Satellite-Based Trends Analysis of Land Surface Temperature, Vegetation Growth, and Precipitation: Evaluating Seasonal Variation and Correlation in Ahmedabad, India

Objectives: This study aims to analyze LST, NDVI, and precipitation patterns in Ahmedabad, India, from 2014 to 2023. The main research purpose is to study component relationships and assess the influence of vegetation and rainfall on urban heat management. Methods: The study used Landsat 8 satellite data at a high resolution together with CHIRPS rainfall data through Google Earth Engine (GEE) to extract LST, NDVI, and precipitation patterns. The analysis computed seasonal averages while Pearson correlation methods evaluated variable relationships between pre-monsoon, monsoon, and post-monsoon periods. The team used previous findings to validate the obtained temporal trends in their analysis. Findings: The data showed that when pre-monsoonal heat stress increased from 39.32 °C in 2014 to 41.29 °C in 2023 while all seasons demonstrated intensifying heat stress patterns. The NDVI levels showed a decreasing tendency during this period, as it went from 0.362 to 0.343, thus indicating both vegetation reduction and heat-related stress in the area. The positive connection between precipitation and NDVI reached its highest value of 0.43 during monsoon, while during post-monsoon it increased to approximately 0.52. During post-monsoon periods, the negative relationship between NDVI and LST reached -0.59. Surface temperatures show different patterns of influence depending on seasonal variations between rainfall and vegetative cover. Novelty: The research combines long-term high-definition seasonal evaluations of LST and NDVI and precipitation records from Landsat 8 and GEE for analyzing changes in a rapidly expanding Indian metropolis. This study stands apart from prior short-term and coarse-resolution research since it delivers both fine-scale and season-specific understanding regarding how climate and urbanization jointly affect surface thermal environments. The study delivers essential knowledge to develop urban planning approaches that combine vegetation control and heat wave protection systems under climate change. Keywords: Land Surface Temperature, NDVI, precipitation, Seasonal variation, Pearson correlation, Satellite data