Land Management and Utilization

Research Article

Dynamic Change Analysis of Landuse Landcover in Darrang, Assam (India) Using Remote Sensing and Geospatial Techniques

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https://doi.org/10.54963/lmu.v1i4.2129
Volume 1 Issue 4 (2025)
Copyright (c) 2025 Sarmistha Das, Pratistha Bhattacharyya, Shukla Acharjee, Biswajit Nath, Binita Pathak
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Authors

  • Sarmistha Das

    Centre for Studies in Geography, Dibrugarh University, Dibrugarh 786004, Assam, India
  • Pratistha Bhattacharyya

    Centre for Studies in Geography, Dibrugarh University, Dibrugarh 786004, Assam, India
  • Shukla Acharjee

    Centre for Studies in Geography, Dibrugarh University, Dibrugarh 786004, Assam, India
    Centre for Atmospheric Studies, Dibrugarh University, Dibrugarh 786004, Assam, India
  • Biswajit Nath

    Lab of Geoinformatics and Earth Observation Research (LGEOR), Department of Geography and Environmental Studies, University of Chittagong, Chittagong 4331, Bangladesh
  • Binita Pathak

    Centre for Atmospheric Studies, Dibrugarh University, Dibrugarh 786004, Assam, India
    Department of Physics, Dibrugarh University, Dibrugarh 786004, Assam, India

Received: 22 September 2025 | Revised: 11 October 2025 | Accepted: 17 October 2025 | Published Online: 14 November 2025

In today’s world, the mapping of landuse and landcover (LULC) and its change analysis are considered a critical research area. LULC study of an area shows the relationship between human activities and natural processes influencing the ecological balance and socio-economic development. Assam, a state in North-Eastern India, is showing landscape alteration due to multiple developmental processes. The present study is first carried out mapping of LULC using multi-temporal Landsat Satellite Earth Observation datasets from 1995–2025, followed by change analyses of influencing factors that altered LULC in Darrang district of Assam. Geospatial tools like ERDAS Imagine and ArcGIS 10.8 software were applied for image processing and supervised classification using the maximum likelihood algorithm. The overall classification accuracy ranged from 83.85% to 91.43%, indicating a very good to excellent agreement. Categories are considered for the present analysis. In this connection, six major LULC classes are generated, and dynamic changes are interpreted and analysed for three decades. The result of this study reveals several changing aspects, including decline in vegetation cover from 13.85% in 1995 to 11.74% in 2015 and a slight increase of 0.63% in 2025. In addition, a decrease in agricultural land from 57.84% in 1995 to 43.35% in 2025 and an increase in built-up area from 5.05% in 1995 to 12.31% in 2025 are also evident. A notable rise of about 8.28% also seen in the area under barren land from 1995 to 2025. The study of LULC change mapping are necessary for future environmental protection and sustainable development.

Keywords:

Landuse and Landcover Dynamic Changes Driving Factors Landsat Imagery Darrang Assam

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