Impact evaluation and driving type identification of human factors on rural human settlement environment: Taking Gansu Province, China as an example
Evaluating the quality of rural human (RH) settlements and clarifying its spatial differentiation characteristics have the most direct guiding role for the formulation of regional construction policies and the optimization of RH settlements. In this study, the index model of environmental quality of...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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De Gruyter
2020-11-01
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| Series: | Open Geosciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/geo-2020-0126 |
| _version_ | 1818587444046462976 |
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| author | Dou Haojian Ma Libang Li Huan Bo Jie Fang Fang |
| author_facet | Dou Haojian Ma Libang Li Huan Bo Jie Fang Fang |
| author_sort | Dou Haojian |
| collection | DOAJ |
| description | Evaluating the quality of rural human (RH) settlements and clarifying its spatial differentiation characteristics have the most direct guiding role for the formulation of regional construction policies and the optimization of RH settlements. In this study, the index model of environmental quality of RH settlement was established. ImPACT and trade-off analysis methods were used to quantitatively identify the spatial differentiation of RH settlement and dominant impact human factors of it in Gansu Province in 2017. Then, the driving type of RH settlement environment was identified. Results are as follows. (1) The overall environmental quality of RH settlement in Gansu Province shows a decreasing trend from “west to east.” (2) The environmental quality of RH settlement is mainly affected by eight factors, of which the effect of quantity index per capita is more significant. (3) The trade-off relationship between the environmental quality index and these eight dominant factors is mainly low–low, which indicates that the human factors are the main reason for the environmental quality of the RH settlement. (4) Based on the dominant human factors, Gansu Province is classified into four driving types, of which the proportion of comprehensive type accounts for 77.01%. |
| first_indexed | 2024-12-16T09:08:57Z |
| format | Article |
| id | doaj.art-25f8de5fdc714c48b2577d812de4878f |
| institution | Directory Open Access Journal |
| issn | 2391-5447 |
| language | English |
| last_indexed | 2024-12-16T09:08:57Z |
| publishDate | 2020-11-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Geosciences |
| spelling | doaj.art-25f8de5fdc714c48b2577d812de4878f2022-12-21T22:37:01ZengDe GruyterOpen Geosciences2391-54472020-11-011211324133710.1515/geo-2020-0126geo-2020-0126Impact evaluation and driving type identification of human factors on rural human settlement environment: Taking Gansu Province, China as an exampleDou Haojian0Ma Libang1Li Huan2Bo Jie3Fang Fang4College of Geography and Environmental Science, Northwest Normal University, Lanzhou, 730000, ChinaCollege of Geography and Environmental Science, Northwest Normal University, Lanzhou, 730000, ChinaCollege of Geography and Environmental Science, Northwest Normal University, Lanzhou, 730000, ChinaCollege of Geography and Environmental Science, Northwest Normal University, Lanzhou, 730000, ChinaCollege of Geography and Environmental Science, Northwest Normal University, Lanzhou, 730000, ChinaEvaluating the quality of rural human (RH) settlements and clarifying its spatial differentiation characteristics have the most direct guiding role for the formulation of regional construction policies and the optimization of RH settlements. In this study, the index model of environmental quality of RH settlement was established. ImPACT and trade-off analysis methods were used to quantitatively identify the spatial differentiation of RH settlement and dominant impact human factors of it in Gansu Province in 2017. Then, the driving type of RH settlement environment was identified. Results are as follows. (1) The overall environmental quality of RH settlement in Gansu Province shows a decreasing trend from “west to east.” (2) The environmental quality of RH settlement is mainly affected by eight factors, of which the effect of quantity index per capita is more significant. (3) The trade-off relationship between the environmental quality index and these eight dominant factors is mainly low–low, which indicates that the human factors are the main reason for the environmental quality of the RH settlement. (4) Based on the dominant human factors, Gansu Province is classified into four driving types, of which the proportion of comprehensive type accounts for 77.01%.https://doi.org/10.1515/geo-2020-0126driving type human factorsimpact evaluationrural human settlement environment |
| spellingShingle | Dou Haojian Ma Libang Li Huan Bo Jie Fang Fang Impact evaluation and driving type identification of human factors on rural human settlement environment: Taking Gansu Province, China as an example Open Geosciences driving type human factors impact evaluation rural human settlement environment |
| title | Impact evaluation and driving type identification of human factors on rural human settlement environment: Taking Gansu Province, China as an example |
| title_full | Impact evaluation and driving type identification of human factors on rural human settlement environment: Taking Gansu Province, China as an example |
| title_fullStr | Impact evaluation and driving type identification of human factors on rural human settlement environment: Taking Gansu Province, China as an example |
| title_full_unstemmed | Impact evaluation and driving type identification of human factors on rural human settlement environment: Taking Gansu Province, China as an example |
| title_short | Impact evaluation and driving type identification of human factors on rural human settlement environment: Taking Gansu Province, China as an example |
| title_sort | impact evaluation and driving type identification of human factors on rural human settlement environment taking gansu province china as an example |
| topic | driving type human factors impact evaluation rural human settlement environment |
| url | https://doi.org/10.1515/geo-2020-0126 |
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