From GI, UGI to UAGI: Ecosystem service types and indicators of green infrastructure in response to ecological risks and human needs in global metropolitan areas

《From GI, UGI to UAGI: Ecosystem service types and indicators of green infrastructure in response to ecological risks and human needs in global metropolitan areas》

打印

作者: Jiake Shen;Zhenwei Peng;Yuncai Wang

来源: CITIES,Vol.135,Issue1,Article 104176

语言: 英文

关键字

作者单位: Key Laboratory of Ecology and Energy-saving Study of Dense Habitat (Tongji University), Ministry of Education, Department of Urban Planning, College of Architecture and Urban Planning, Tongji University, No.1239 Siping Rd., Shanghai 200092, China;Joint Laboratory of Ecological Urban Design (Research Centre for Land Ecological Planning, Design and Environmental Effects, International Joint Research Centre of Urban-Rural Ecological Planning and Design), Department of Landscape Architecture, College of Architecture and Urban Planning, Tongji University, No. 1239 Siping Rd., Shanghai 200092, China;Key Laboratory of Ecology and Energy-saving Study of Dense Habitat (Tongji University), Ministry of Education, Department of Urban Planning, College of Architecture and Urban Planning, Tongji University, No.1239 Siping Rd., Shanghai 200092, China;Joint Laboratory of Ecological Urban Design (Research Centre for Land Ecological Planning, Design and Environmental Effects, International Joint Research Centre of Urban-Rural Ecological Planning and Design), Department of Landscape Architecture, College of Architecture and Urban Planning, Tongji University, No. 1239 Siping Rd., Shanghai 200092, China;Department of Geography, Ghent University, Ghent 9000, Belgium;Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China;The State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430000, China;Department of Architecture & Urban Planning, Ghent University, Ghent 9000, Belgium;Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, 350108 Fuzhou, China;National Engineering Research Center of Geospatial Information Technology, Fuzhou University, 350108 Fuzhou, China;Academy of Digital China (Fujian), China;PBL Netherlands Environmental Assessment Agency, PO Box 30314, 2500 GH The Hague, the Netherlands;Institute for Science in Society, Radboud University, PO Box 9010, 6500 GL, Nijmegen, the Netherlands;BEEA Limited, PO Box 28105, Wellington 6150, New Zealand;School of Geography, Environment and Earth Sciences, Victoria University of Wellington, PO Box 600, Wellington 6140, New Zealand;Department of Environmental Science, Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, PO Box 9010, 5600 GL Nijmegen, the Netherlands;Full Length Article"}]},{"#name":"title","$":{"id":"tm005"},"_":"Comparing three spatial modeling tools for assessing urban ecosystem services"}],"floats":[],"footnotes":[],"attachments":[]},"openArchive":false,"openAccess":true,"document-subtype":"fla","content-family":"serial","contentType":"JL","abstract":{"$$":[{"$$":[{"$":{"id":"st005"},"#name":"section-title","_":"Highlights"},{"$$":[{"$$":[{"$$":[{"$$":[{"#name":"label","_":"•"},{"$":{"view":"all","id":"p0005"},"#name":"para","_":"We applied three ecosystem service models (InVEST, LUCI, NC-Model) to a common study area."}],"$":{"id":"o0005"},"#name":"list-item"},{"$$":[{"#name":"label","_":"•"},{"$":{"view":"all","id":"p0010"},"#name":"para","_":"We compared three urban ecosystem services quantified for the current situation and two scenarios."}],"$":{"id":"o0010"},"#name":"list-item"},{"$$":[{"#name":"label","_":"•"},{"$":{"view":"all","id":"p0015"},"#name":"para","_":"We found positive correlations but also systematic differences between model outputs for a given service."}],"$":{"id":"o0015"},"#name":"list-item"},{"$$":[{"#name":"label","_":"•"},{"$":{"view":"all","id":"p0020"},"#name":"para","_":"Models also responded differently to the scenarios."}],"$":{"id":"o0020"},"#name":"list-item"},{"$$":[{"#name":"label","_":"•"},{"$":{"view":"all","id":"p0025"},"#name":"para","_":"We recommend more systematic assessments of uncertainty in urban ecosystem service modelling."}],"$":{"id":"o0025"},"#name":"list-item"}],"$":{"id":"l0005"},"#name":"list"}],"$":{"view":"all","id":"sp0005"},"#name":"simple-para"}],"$":{"view":"all","id":"as005"},"#name":"abstract-sec"}],"$":{"view":"all","id":"ab005","lang":"en","class":"author-highlights"},"#name":"abstract"},{"$$":[{"$":{"id":"st010"},"#name":"section-title","_":"Abstract"},{"$$":[{"$":{"view":"all","id":"sp0010"},"#name":"simple-para","_":"The (re)integration of nature into cities has been a progressively promoted strategy to foster sustainable urbanization. To quantify the ecosystem services (ES) provided by urban nature, spatially explicit ES modeling is a key method. However, particularly in absence of independent validation data, there is a clear need for multi-model assessments in order to better understand uncertainties in model outcomes. Here we applied three commonly used open-source ES models (i.e., InVEST, LUCI, NC-Model) to quantify three key urban ES (i.e., local temperature regulation, flood protection and global climate regulation) using the city of The Hague (The Netherlands) as a case study. We quantified the three ES for the current situation and under two hypothetical scenarios representing changes in the amount of vegetation within the city. We found mostly positive correlations between the estimates for a given ES (Spearman’s ρ from 0.11 to 0.84). Yet, our comparison also revealed systematic differences in the ES indicator values between the ES models, as well as different responses to the scenarios. These differences may stem from differences in model structure (i.e., differences in biophysical processes accounted for) and model parameterization (i.e., differences in the value used to quantify a given biophysical process). To further advance urban ES modeling, we recommend i) to improve the representation of urban nature (e.g., green roofs, bioswales, gardens) and urban-specific conditions and processes (e.g., drainage systems, building patterns, soil characteristics) in urban ES models and ii) to systematically account for uncertainty in (urban) ES assessments (e.g., through multi-model assessments)."}],"$":{"view":"all","id":"as010"},"#name":"abstract-sec"}],"$":{"view":"all","id":"ab010","class":"author"},"#name":"abstract"}],"$":{"xmlns:ce":true,"xmlns:dm":true,"xmlns:sb":true},"#name":"abstracts"},"pdf":{"urlType":"download","url":"/science/article/pii/S2212041622000961/pdfft?md5=ceb432547732008aadb8f739b116d97c&pid=1-s2.0-S2212041622000961-main.pdf"},"iss-first":"","vol-first":"59","isThirdParty":false,"issn-primary-unformatted":"22120416","issn-primary-formatted":"2212-0416"},{"pii":"S026427512200600X","doi":"10.1016/j.cities.2022.104161","journalTitle":"Cities","publicationYear":"2023","publicationDate":"2023-03-01","volumeSupText":"Volume 134","articleNumber":"104161","pageRange":"104161","trace-token":"AAAAQN06ZqDNY0x3I9YrtNNRyLfTdhQfHERah-GvuhQ_U-SpVIdUAT_QHA60hKiRl7cjvSVhWLYPZHw-3FynIQc56tG-9EO-spSpBDcdtW1vGycH7cIMVQ","authors":{"content":[{"#name":"author-group","$":{"id":"ag0005"},"$$":[{"#name":"author","$":{"id":"au0005","author-id":"S026427512200600X-cf579f8460060a4f0d9d4b62799ba863"},"$$":[{"#name":"given-name","_":"Yechennan;Institute of Geography, Center for Earth System Research and Sustainability (CEN), University of Hamburg, 20146 Hamburg, Germany;School of Integrated Climate System Sciences, University of Hamburg, 20146 Hamburg, Germany;Department of Earth Sciences, University of Sargodha, Sargodha, Pakistan;Department of Geography, Lab for Landscape Ecology, Humboldt Universität zu Berlin, Berlin, Germany;Department of Urban and Environmental Sociology, Helmholtz Centre for Environmental Research UFZ, Leipzig, Germany;St. Peter's College, University of Oxford, New Inn Hall Street, Oxford OX1 2DL, United Kingdom;Department for Continuing Education, University of Oxford, Rewley House, 1 Wellington Square, OX1 2JA, Oxford, United Kingdom;Technical University of Munich, Chair of Data Science in Earth Observation, Arcisstraße 21, Munich 80333, Germany;German Aerospace Center, Remote Sensing Technology Institute, Muenchener Straße 20, Weßling 82234, Germany

摘要: Green infrastructure (GI), providing multiple ecosystem services (ESs), is considered a key way to address ecological risks and human needs faced by global metropolitan areas. However, there is no review of GI's response to multiscale risks and needs by providing ESs. To address this research gap, we used systematic review method by searching articles constructing GI based on ES evaluation and mapping from 2005 to 2021 in Scopus and Web of Science databases, and eventually selected 101 articles. We observed three research scales and GI construction forms: GI and its components, urban GI (UGI), and urban agglomeration GI (UAGI). We found that: 1) flood disasters and human demand for outdoor recreational spaces were dominant risks and needs co-faced by metropolitan areas on three scales. 2) The proportion of GI components in UGI and UAGI providing special ES for specific risk and need should be raised to avoid disservices or ES trade-offs. 3) More attention should be given to the overall ES capacity in both quantity and efficiency of UGI and UAGI networks. Finally, UAGI with superiority in function, layout, and ability to address risks and needs was proposed as a prioritized planning approach to adapt to development of metropolitan areas.