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Ecosystem Service Function Supply–Demand Evaluation of Urban Functional Green Space Based on Multi-Source Data Fusion.
- Source :
-
Remote Sensing . Jan2023, Vol. 15 Issue 1, p118. 25p. - Publication Year :
- 2023
-
Abstract
- With the rapid development of urbanization, it is an important goal for urban green space (UGS) to meet the needs of residents' production and life using a supply–demand evaluation method of ecosystem service (ES). However, most studies have considered all functional types of UGS as the supply side, or rely solely on a single supply or demand side to conduct ecosystem service function (ESF) evaluation, resulting in less accurate and targeted research findings. As a result, a novel methodological framework for matching each ESF with corresponding functional types of UGS, and considering both supply and demand sides have been required. Firstly, the object-oriented approach combining support vector machine (SVM) and normalized difference vegetation index (NDVI) was used to automatically identify UGS, and integrated Point of Interest (POI), urban built-up area, road land, parcel, and socio-economic data to classify six functional types of UGS using the near-convex-hull. Next, matching the functional types of UGS with five ESFs, both supply and demand status were evaluated using the carbon sequestration and release analysis, Gaussian two-step floating catchment area, and spatial equilibrium degree methods. This method was demonstrated in Beijing, China. The results show: (1) the ES supply–demand situation provided by each functional type of UGS is different in five ESFs; (2) considering both supply and demand is more intuitive to see whether the city's demand for UGS has been met. Our results provide a new perspective for evaluating the contribution of UGS and have practical implications for UGS planning. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 15
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 161182935
- Full Text :
- https://doi.org/10.3390/rs15010118