Blog
About

0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Deep learning: To better understand how human activities affect the value of ecosystem services—A case study of Nanjing

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The value of ecosystem services is affected by increasing human activities. However, the anthropogenic driving mechanisms of ecosystem services are poorly understood. Here, we established a deep learning model to approximate the ecosystem service value (ESV) of Nanjing City using 23 socioeconomic factors. A multi-view analysis was then conducted on feasible impact mechanisms using model disassembly. The results indicated that certain factors had their own significant and independent effects on ESV, such as the proportion of water areas in the land-use structure and the output value of the secondary industry. The proportion of ecological water should be increased as much as possible, whereas the output value of the secondary industry should be reasonably controlled in Nanjing. Other intrinsically related factors were likely to be composited together to affect ESV, such as industrial water consumption and industrial electricity consumption. In Nanjing, simultaneously optimizing socio-economic factors related to city size, resources, and energy use efficiency likely represents an effective management strategy for maintaining and enhancing regional ecological service capabilities. The results of this work suggest that deep learning is an effective method of deepening studies on the prediction of ESV trends and human-driven mechanisms.

          Related collections

          Most cited references 42

          • Record: found
          • Abstract: not found
          • Article: not found

          Deep learning and process understanding for data-driven Earth system science

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Mapping ecosystem services bundles to detect high- and low-value ecosystem services areas for land use management

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              New green theories of urban development in China

               Q.F. Ji,  C.C. Li,  P. JONES (2017)
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: VisualizationRole: Writing – original draft
                Role: ConceptualizationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Investigation
                Role: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: ResourcesRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                6 October 2020
                2020
                : 15
                : 10
                Affiliations
                [1 ] School of Geography and Ocean Science, Nanjing University, Nanjing, China
                [2 ] School of Architecture and Urban Planning, Nanjing University, Nanjing, China
                [3 ] Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
                [4 ] School of Geography, Nantong University, Nantong, China
                Institute for Advanced Sustainability Studies, GERMANY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Article
                PONE-D-20-12056
                10.1371/journal.pone.0238789
                7537890
                33021994
                © 2020 Liu et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 5, Tables: 6, Pages: 16
                Product
                Funding
                Funded by: Environmental Protection Research Project of Jiangsu Province
                Award ID: 2018008
                Award Recipient :
                Funded by: Environmental Science and Technology Project of Nanjing
                Award ID: 201904
                Award Recipient :
                This work was supported by Department of Ecology and Environment of Jiangsu Provvince ( http://hbt.jiangsu.gov.cn/) grants 2018008 to T.N., and Department of Science and Technology of Jiangsu Province ( http://std.jiangsu.gov.cn/) grants 201904 to T.N. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Ecology
                Ecosystems
                Ecology and Environmental Sciences
                Ecology
                Ecosystems
                Computer and Information Sciences
                Artificial Intelligence
                Machine Learning
                Deep Learning
                Earth Sciences
                Geography
                Human Geography
                Land Use
                Social Sciences
                Human Geography
                Land Use
                Biology and Life Sciences
                Ecology
                Ecosystems
                Ecosystem Functioning
                Ecology and Environmental Sciences
                Ecology
                Ecosystems
                Ecosystem Functioning
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Social Sciences
                Economics
                Development Economics
                Economic Development
                Ecology and Environmental Sciences
                Conservation Science
                Biology and Life Sciences
                Ecology
                Plant Ecology
                Plant Communities
                Grasslands
                Ecology and Environmental Sciences
                Ecology
                Plant Ecology
                Plant Communities
                Grasslands
                Biology and Life Sciences
                Plant Science
                Plant Ecology
                Plant Communities
                Grasslands
                Ecology and Environmental Sciences
                Terrestrial Environments
                Grasslands
                Custom metadata
                All spatial files are available from the Resource and Environment Data of Cloud Platform, CAS (DOIs: 10.12078/2018060503, 10.12078/2017121102, 10.12078/2017121101, 10.12078/2018060601).

                Uncategorized

                Comments

                Comment on this article