Dynamic evaluation of small urban green areas at local level using GEOBIA

Abstract

<p>Urban green infrastructure has various benefits known as ecosystem services such as regulating, cultural, provisioning and supporting services. Among the provided benefits there are decrease of air temperature, increasing humidity and mitigating urban heat island as regulating services; human-nature relations as cultural services; improving air quality, carbon sequestration as provisioning services and photosynthesis, nutrient and water cycling as supporting services. The high intensity of the urbanization process across the last decades coupled with weak legislative frameworks resulted both in large areas affected by urban sprawl and densification of the existing urban fabric. Both phenomenon generated loss in open spaces, especially green areas. In the context of the sustainable urbanization promoted by HABITAT Agenda, the knowledge related with the distribution, size and quality of urban green areas represents a priority. The study aim is to identify small urban green areas at local level at different time moments for a dynamic evaluation. We focused on small urban green areas since they are scarcely analysed even if their importance for the urban quality of life Is continuously increasing given the urbanization process. We used satellite imagery acquired by Planet Satellite Constellations, with a spatial resolution of 3.7 m and daily coverage, for extracting green areas. The images were processed using Geographic Object-Based Image Analysis (OBIA) techniques implemented in Esri ArcGIS Pro. The spatial analysis we performed generated information about distribution, surfaces, quality (based on NDVI) and dynamic of small urban green areas. The results are connected with the local level development of the urban areas we analysed, but also with the population consumption pattern for leisure services, housing, transport or other public utilities. The analysis can represent a complementary method for extracting green areas at urban level and can support the data collection for calculating urban sustainability indicators.</p>