Temporal Assessment of Surface Land Transformations Using Landsat-8 Imagery and GIS

Abstract

Land use and land cover change is a key indicator of human and environmental interaction, reflecting the impact of urbanization, agriculture, and climate variability on natural resources. This study focuses on the spatio-temporal assessment of LULC transformations in Jogulamba Gadwal District, Telangana, for the period 2015 to 2024, using Landsat-8 satellite imagery and Geographic Information System (GIS) techniques. Multi-temporal images were processed through layer stacking, band composition, and supervised classification to identify five major land-cover categories: vegetation, agricultural land, built-up area, barren land, and water bodies. Accuracy assessment was performed using ground-truth data and confusion-matrix validation. The results revealed a notable increase in vegetation and barren land, primarily due to rapid urban expansion and agricultural conversion. Water bodies showed slight temporal fluctuations linked to rainfall variation. The analysis demonstrates the value of integrating satellite imagery and GIS for monitoring land-use dynamics and supports sustainable resource-management planning in semi-arid regions of Telangana.

Introduction

Land Use and Land Cover (LULC) analysis is crucial for understanding how human activities influence the environment, particularly in semi-arid regions like Telangana. Rapid population growth, agricultural expansion, and urban development have driven major land-use changes, affecting hydrological processes, ecosystem stability, and regional sustainability. Remote Sensing (RS) and GIS technologies—especially multi-temporal Landsat imagery—enable accurate mapping and monitoring of these changes.

This study examines the spatio-temporal LULC transformations in Jogulamba Gadwal District, Telangana, between 2015 and 2024, using Landsat-8 data processed in ArcGIS. The classified land-cover categories include agricultural land, vegetation, built-up areas, barren land, and water bodies. The district spans about 2,575.5 km², characterized by a semi-arid climate, undulating terrain, and predominantly agricultural land use.

Methodologically, the study involves data acquisition from USGS, image preprocessing (layer stacking, atmospheric correction, FCC generation), supervised classification using the Maximum Likelihood algorithm, and preparation of thematic maps with area statistics.

Results show notable land-cover changes over the decade. In 2015, built-up areas dominated (1,764.34 km²), with moderate vegetation (320.98 km²) and significant barren land (317.58 km²). By 2024, barren land had more than doubled to 696.17 km², water bodies increased substantially to 144.98 km², and vegetation rose to 527.58 km². Meanwhile, built-up areas decreased to 1,090.15 km², while forest cover remained relatively stable. These trends indicate expanding barren surfaces, increased water storage, shifts in vegetation cover, and reduced settlement-related land use. The findings provide essential insights for sustainable land and water-resource planning in the district.

Conclusion

The analysis of landuse and landcover between 2015 to 2024 using Landsat-8 imagery and GIS revealed distinct changes in the surface features of within the study area. The district experienced a steady increase in barren land from 317.58 km² to 696.17 km² and a rise in water bodies extent from 58.93 km² to 144.98 km², indicating both land degradation and improved surface-water storage. Vegetation also increased from 320.98 km² to 527.58 km², reflecting the increase in the agricultural activities in the study area. Built-up area declined from 1764.34 km² to 1,090.15 km², representing phases of rapid development followed by saturation. Forest cover almost remained the same throughout the study area. Overall, the district’s land transformation trends suggest that urban growth, agricultural conversion and climatic variability are the major factors influencing surface-land changes. The increase in barren areas highlights the need for integrated land-use planning, afforestation and soil water conservation initiatives. The study confirms that Landsat-8 imagery integrated with GIS provides an effective and economical approach for continuous monitoring of regional land-use dynamics and supports future decision-making for sustainable land resource management in semi-arid regions of Telangana.

References

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Copyright

Copyright © 2025 Banoth Sohan Singh, C. Sarala. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.