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Zhao W, Ma J, Liu Q, Song J, Tysklind M, Liu C, Wang D, Qu Y, Wu Y, Wu F. Comparison and application of SOFM, fuzzy c-means and k-means clustering algorithms for natural soil environment regionalization in China. ENVIRONMENTAL RESEARCH 2023; 216:114519. [PMID: 36252833 DOI: 10.1016/j.envres.2022.114519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 09/28/2022] [Accepted: 10/04/2022] [Indexed: 06/16/2023]
Abstract
Soil attributes and their environmental drivers exhibit different patterns in different geographical directions, along with distinct regional characteristics, which may have important effects on substance migration and transformation such as organic matter and soil elements or the environmental impacts of pollutants. Therefore, regional soil characteristics should be considered in the process of regionalization for environmental management. However, no comprehensive evaluation or systematic classification of the natural soil environment has been established for China. Here, we established an index system for natural soil environmental regionalization (NSER) by combining literature data obtained based on bibliometrics with the analytic hierarchy process (AHP). Based on the index system, we collected spatial distribution data for 14 indexes at the national scale. In addition, three clustering algorithms-self-organizing feature mapping (SOFM), fuzzy c-means (FCM) and k-means (KM)-were used to classify and define the natural soil environment. We imported four cluster validity indexes (CVI) to evaluate different models: Davies-Bouldin index (DB), Silhouette index (Sil) and Calinski-Harabasz index (CH) for FCM and KM, clustering quality index (CQI) for SOFM. Analysis and comparison of the results showed that when the number of clusters was 13, the FCM clustering algorithm achieved the optimal clustering results (DB = 1.16, Sil = 0.78, CH = 6.77 × 106), allowing the natural soil environment of China to be divided into 12 regions with distinct characteristics. Our study provides a set of comprehensive scientific research methods for regionalization research based on spatial data, it has important reference value for improving soil environmental management based on local conditions in China.
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Affiliation(s)
- Wenhao Zhao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Jin Ma
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Qiyuan Liu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Jing Song
- State Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Mats Tysklind
- Department of Chemistry, Umeå University, Umeå, 90187, Sweden
| | - Chengshuai Liu
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, 550081, China
| | - Dong Wang
- Department of Chemistry, Umeå University, Umeå, 90187, Sweden
| | - Yajing Qu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Yihang Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Fengchang Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
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Shen W, Zhang L, Li S, Zhuang Y, Liu H, Pan J. A framework for evaluating county-level non-point source pollution: Joint use of monitoring and model assessment. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 722:137956. [PMID: 32208281 DOI: 10.1016/j.scitotenv.2020.137956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 03/13/2020] [Accepted: 03/13/2020] [Indexed: 06/10/2023]
Abstract
It is believed that non-point source (NPS) pollution threatens the regional environment. Because of the disconnection between the hydrological scale and the administrative scale of implementing feasible management policies in existing research, watershed-based management measures have limited application in current NPS control. In this study, a framework for county-level monitoring and evaluation is proposed, which contains a cascade monitoring scheme and an adaptable assessment scheme. The cascade monitoring scheme is based on the principle of "pollution source-transport pathways-receiving waters" layout method and the adaptable assessment scheme makes full use of monitoring data in the model. A set of processes was designed to monitor and assess county-level NPS pollution, from the initial step of county basic situation investigations to the final step of NPS pollution assessment. Two schemes are included in the process to improve the feasibility of the results. Here, the importance of the joint use of monitoring and simulation for environmental policy and management is stressed, and focus is on the characteristics of administrative boundaries. A case study involving Nanle County is presented, and a detailed layout scheme and the assessment results are given in this paper.
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Affiliation(s)
- Wangzheng Shen
- Hubei Provincial Engineering Research Center of Non-Point Source Pollution Control, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Liang Zhang
- Hubei Provincial Engineering Research Center of Non-Point Source Pollution Control, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China.
| | - Sisi Li
- Hubei Provincial Engineering Research Center of Non-Point Source Pollution Control, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China
| | - Yanhua Zhuang
- Hubei Provincial Engineering Research Center of Non-Point Source Pollution Control, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China
| | - Hongbin Liu
- Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, 100081 Beijing, China
| | - Junting Pan
- Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, 100081 Beijing, China
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Relevance Analysis of Sustainable Development of China's Yangtze River Economic Belt Based on Spatial Structure. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16173076. [PMID: 31450878 PMCID: PMC6747499 DOI: 10.3390/ijerph16173076] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/06/2019] [Revised: 08/05/2019] [Accepted: 08/09/2019] [Indexed: 11/17/2022]
Abstract
Scientifically justifiable spatial structure can not only promote the efficient use of regional resources, but can also effectively avoid “urban diseases”, such as traffic congestion, housing shortage, resource scarcity, and so on. It is the “regulator” and “booster” of regional development. Firstly, this paper measures the spatial structure of the Yangtze River Economic Belt from the four dimensions of scale distribution, central structure, spatial connection, and compactness: Gini coefficient of urban scale, urban primacy, regional economic linkage strength, and spatial compactness. Secondly, the optimized Super-Slack Based Measure-Undesirable model is used to evaluate the sustainable development status of the Yangtze River Economic Belt. Finally, a sustainable development correlation analysis model based on regional spatial structure is constructed. Based on the overall perspective of the Yangtze River Economic Belt and the individual perspective of 11 provinces and cities, the relationship between the spatial structure of the Yangtze River Economic Belt and sustainable development is analyzed. It is found that the impact of the four spatial structure indicators on the sustainable development level of the Yangtze River Economic Zone is relatively stable in five different periods. The ranking results are as follows: Gini coefficient of urban scale > urban primacy > regional economic linkage strength > spatial compactness.
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