Spatiotemporal LULC transformation and its association with urban heat island amplification in Hyderabad city using machine learning
Year: 2026
Type: article
Abstract: Hyderabad has experienced rapid urban expansion during the last two decades, resulting in substantial land use/land cover (LULC) transformation and increasing urban heat island intensity. However, comprehensive assessments integrating long-term predictive modelling with high-confidence hotspot identification remain scarce for rapidly growing tropical cities. Therefore, this study introduces a novel multi-method approach combining machine learning algorithm (Support Vector Machine), geospatial statistics (Getis-Ord GI hotspot analysis at 99% confidence level), and predictive modelling (ANN-MLP using MOLUSCE plugin) to assess and forecast LULC and land surface temperature (LST) dynamics in Hyderabad city. Landsat 5 TM and Landsat 8 OLI/TIRS data of 2001, 2011, and 2021 were used to quantify LST variations and identify persistent hotspots. The results indicate that the highest temperature is observed in urban built-up areas (35.93ºC) and open spaces (37.25ºC) and the lowest temperature is observed in water bodies (17.99ºC). The multiple linear regression analysis shows that urban built-up fraction (β = 0.58, p < 0.001) is the strongest positive driver of LST, while water bodies (β = − 0.44, p < 0.001) and NDVI (β = − 0.53, p < 0.001) have the most significant cooling effects. The predicted modelling for 2030 showed that the temperature of between 37–40°C covered the largest area (10,065 hectares) followed by 34–37 °C (6,994 hectares) influenced by urbanization (7,876 hectares of built-up area). Also, open space (1,959 hectares), water bodies (0.72 hectares) and aquatic vegetation (2.34 hectares) were associated with lower LST values than built-up areas in Hyderabad City. This study is the first to combine hotspot analysis with long-term predictive modelling in the city of Hyderabad, thus offering actionable insights to urban planners through a scenario-based assessment of future thermal conditions. Findings such as these highlight the need to incorporate water bodies, green spaces, and sustainable land-use planning in mitigating UHI effects and improving urban climate resilience.
Source: Discover Earth Observation
Institution: Central University of Punjab
Language: English
Topic: Urban Heat Island Mitigation
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Funder: U.S. Geological Survey
OpenAlex ID: W7224228097