Trend Analysis and Temperature Prediction Using MODIS Time Series Images in the Metropolitan Regions of Campinas and Piracicaba - Brazil

Abstract. This study examines land surface temperature (LST) trends and future projections in the Metropolitan Regions of Campinas and Piracicaba, São Paulo, Brazil, from 2002 to 2022. A time series of 15,091 MODIS LST images (MOD11A1 and MYD11A1 products, v6.1) was processed using Google Earth Engine to generate monthly composites, which were subsequently analyzed in ArcGIS Pro. Harmonic regression modeling identified seasonal and interannual temperature trends and simulated monthly temperatures through 2033. Eight municipalities, grouped by urban density, were selected for detailed comparison. The results indicate persistently higher LST values in highly urbanized areas, while municipalities with initially lower urbanization levels exhibited steeper warming trends over time. Projected January temperature increases between 2023 and 2033 range from 0.4°C to 1.0°C, with the most pronounced changes occurring in areas experiencing rapid land-use transformation. These findings are consistent with broader patterns of urban heat island intensification, emphasizing the combined effects of vegetation loss, impervious surface expansion, and urban densification. While the projections are statistical estimates based on historical trends, they provide valuable guidance for climate adaptation strategies and urban planning. This study demonstrates the utility of MODIS time series and multidimensional GIS analysis for monitoring and forecasting thermal dynamics in rapidly urbanizing regions.