An urban-rural Fringe extraction method based on Combined Urban-rural Fringe Index (CUFI)
In this article, a multi-source data-based method for urban-rural fringe extraction is proposed to solve the problem of insufficiently accurate division of urban-rural fringe, which can conveniently and accurately realise the extraction of the area of urban-rural fringe. The method uses multi-source...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-01-01
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| Series: | Geocarto International |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10106049.2024.2311211 |
| _version_ | 1826938996405567488 |
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| author | Hongrui Duan Fuguang Du Yajing Zhang Xiaojun Jiang Bo Chen |
| author_facet | Hongrui Duan Fuguang Du Yajing Zhang Xiaojun Jiang Bo Chen |
| author_sort | Hongrui Duan |
| collection | DOAJ |
| description | In this article, a multi-source data-based method for urban-rural fringe extraction is proposed to solve the problem of insufficiently accurate division of urban-rural fringe, which can conveniently and accurately realise the extraction of the area of urban-rural fringe. The method uses multi-source data such as night light remote sensing images, POI data and high-resolution remote sensing images. We constructed the Combined Urban-Rural Fringe Index (CUFI) model based on the characteristics of NDVI and NTL, POI kernel density value points that change from the city centre to the surrounding area. The calculation of CUFI involves three aspects. The initial step involves processing data, which includes reducing noise in nighttime light images and removing inaccurate information from POI data. The subsequent step involves calculating combined features of NTL and POI kernel density, which includes analyzing the kernel density of POI data, standardizing the results of POI kernel density and nighttime light data, computing NTL & POI indexes using the equal weight combined feature calculation method and reclassifying NTL & POI indexes .The third part involves rejecting misinformation using NDVI. This includes calculating the NDVI index using high-resolution satellite data, rejecting bare land information in the NDVI index using nighttime light data, and reclassifying the processed results. The reclassified results are then multiplied with the reclassification results of the NTL&POI index to obtain the CUFI calculation results. In order to verify the effectiveness and reliability of the method, Tangshan City, Hebei Province was selected as the experimental area, and the method was used to compare and analyse the accuracy with the traditional urban built-up area boundary extraction method. The results show that compared with the traditional method, the extraction accuracy of the CUFI method is higher, reaching 89.51%, which is able to effectively identify urban villages and lakes in the urban area, as well as improving the resolution of extracting Urban-Rural Fringe using NTL& POI methods, and also the urban-rural fringe which has weak night light and fewer POI points, but actually has urban-rural duality attributes Extraction. |
| first_indexed | 2024-03-07T21:18:53Z |
| format | Article |
| id | doaj.art-7aec8e60dfcf49789447b72c54dbc1fd |
| institution | Directory Open Access Journal |
| issn | 1010-6049 1752-0762 |
| language | English |
| last_indexed | 2025-02-17T19:07:21Z |
| publishDate | 2024-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geocarto International |
| spelling | doaj.art-7aec8e60dfcf49789447b72c54dbc1fd2024-12-10T08:23:09ZengTaylor & Francis GroupGeocarto International1010-60491752-07622024-01-0139110.1080/10106049.2024.2311211An urban-rural Fringe extraction method based on Combined Urban-rural Fringe Index (CUFI)Hongrui Duan0Fuguang Du1Yajing Zhang2Xiaojun Jiang3Bo Chen4Department of Resource Management, Tangshan Normal University, Tangshan, ChinaDepartment of Resource Management, Tangshan Normal University, Tangshan, ChinaDepartment of Resource Management, Tangshan Normal University, Tangshan, ChinaDepartment of Resource Management, Tangshan Normal University, Tangshan, ChinaSchool of Geographic Information and Tourism, Chuzhou University, Chuzhou, ChinaIn this article, a multi-source data-based method for urban-rural fringe extraction is proposed to solve the problem of insufficiently accurate division of urban-rural fringe, which can conveniently and accurately realise the extraction of the area of urban-rural fringe. The method uses multi-source data such as night light remote sensing images, POI data and high-resolution remote sensing images. We constructed the Combined Urban-Rural Fringe Index (CUFI) model based on the characteristics of NDVI and NTL, POI kernel density value points that change from the city centre to the surrounding area. The calculation of CUFI involves three aspects. The initial step involves processing data, which includes reducing noise in nighttime light images and removing inaccurate information from POI data. The subsequent step involves calculating combined features of NTL and POI kernel density, which includes analyzing the kernel density of POI data, standardizing the results of POI kernel density and nighttime light data, computing NTL & POI indexes using the equal weight combined feature calculation method and reclassifying NTL & POI indexes .The third part involves rejecting misinformation using NDVI. This includes calculating the NDVI index using high-resolution satellite data, rejecting bare land information in the NDVI index using nighttime light data, and reclassifying the processed results. The reclassified results are then multiplied with the reclassification results of the NTL&POI index to obtain the CUFI calculation results. In order to verify the effectiveness and reliability of the method, Tangshan City, Hebei Province was selected as the experimental area, and the method was used to compare and analyse the accuracy with the traditional urban built-up area boundary extraction method. The results show that compared with the traditional method, the extraction accuracy of the CUFI method is higher, reaching 89.51%, which is able to effectively identify urban villages and lakes in the urban area, as well as improving the resolution of extracting Urban-Rural Fringe using NTL& POI methods, and also the urban-rural fringe which has weak night light and fewer POI points, but actually has urban-rural duality attributes Extraction.https://www.tandfonline.com/doi/10.1080/10106049.2024.2311211CUFIurban-rural fringenighttime lighting dataPOITangshan city |
| spellingShingle | Hongrui Duan Fuguang Du Yajing Zhang Xiaojun Jiang Bo Chen An urban-rural Fringe extraction method based on Combined Urban-rural Fringe Index (CUFI) Geocarto International CUFI urban-rural fringe nighttime lighting data POI Tangshan city |
| title | An urban-rural Fringe extraction method based on Combined Urban-rural Fringe Index (CUFI) |
| title_full | An urban-rural Fringe extraction method based on Combined Urban-rural Fringe Index (CUFI) |
| title_fullStr | An urban-rural Fringe extraction method based on Combined Urban-rural Fringe Index (CUFI) |
| title_full_unstemmed | An urban-rural Fringe extraction method based on Combined Urban-rural Fringe Index (CUFI) |
| title_short | An urban-rural Fringe extraction method based on Combined Urban-rural Fringe Index (CUFI) |
| title_sort | urban rural fringe extraction method based on combined urban rural fringe index cufi |
| topic | CUFI urban-rural fringe nighttime lighting data POI Tangshan city |
| url | https://www.tandfonline.com/doi/10.1080/10106049.2024.2311211 |
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