Mapping and monitoring Urban Environment through Sentinel-1 SAR data
About this good practice
Focusing on sustainable and strategic development, Veneto Region decided to manage its urban and territorial planning by developing a semi-automatic process to map and monitor the regional urban environment, and in particular to extract the spatial extent of urban features over non-urban areas (i.e., urban footprint).
By using Sentinel-1 SAR imagery and performing a multitemporal analysis of interferometric coherence data as well as supervised and non-supervised classification algorithms, it has been proven possible to identify the urban footprint in a precise (level I CLC), fast and cost-efficient way.
Stakeholders and beneficiaries are mainly regional authorities and agencies in charge of spatial planning, cartography and soil consumption monitoring (Veneto Region and Regional Agency for Environment Protection – ARPAV).
Furthermore, there has been a specific interest by policy makers on this practice, as soil consumption became a topic of growing importance in the public debate. In fact, this methodology may be a useful tool to support the production of geographic indicators to assess the targets of SDG 11 (“Make cities and human settlements inclusive, safe, resilient and sustainable”, as defined in the UN 2030 Agenda) or the EU Soil Strategy (part of the EU Green Deal).
Resources needed
Total cost for the completion and the release of the new land cover map for Veneto Region: 200.000 €;
Cost for the yearly update and maintenance: 50.000 €/ year.
Evidence of success
The images produced with this semi-automatic process resulted in a high overall accuracy (up to 90%) in comparison to images produced with traditional techniques, with errors lower than 1%–2% in regards to percentage of urban footprint monitoring (study by A. Semenzato, S. Pappalardo, D. Codato, U. Trivelloni, S. De Zorzi, S. Ferrari, M. Massironi, 2020).
Potential for learning or transfer
Since this methodology relies on open source tools and software and globally available free data, it can be easily replicated in other regions.
Further information
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Good practice owner
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