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Climate issues are nowadays one of the most pressing societal challenges, with cities being identified among the landmarks for climate change. This study investigates the effect of urban land cover composition on a relevant climate-related variable, i.e., the air temperature. The analysis exploits different big geo-data sources, namely high-resolution satellite imagery and in-situ air temperature observations, using the city of Milan (Northern Italy) as a case study. Satellite imagery from the Landsat 8, Sentinel-2, and RapidEye missions are used to derive Local Climate Zone (LCZ) maps depicting land cover compositions across the study area. Correlation tests are run to investigate and measure the influence of land cover composition on air temperature. Results show an underlying connection between the two variables by detecting an average temperature offset of about 1.5∘    C between heavily urbanized and vegetated urban areas. The approach looks promising in investigating urban climate at a local scale and explaining effects through maps and exploratory graphs, which are valuable tools for urban planners to implement climate change mitigation strategies. The availability of worldwide coverage datasets, as well as the exclusive use of Free and Open Source Software (FOSS), provide the analysis with a potential to be empowered, replicated, and improved.

Measuring Urban Land Cover Influence on Air Temperature through Multiple Geo-Data—The Case of Milan, Italy