstract:
Geospatial big data is currently received overwhelming attention and is currently the hotspot platform to cater to big data processing for Remote Sensing and GIS. Mapping land use and land cover (LULC) is important for efficiently analysing, monitoring, conserving, and planning resources. Remote sensing data is extensively utilized to research terrestrial features in less time, at a lower cost, and with greater accuracy, and GIS provides an appropriate platform for data analysis. The objective is to evaluate the feasibility of RS and GIS as a free cloud-based platform by performing a classification of Rahuri tehsil from Landsat composites of three different years (2011, 2015, and 2019). The best-categorized findings were then imported and further processed using commercial software (SAGA GIS) to quantify the changes over time. The eight-year period shows massive changes in various parameters. The cropland decreased in all three years. The cropland contributed about 48731.31 ha, i.e., 45.906% of the total area in 2011; this was reduced to 41880.96 ha in 2015, which was further reduced to 37490.13 ha, i.e., 39.45% in 2019, almost by 10%. The total increase in barren land is 5.02% from 2011 to 2015 and 5.12% from 2015 to 2019. In 8 years, the overall increase in barren land is 10.14%, with the decline in agriculture and water bodies being the primary reasons for this increase. The fallow land shows little change, with few differences. The build-up is considered an increasing parameter in all three years; it increased from 1.53% to 2.509% in eight years. Water bodies decreased in all three years, from 4689.54 ha in 2011 to 3738.69 ha in 2015 and further to 3150.9 ha in 2019, i.e., almost by 1.45% in eight years. On the other hand, GIS has performed quite effectively and quickly in terms of time and processing complexity of various datasets with minimal human engagement and intervention.