Assessment of Green Infrastructure in Riparian Zones Using Copernicus Programme
Autor: | Diego González-Aguilera, Laura Piedelobo, Andrea Taramelli, Alessandra Nguyen Xuan, Emma Schiavon, Emiliana Valentini, José-Luis Molina |
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Rok vydání: | 2019 |
Předmět: |
geography
geography.geographical_feature_category 010504 meteorology & atmospheric sciences Land use business.industry Erosion control Environmental resource management green infrastructure riparian zone natural water retention measure ecosystem service Copernicus Sentinel-2 vegetation index water index downstream service 010501 environmental sciences 01 natural sciences Ecosystem services General Earth and Planetary Sciences Riparian forest Environmental science business Green infrastructure Bank Restoration ecology 0105 earth and related environmental sciences Riparian zone |
Zdroj: | Remote Sensing; Volume 11; Issue 24; Pages: 2967 |
ISSN: | 2072-4292 |
Popis: | This article presents an approach to identify Green Infrastructure (GI), its benefits and condition. This information enables environmental agencies to prioritise conservation, management and restoration strategies accordingly. The study focuses on riparian areas due to their potential to supply Ecosystem Services (ES), such as water quality, biodiversity, soil protection and flood or drought risk reduction. Natural Water Retention Measures (NWRM) related to agriculture and forestry are the type of GI considered specifically within these riparian areas. The approach is based on ES condition indicators, defined by the European Environment Agency (EEA) to support the policy targets of the 2020 Biodiversity Strategy. Indicators that can be assessed through remote sensing techniques are used, namely: capacity to provide ecosystem services, proximity to protected areas, greening response and water stress. Specifically, the approach uses and evaluates the potential of freely available products from the Copernicus Land Monitoring Service (CLMS) to monitor GI. Moreover, vegetation and water indices are calculated using data from the Sentinel-2 MSI Level-2A scenes and integrated in the analysis. The approach has been tested in the Italian Po river basin in 2018. Firstly, agriculture and forest NWRM were identified in the riparian areas of the river network. Secondly, the Riparian Zones products from the CLMS local component and the satellite-based indices were linked to the aforementioned ES condition indicators. This led to the development of a pixel-based model that evaluates the identified GI according to: (i) its disposition to provide riparian regulative ES and (ii) its condition in the analysed year. Finally, the model was used to prioritise GI for conservation or restoration initiatives, based on its potential to deliver ES and current condition. |
Databáze: | OpenAIRE |
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