Journal of Agricultural Engineering
  • Year: 2025
  • Volume: 62
  • Issue: 4

Spatiotemporal Changes in Land Use/Land Cover: A Case Study of Hamirpur Block, Himachal Pradesh

  • Author:
  • Rajneesh Jaswal1, R. K. Aggarwal1,*, Pratima Vaidya1, Deepak Agnihotri2, Ghanshyam Agrawal3
  • Total Page Count: 9
  • Page Number: 1006 to 1014

1Department of Environmental Science, Dr. Y. S. Parmar University of Horticulture & Forestry, Nauni, Solan, Himachal Pradesh, India

2Computing and Informatics Centre, Dr. Y.S. Parmar University of Horticulture & Forestry, Nauni, Solan, Himachal Pradesh, India

3Department of Soil Science and Water Management, Dr. Y.S. Parmar University of Horticulture & Forestry, Nauni, Solan, Himachal Pradesh, India

*Corresponding Author’s E-mail Address: rajeev1792@rediffmail.com

Online Published on 30 January, 2026.

Abstract

Anthropogenic growth-oriented activities have resulted in climate change over the globe, and thus, it is important to detect changes in land use/land cover (LULC) over different parts of the world in order to assess their influence on climate change. This study presents development and verification of the LULC changes in Hamirpur block of Himachal Pradesh, India due to modern urbanization. The LULC changes were evaluated over three periods, i.e., 2002-2013, 2013-2021 and 2002-2021. High-resolution imageries of Landsat-7, Landsat-8 and Sentinel-2 for the years 2002, 2013 and 2021, respectively, were used for developing the LULC maps by employing supervised classification techniques. The developed maps were verified by collecting ground truth data of 140 sites. The overall accuracy of the classified images for the years 2002, 2013, and 2021 was found to be 97.86%, 98.57% and 87.86%, respectively. The kappa coefficient values for 2002, 2013 and 2021 were 0.94, 0.98 and 0.95, respectively. Further, overlay analysis was carried out on the LULC maps for 2002-2013 and 2013-2021 to analyze the changes in LULC. The results revealed that area under agricultural land, barren/ shrub/ wasteland, and waterbody declined by 4.91%, 21.69%, and 25%, respectively during 2002-2021 period. An area of 0.992 km2 of waterbody class was converted to forest land, agriculture land, barren land and built-up area. The forest and agriculture classes (2.075 km2 area) were converted to built-up land. The reduction in waterbody is likely to affect water availability for irrigation and decrease crop production due to water shortage in future. However, built-up and forest areas increased by 2.39 km2 (22.05%) and 0.82 km2 (1.14%), respectively. These scientific observations support that anthropogenic growth-oriented activities are contributing to changes in LULC and climate.

Keywords

Confusion matrix, Producer accuracy, Remote sensing, Supervised classification, Kappa coefficient