• 论文 •

### Assessing Suitability of Rural Settlements Using an Improved Technique for Order Preference by Similarity to Ideal Solution

LIU Yanfang1,2, CUI Jiaxing1,2, KONG Xuesong1,2, ZENG Chen3

1. 1. School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China;
2. Key Laboratory of GIS, Ministry of Edu-cation, Wuhan University, Wuhan 430079, China;
3. College of Land Administration, Huazhong Agricultural University, Wuhan 430070, China
• 收稿日期:2015-06-29 修回日期:2015-10-16 出版日期:2016-10-27 发布日期:2016-08-25
• 通讯作者: CUI Jiaxing.E-mail:cuijiaxing@whu.edu.cn E-mail:cuijiaxing@whu.edu.cn
• 基金资助:

Under the auspices of National Natural Science Foundation of China (No. 41371429, 41401196)

### Assessing Suitability of Rural Settlements Using an Improved Technique for Order Preference by Similarity to Ideal Solution

LIU Yanfang1,2, CUI Jiaxing1,2, KONG Xuesong1,2, ZENG Chen3

1. 1. School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China;
2. Key Laboratory of GIS, Ministry of Edu-cation, Wuhan University, Wuhan 430079, China;
3. College of Land Administration, Huazhong Agricultural University, Wuhan 430070, China
• Received:2015-06-29 Revised:2015-10-16 Online:2016-10-27 Published:2016-08-25
• Contact: CUI Jiaxing.E-mail:cuijiaxing@whu.edu.cn E-mail:cuijiaxing@whu.edu.cn
• Supported by:

Under the auspices of National Natural Science Foundation of China (No. 41371429, 41401196)

Land suitability assessment is a prerequisite phase in land use planning; it guides toward optimal land use by providing information on the opportunities and constraints involved in the use of a given land area. A geographic information system-based procedure, known as rural settlement suitability evaluation (RSSE) using an improved technique for order preference by similarity to ideal solution (TOPSIS), was adopted to determine the most suitable area for constructing rural settlements in different geographical locations. Given the distribution and independence of rural settlements, a distinctive evaluation criteria system that differed from that of urban suitability was established by considering the level of rural infrastructure services as well as living and working conditions. The unpredictable mutual interference among evaluation factors has been found in practical works. An improved TOPSIS using Mahalanobis distance was applied to solve the unpredictable correlation among the criteria in a suitability evaluation. Uncertainty and sensitivity analyses obtained via Monte Carlo simulation were performed to examine the robustness of the model. Daye, a resource-based city with rapid economic development, unsatisfied rural development, and geological environmental problems caused by mining, was used as a case study. Results indicate the following findings: 1) The RSSE model using the improved TOPSIS can assess the suitability of rural settlements, and the suitability maps generated using the improved TOPSIS have higher information density than those generated using traditional TOPSIS. The robustness of the model is improved, and the uncertainty is reduced in the suitability results. 2) Highly suitable land is mainly distributed in the northeast of the study area, and the majority of which is cultivated land, thereby leading to tremendous pressure on the loss of cultivated land. 3) Lastly, 12.54% of the constructive expansion permitted zone and 8.36% of the constructive expansion conditionally permitted zone are situated in an unsuitable area, which indicates that the general planning of Daye lacks the necessary verification of suitability evaluation. Guidance is provided on the development strategy of rural settlement patches to support decision making in general land use planning.

Abstract:

Land suitability assessment is a prerequisite phase in land use planning; it guides toward optimal land use by providing information on the opportunities and constraints involved in the use of a given land area. A geographic information system-based procedure, known as rural settlement suitability evaluation (RSSE) using an improved technique for order preference by similarity to ideal solution (TOPSIS), was adopted to determine the most suitable area for constructing rural settlements in different geographical locations. Given the distribution and independence of rural settlements, a distinctive evaluation criteria system that differed from that of urban suitability was established by considering the level of rural infrastructure services as well as living and working conditions. The unpredictable mutual interference among evaluation factors has been found in practical works. An improved TOPSIS using Mahalanobis distance was applied to solve the unpredictable correlation among the criteria in a suitability evaluation. Uncertainty and sensitivity analyses obtained via Monte Carlo simulation were performed to examine the robustness of the model. Daye, a resource-based city with rapid economic development, unsatisfied rural development, and geological environmental problems caused by mining, was used as a case study. Results indicate the following findings: 1) The RSSE model using the improved TOPSIS can assess the suitability of rural settlements, and the suitability maps generated using the improved TOPSIS have higher information density than those generated using traditional TOPSIS. The robustness of the model is improved, and the uncertainty is reduced in the suitability results. 2) Highly suitable land is mainly distributed in the northeast of the study area, and the majority of which is cultivated land, thereby leading to tremendous pressure on the loss of cultivated land. 3) Lastly, 12.54% of the constructive expansion permitted zone and 8.36% of the constructive expansion conditionally permitted zone are situated in an unsuitable area, which indicates that the general planning of Daye lacks the necessary verification of suitability evaluation. Guidance is provided on the development strategy of rural settlement patches to support decision making in general land use planning.