Monitoring Landuse and Land Cover Changes Prospects using Remote Sensing and GIS for Mahanadi River Delta, Orissa, India

IJEP 43(3): 251-256 : Vol. 43 Issue. 3 (March 2023)

Y. Padmini1, Chandana Indeti2, Yamala Vinay Kumar2, M. Srinivasa Rao2 and Gara Raja Rao2*

1. Dr. B.R. Ambedkar University, Department of Geosciences, Srikakulam, Andhra Pradesh – 532 410, India
2. Andhra University, Department of Geology, Visakhapatnam, Andhra Pradesh – 530 003, India


Natural landscapes have altered dramatically via anthropogenic activity, particularly in places that are heavily influenced by climate change and population increase, such as nations, like India. It is crucial for sustainable development, particularly effective water management methods, to know about the influence of landuse and land cover (LULC) changes. Geographic information systems (GIS) and remote sensing (RS) were employed for monitoring landuse changes utilising Quantum ArcGIS and ERDAS Imagine. This research studied the variations in LULC in the Mahanadi river basin delta, Orissa for the years 2010, 2015 and 2020. Landsat satellite pictures were employed to track the landuse changes. For the categorization of Landsat images, maximum-likelihood supervised classification was applied. The broad categorization identifies four basic groups in the research region, including (i) water bodies, (ii) agriculture fields, (iii) forests, (iv) barren lands, (v) built-up areas and (vi) aquaculture. The findings indicated a big growth in forests from the year 2010 to 2020, but a substantial increase in barren lands had happened by the year 2020, while built-up landuse has witnessed a quick climb. The kappa coefficient was used to measure the validity of identified photos, with an overall kappa coefficient of 0.82, 0.84 and 0.90 for the years 2010, 2015 and 2020, respectively. However, a large drop will occur in agriculture fields in the predicted years. The study effectively demonstrates LULC alterations showing substantial patterns of landuse change in the Mahanadi delta. This information might be valuable for landuse management and future planning in the region.


Landuse/Land cover, Sustainable planning, Landsat image, Remote sensing, GIS


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