A remote sensing index for assessing peri-urban ecosystem services: a case from tuscany (italy)

This work proposes a Resilience Index of Ecosystem Services (RIES) that is based on remote sensing to assess the ecological quality of highly anthropized territories. The study area is characterized as an urbanized area of Florence and Prato in central Tuscany (Italy). The proposed method was derived from the Pressure-State-Response (PSR) framework, which focuses on the notion of causality and involves the selection and measurements of three categories indicators: environmental state, anthropogenic pressure and climatic response. The first of which consists of the Ecosystem Services Provision Index (ESPI), which is derived from the Cascade theory and is evaluated using two statistics of the seasonal dynamics of the normalized difference vegetation index (NDVI), that are calculated from Sentinel 2 images: the annual mean (mean NDVI) and the intra-annual Coefficient of Variation of the NDVI (CV NDVI). The calculation is as follows: ESPI = average NDVI * (1-NDVI CV). The second category is characterized by the Normalized Difference Built-up Index (NDBI) and is derived from the Sentinel 2 images. The third is composed of the climate resilience index, which is calculated by combining the Land Surface Temperatures (LST) with the Tasseled Cap - wetness index both from Landsat 8 images. The third is composed of the climate resilience index, which is calculated by combining the Land Surface Temperatures (LST) with the Tasseled Cap - wetness index both from Landsat 8 images. These three macro indices are aggregated through a Dempster-Shafer rule of combination with weights derived using a Principal Components Analysis (PCA). The aggregation of these macro indices allows us to obtain the RIES index.