Empirical Analysis of a Super-SBM-Based Framework for Wetland Carbon Stock Safety Assessment
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Published:2024-05-09
Issue:10
Volume:16
Page:1678
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ISSN:2072-4292
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Container-title:Remote Sensing
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language:en
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Short-container-title:Remote Sensing
Author:
Chen Lijie1, Wang Zhe2, Ma Xiaogang2ORCID, Zhao Jingwen13, Que Xiang12ORCID, Liu Jinfu34, Chen Ruohai5, Li Yimin5
Affiliation:
1. College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China 2. Department of Computer Science, University of Idaho, Moscow, ID 83844, USA 3. Key Laboratory of Ecology and Resources Statistics in Higher Education Institutes of Fujian Province, Fujian Agriculture and Forestry University, Fuzhou 350002, China 4. Technology Innovation Center for Monitoring and Restoration Engineering of Ecological Fragile Zone in Southeast China, Ministry of Natural Resources, Fuzhou 350001, China 5. Quanzhou Bay Estuary Wetland Nature Reserve Management Office, Quanzhou 350000, China
Abstract
With climate change and urbanization expansion, wetlands, which are some of the largest carbon stocks in the world, are facing threats such as shrinking areas and declining carbon sequestration capacities. Wetland carbon stocks are at risk of being transformed into carbon sources, especially those of wetlands with strong land use–natural resource conservation conflict. Moreover, there is a lack of well-established indicators for evaluating the health of wetland carbon stocks. To address this issue, we proposed a novel framework for the safety assessment of wetland carbon stocks using the Super Slack-Based Measure (Super-SBM), and we then conducted an empirical study on the Quanzhou Bay Estuary Wetland (QBEW). This framework integrates the unexpected output indicator (i.e., carbon emissions), the expected output indicators, including the GDP per capita and carbon stock estimates calculated via machine learning (ML)-based remote sensing inversion, and the input indicators, such as environmental governance investigations, climate conditions, socio-economic activities, and resource utilization. The results show that the annual average safety assessment for carbon pools in the QBEW was a meager 0.29 in 2015, signaling a very poor state, likely due to inadequate inputs or excessive unexpected outputs. However, there has been a substantial improvement since then, as evidenced by the fact that all the safety assessments have exceeded the threshold of 1 from 2018 onwards, reflecting a transition to a “weakly effective” status within a safe and acceptable range. Moreover, our investigation employing the Super-SBM model to calculate the “slack variables” yielded valuable insights into optimization strategies. This research advances the field by establishing a safety measurement framework for wetland carbon pools that leverages efficiency assessment methods, thereby offering a quantitative safeguard mechanism that supports the achievement of the “3060” dual-carbon target.
Funder
National Natural Science Foundation of China Natural Science Foundation of Fujian Province U.S. National Science Foundation Key Project of Scientific and Technological Innovation of Fujian Province Science and Technology Innovation Project of Fujian Agriculture and Forestry University
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