TY  - JOUR
AU  - Gupta, Rupesh Kumar
PY  - 2026
DA  - 2026/05/19
TI  - Integrated Assessment and Projection of Urban Expansion and Thermal Dynamics in Bangalore Using Multi-Temporal Landsat Data and Machine Learning Techniques
JO  - Advances in Environmental and Engineering Research
SP  - 009
VL  - 07
IS  - 02
AB  - Rapid urbanization has remarkably altered land surface characteristics and thermal environments in Indian metropolitan cities, thereby increasing ecological pressure and urban heat risk. This study integrates assessments of land use and land cover (LULC) change and LST, and the UTFVI for Bangalore, India, using multi-temporal Landsat imagery and geospatial techniques, along with machine learning methods. LULC changes were studied and analyzed for 2000 and 2020, and a simulation to 2024 was performed, employing a Random Forest Classifier and a CA–ANN outline with the MOLUSCE model in QGIS. At the same time, seasonal LST and UTFVI patterns were studied for 2005, 2015, and 2025, and future thermal conditions were forecast for 2045 using Random Forest regression. The study’s outcomes show remarkable growth in the urban region, with the built-up area increasing from 277.93 km2 (12.64%) in 2000 to 501.89 km2 (22.83%) in 2020, projected to be 666.19 km2 (30.30%) by 2045. A sharp reduction in the areas of water bodies and vegetation cover accompanied this. The thermal analysis indicates a clear increase in warming during both summer and winter. There was also a consistent spreading pattern of moderate to high temperatures, ranging from 30-35°C and 35-40°C. According to the UTFVI, there is a shift in ecological thermal patterns, with a reduction in extreme “worst” levels of thermal stress zones and a considerable expansion of mid-levels. The study's results highlight the relationship between land-use dynamics and urban thermal dynamics. Specifically highlighting the pressing need for climate-sensitive approaches in land-use planning, focus on the preservation of green and blue spaces, and the adoption of sustainable urban growth paths.
SN  - 2766-6190
UR  - https://doi.org/10.21926/aeer.2602009
DO  - 10.21926/aeer.2602009
ID  - Gupta2026
ER  -