Land Use and Land Cover Analysis of Hyderabad Metropolitan Development Authority (HMDA) Using Remote Sensing and GIS Techniques

Abstract

Rapid urbanization in the Hyderabad Metropolitan Development Authority (HMDA) region has resulted in significant transformations of land use and land cover (LULC) over the past 15 years. These changes, primarily characterized by the expansion of built-up areas at the expense of vegetation and water bodies, pose challenges to environmental sustainability and urban resilience. This study employs multi-temporal satellite imagery from 2009, 2014, 2019, and 2024 to map and quantify LULC dynamics using remote sensing and Geographic Information System (GIS) techniques. Supervised classification, supported by accuracy assessments exceeding 85%, was applied to delineate five key classes: built-up, vegetation, dense vegetation, barren soil, and water bodies. The results reveal a 33% increase in built-up land alongside substantial declines in vegetation (?240 km²) and water bodies (?87 km²). Spatial analysis highlights radial urban growth concentrated around Hyderabad’s core and outward expansion into surrounding districts. These findings demonstrate the ecological pressures of urban sprawl and emphasize the need for integrating geospatial monitoring into urban planning. By providing evidence-based insights, the study supports strategies aimed at conserving ecological resources, mitigating urban heat island effects, and promoting sustainable land management in rapidly growing metropolitan regions.

Introduction

Urbanization in the Hyderabad Metropolitan Development Authority (HMDA) area of Telangana, India, has led to significant land use and land cover (LULC) transformations over the last 15 years. Driven by population growth, infrastructure expansion, and economic development, these changes have reduced vegetation, fragmented agricultural land, and shrunk water bodies, posing environmental sustainability challenges.

Purpose:
This study analyzes the LULC changes in HMDA from 2009 to 2024 using multi-temporal satellite imagery and remote sensing techniques. The Maximum Likelihood Classification (MLC) method is applied to classify land into key categories—built-up areas, vegetation, dense vegetation, barren soil, and water bodies. The goal is to provide accurate LULC data to support sustainable urban planning and ecological impact assessments.

Study Area:
The HMDA region spans about 7,257 km², covering Hyderabad and surrounding districts. It lies on the semi-arid Deccan Plateau with a tropical wet-dry climate, featuring diverse topography and ecosystems. The area includes dense urban zones, agricultural land, forests, and water bodies, with rapid urban expansion due to Hyderabad’s commercial and IT significance.

Methodology:
Satellite images from 2009, 2014, 2019, and 2024 (Landsat, Sentinel) were used. Images underwent preprocessing (geometric and atmospheric corrections), and supervised classification was performed with SVM and MLC algorithms, validated through ground truth data, achieving over 85% accuracy.

Results:

• Built-up areas increased significantly from 2421 km² in 2009 to 2874 km² in 2014, reflecting urban growth.

• Vegetation and water bodies declined, while barren land decreased moderately.

• These trends highlight ongoing urbanization pressures, impacting natural landscapes and ecological balance.

Conclusion

This study provides a focused assessment of Land Use and Land Cover (LULC) changes in the HMDA region for the month of May, examining spatial shifts from 2009 to 2024. The results indicate a substantial and consistent increase in built-up areas, driven by urban expansion, which is paralleled by a decline in vegetative cover and water bodies. These transformations underscore the growing pressure urbanization places on the region\'s natural resources. Through the use of remote sensing and GIS techniques, the research effectively maps these changes, offering valuable insights for urban planners and policymakers. The study emphasizes the need for proactive land use policies that promote sustainable development while conserving critical green and blue spaces. If such trends continue unchecked, the region could face severe environmental consequences including reduced groundwater recharge, loss of biodiversity, and increased vulnerability to climate-induced risks. In conclusion, the findings call for a more integrated approach to urban planning—one that leverages geospatial intelligence to ensure balanced growth. Preserving ecological assets alongside infrastructure development is key to securing a livable and resilient future for the HMDA region.

References

[1] Kumar Ashwini (2021), “Impacts of Land Use and Land Cover Changes on Land Surface Temperature over Cachar Region, Northeast India.” MDPI. [2] Lilly Rose Amirtham (2009), “Analysis of Land Surface Temperature and Land Use/Land Cover Types Using Remote Sensing Imagery – Chennai City.” ResearchGate. [3] Pir Mohammad (2022), “Machine Learning Algorithm Based Prediction of Land Use and LST over Ahmedabad City.” ScienceDirect. [4] Priyanka Gupta (2023), “Application of Remote Sensing and GIS Techniques for LULC Change Detection: A Case Study.” IJST. [5] https://earthexplorer.usgs.gov/ [6] https://data.telangana.gov.in/

Copyright

Copyright © 2025 Akula Saikrishna, Dr. M. V. S. S. Giridhar. 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.