Monitoring Land Encroachment and Land Use & Land Cover (LULC) Change in The Pachhua Dun, Dehradun District Using Landsat Images 1989 and 2020

Abstract

Remote sensing and G.I.S help acquire information on changing land use and land cover (LULC), and it plays a pivotal role in measuring and monitoring such local and global changes. The present analysis has been executed on Landsat 5 TM, 1989 and Landsat 8 OLI/TIRS, 2020 images of Pachhua Dun, including Dehradun & Mussoorie urban agglomeration. The present study aims to detect the land encroachment or area of change; rate of change and monitoring spatio-temporal variation in LULC change between 1989-2020 using change detection technique, supervised maximum likelihood classification, and Overall accuracy & Kappa Coefficient (K) was applied as an accuracy assessment tool. The results derived from the change detection analysis exhibits that the highest growth rate was recorded in built-up areas +247.75% (110 km2) and revealed the annual rate of change of 3.55 km2. or 7.99%, the highest among all LULC class during the overall study period of 31 years. The result also found that among all LULC class, the most significant LULC conversion took place from agricultural land to built-up areas followed by open/scrubland and vegetation/forest cover; approximately 69.9km2 of the area under agricultural land was found to be converted into built-up areas. At the same time, 38.9 km2 area of vegetation/forest cover and 36.3 km2 of the area of open/scrubland have converted into agricultural land. Rising anthropogenic influence and unsustainable land-use practices in the study area have led to a large-scale human encroachment and rapid transformation of the natural landscape into the cultural landscape. This analysis provides the essential long-term Geospatial information related to LULC change for making optimum decision-making process and sustainable land-use planning in the Pachhua Dun-Dehradun District, Uttarakhand, India.

Keywords

• lulc
• change detection
• supervised classification
• accuracy assessment
• maximum likelihood classification.