Evaluating the suitability of urban development land with a Geodetector
Ensuring the suitability of urban development land is essential for delineating spatial growth boundaries and urban spatial layouts. However, the significant impact of subjective uncertainty on the suitability evaluation process significantly reduces the reliability of the evaluation results. Thus,...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-04-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X21000042 |
| _version_ | 1828976221799579648 |
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| author | Haiying Wang Fen Qin Chengdong Xu Bin Li Linping Guo Zhe Wang |
| author_facet | Haiying Wang Fen Qin Chengdong Xu Bin Li Linping Guo Zhe Wang |
| author_sort | Haiying Wang |
| collection | DOAJ |
| description | Ensuring the suitability of urban development land is essential for delineating spatial growth boundaries and urban spatial layouts. However, the significant impact of subjective uncertainty on the suitability evaluation process significantly reduces the reliability of the evaluation results. Thus, in this study, we developed a new method to address this issue and improve the accuracy of the evaluation results. Zhengzhou in China was considered as the research area and the data utilized were obtained from the following primary sources: Landsat TM/ETM/OLI image data, land use data, digital elevation model data, spatial primary geographical data, and digital map data. A new method for evaluating the suitability of urban development land was developed by combining logistic regression, principal component analysis, kriging interpolation, K-means, and the Geodetector method to evaluate and classify the suitability of urban development land in Zhengzhou City during 2013. By using logistic regression, we could accurately evaluate the effects of a single factor, thereby avoiding subjective assessments. The principal component can be used to reduce the dimensions of the evaluation results for a single factor where the weight of the principal component is determined by using the cumulative contribution rate in order to obtain the comprehensive evaluation result. Kriging interpolation can be used to predict the evaluation results for the grid surface by using the principal component to comprehensively evaluate the sample points. K-means can be used to automatically classify the evaluation results for the grid surface. Geodetector was used to detect the spatial differentiation of the results in order to confirm the validity of the spatial partition results. These methods can avoid interference due to human factors and yield more objective and accurate evaluation results. The results indicated that the proposed evaluation method can avoid the subjective influence of the evaluation index classification and the determination of the index weight to obtain extremely accurate evaluations and high effectiveness. The suitability grading and evaluation values were highly consistent with the spatial pattern, thereby demonstrating the applicability of the evaluation results. The method and evaluation results may provide a scientific reference to support decisions regarding land resource allocation during urban development. |
| first_indexed | 2024-12-14T14:32:59Z |
| format | Article |
| id | doaj.art-9206ea1c8b314f9da4db43a904c697b7 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-12-14T14:32:59Z |
| publishDate | 2021-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-9206ea1c8b314f9da4db43a904c697b72022-12-21T22:57:44ZengElsevierEcological Indicators1470-160X2021-04-01123107339Evaluating the suitability of urban development land with a GeodetectorHaiying Wang0Fen Qin1Chengdong Xu2Bin Li3Linping Guo4Zhe Wang5College of Environment and Planning, Henan University, Kaifeng 475004, China; Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions(Henan University), Ministry of Education, Kaifeng 475004, China; Institute of Urban Big Data, Henan University, Kaifeng 475004, ChinaCollege of Environment and Planning, Henan University, Kaifeng 475004, China; Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions(Henan University), Ministry of Education, Kaifeng 475004, China; Collaborative Innovation Center of Yellow River Civilization, Henan University, Kaifeng 475001, China; Institute of Urban Big Data, Henan University, Kaifeng 475004, ChinaState Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, ChinaCollege of Environment and Planning, Henan University, Kaifeng 475004, China; Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions(Henan University), Ministry of Education, Kaifeng 475004, China; Corresponding author at: College of Environment and Planning, Henan University, Kaifeng 475004, China.Collaborative Innovation Center of Yellow River Civilization, Henan University, Kaifeng 475001, ChinaCollege of Environment and Planning, Henan University, Kaifeng 475004, ChinaEnsuring the suitability of urban development land is essential for delineating spatial growth boundaries and urban spatial layouts. However, the significant impact of subjective uncertainty on the suitability evaluation process significantly reduces the reliability of the evaluation results. Thus, in this study, we developed a new method to address this issue and improve the accuracy of the evaluation results. Zhengzhou in China was considered as the research area and the data utilized were obtained from the following primary sources: Landsat TM/ETM/OLI image data, land use data, digital elevation model data, spatial primary geographical data, and digital map data. A new method for evaluating the suitability of urban development land was developed by combining logistic regression, principal component analysis, kriging interpolation, K-means, and the Geodetector method to evaluate and classify the suitability of urban development land in Zhengzhou City during 2013. By using logistic regression, we could accurately evaluate the effects of a single factor, thereby avoiding subjective assessments. The principal component can be used to reduce the dimensions of the evaluation results for a single factor where the weight of the principal component is determined by using the cumulative contribution rate in order to obtain the comprehensive evaluation result. Kriging interpolation can be used to predict the evaluation results for the grid surface by using the principal component to comprehensively evaluate the sample points. K-means can be used to automatically classify the evaluation results for the grid surface. Geodetector was used to detect the spatial differentiation of the results in order to confirm the validity of the spatial partition results. These methods can avoid interference due to human factors and yield more objective and accurate evaluation results. The results indicated that the proposed evaluation method can avoid the subjective influence of the evaluation index classification and the determination of the index weight to obtain extremely accurate evaluations and high effectiveness. The suitability grading and evaluation values were highly consistent with the spatial pattern, thereby demonstrating the applicability of the evaluation results. The method and evaluation results may provide a scientific reference to support decisions regarding land resource allocation during urban development.http://www.sciencedirect.com/science/article/pii/S1470160X21000042GeodetectorK-means clusteringLogistic regressionPrincipal component analysisSuitability evaluationUrban development land |
| spellingShingle | Haiying Wang Fen Qin Chengdong Xu Bin Li Linping Guo Zhe Wang Evaluating the suitability of urban development land with a Geodetector Ecological Indicators Geodetector K-means clustering Logistic regression Principal component analysis Suitability evaluation Urban development land |
| title | Evaluating the suitability of urban development land with a Geodetector |
| title_full | Evaluating the suitability of urban development land with a Geodetector |
| title_fullStr | Evaluating the suitability of urban development land with a Geodetector |
| title_full_unstemmed | Evaluating the suitability of urban development land with a Geodetector |
| title_short | Evaluating the suitability of urban development land with a Geodetector |
| title_sort | evaluating the suitability of urban development land with a geodetector |
| topic | Geodetector K-means clustering Logistic regression Principal component analysis Suitability evaluation Urban development land |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X21000042 |
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