Assessment of Land Use Land Cover Change using Multi-temporal Dataand Geospatial Techniques: A Case Study of Shimla City
DOI:
https://doi.org/10.48165/prakriti.2026.3.02.03Keywords:
Landuse/Landcover (LULC), Google Earth, GIS, remote sensing, supervised classification, Shimla CityAbstract
Shimla City has experienced a wide range of changes in land use and land cover (LULC). This study used Remote Sensing (RS) to detect and quantify LULC changes that occurred in the city throughout a thirty study period, using Landsat and Google earth imageries (960 images) acquired between 1991 and 2021. This study aims to investigate the spatial pattern of land usage in Shimla by ward. A supervised classification method using an Artificial Neural Network (ANN) was used to classify and map LULC types. The compound annual growth rate (CAGR) and instability index used to quantify and estimate the changes in time series data while dealing with land use data. Using the classified images, a post classification comparison approach is use to detect LULC changes between 1991 and 2021. The study revealed that huge population growth has eventually resulted in unprecedented land use change in the built-up category in the city, which has increased from 5.92 percent in 1991 to 13.96 percent in 2021, thus showing a change of 8.04 percent and registering a growth rate of 3.64 percent (2.46 km2). Between 1991 and 2021, the area under forest decreased marginally from -6.96 percent to 4.66 percent, while other fallow land use decreased from 5.86 percent to 4.66 percent. The agricultural land also underwent a decline, from 1.43 percent in 1991 to 1.25 percent in 2021. The findings of this study provide the extensive explanation and spatio-temporal differentiation maps and tables created with geospatial data will undoubtedly aid in understanding the city growth dynamics process and changing form of land-use land cover and aid the decision-making process of local planners, stakeholders, and academicians.
References
Balasubramanian, A. (2017). India: Topography and slope. Centre for Advanced Studies in Earth Science, University of Mysore.
Basawaraja, R., et al. (2011). Analysis of the impact of urban sprawl in altering the land-use and land-cover pattern of Raichur City, India, using geospatial technologies. Journal of Geography and Regional Planning, 4(8), 455–462.
Kafi, K. M., et al. (2014). An analysis of LULC change detection using remotely sensed data: A case study of Bauchi City. Earth and Environmental Science, 20, 1–10.
Malarvizhi, K., et al. (2016). Use of high-resolution Google Earth satellite imagery in land-use map preparation for urban-related applications. Procedia Technology, 24, 1835–1842.
Moss, M. L., & Neill, H. O. (2012). Urban mobility in the 21st century. NYU Rudin Center for Transportation Policy.
Nassar, A. K., et al. (2014). Developing the desert: The pace and process of urban growth in Dubai. Computers, Environment and Urban Systems, 45, 50–62.
Poudel, K. P. (1996). Geographic information system-based hill-slope instability analysis for land-use planning perspective: The case of Upper Madi Watershed, Kaski, Nepal. Tribhuvan University Journal, 19(2), 25–42.
Shandas, V., et al. (2017). Rapid urban growth and land use patterns in Doha, Qatar: Opportunities for sustainability. European Journal of Sustainable Development, 11, 2542–4742.
