Spatial Analysis of Urban Historic Landscapes Based on Semiautomatic Point Cloud Classification with RandLA-Net Model—Taking the Ancient City of Fangzhou in Huangling County as an Example
Under the synergy of urban heritage conservation and regional cultural continuity, this study explores the spatial features of “mausoleum–city symbiosis” landscapes in Huangling County’s gully regions. Focusing on Fangzhou Ancient City, we address historical spatial degradation caused by excessive i...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Online Access: | https://www.mdpi.com/2073-445X/14/6/1156 |
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| author | Jiaxuan Wang Yixi Gu Xinyi Su Li Ran Kaili Zhang |
| author_facet | Jiaxuan Wang Yixi Gu Xinyi Su Li Ran Kaili Zhang |
| author_sort | Jiaxuan Wang |
| collection | DOAJ |
| description | Under the synergy of urban heritage conservation and regional cultural continuity, this study explores the spatial features of “mausoleum–city symbiosis” landscapes in Huangling County’s gully regions. Focusing on Fangzhou Ancient City, we address historical spatial degradation caused by excessive industrialization and disordered urban expansion. A methodological framework is proposed, combining low-altitude UAV-derived high-density point cloud data with RandLA-Net for semi-automatic semantic segmentation of buildings, vegetation, and roads by integrating multispectral and geometric attributes. Key findings reveal: (1) Modern buildings’ abnormal elevation in steep slopes disrupts the plateau–city visual corridor; (2) Statistical analysis shows significant morphological disparities between historical and modern streets; (3) Modern structures exceed traditional height limits, while divergent roof slopes aggravate aesthetic fragmentation. This multi-level spatial analysis offers a paradigm for quantifying historical urban spaces and validates deep learning’s feasibility in heritage spatial analytics, providing insights for balancing conservation and development in ecologically fragile areas. |
| format | Article |
| id | doaj-art-0484c6f226ac4e39831e124b8bbba027 |
| institution | Kabale University |
| issn | 2073-445X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj-art-0484c6f226ac4e39831e124b8bbba0272025-08-20T03:27:32ZengMDPI AGLand2073-445X2025-05-01146115610.3390/land14061156Spatial Analysis of Urban Historic Landscapes Based on Semiautomatic Point Cloud Classification with RandLA-Net Model—Taking the Ancient City of Fangzhou in Huangling County as an ExampleJiaxuan Wang0Yixi Gu1Xinyi Su2Li Ran3Kaili Zhang4School of Landscape Architecture, Beijing Forestry University, No. 35 Qinghua East Road, Haidian District, Beijing 100083, ChinaSchool of Landscape Architecture, Beijing Forestry University, No. 35 Qinghua East Road, Haidian District, Beijing 100083, ChinaSchool of Landscape Architecture, Beijing Forestry University, No. 35 Qinghua East Road, Haidian District, Beijing 100083, ChinaSchool of Landscape Architecture, Beijing Forestry University, No. 35 Qinghua East Road, Haidian District, Beijing 100083, ChinaSchool of Landscape Architecture, Beijing Forestry University, No. 35 Qinghua East Road, Haidian District, Beijing 100083, ChinaUnder the synergy of urban heritage conservation and regional cultural continuity, this study explores the spatial features of “mausoleum–city symbiosis” landscapes in Huangling County’s gully regions. Focusing on Fangzhou Ancient City, we address historical spatial degradation caused by excessive industrialization and disordered urban expansion. A methodological framework is proposed, combining low-altitude UAV-derived high-density point cloud data with RandLA-Net for semi-automatic semantic segmentation of buildings, vegetation, and roads by integrating multispectral and geometric attributes. Key findings reveal: (1) Modern buildings’ abnormal elevation in steep slopes disrupts the plateau–city visual corridor; (2) Statistical analysis shows significant morphological disparities between historical and modern streets; (3) Modern structures exceed traditional height limits, while divergent roof slopes aggravate aesthetic fragmentation. This multi-level spatial analysis offers a paradigm for quantifying historical urban spaces and validates deep learning’s feasibility in heritage spatial analytics, providing insights for balancing conservation and development in ecologically fragile areas.https://www.mdpi.com/2073-445X/14/6/1156historic urban landscapecultural heritage preservationRandLA-Netpoint cloud classificationthree-dimensional spatial analysis |
| spellingShingle | Jiaxuan Wang Yixi Gu Xinyi Su Li Ran Kaili Zhang Spatial Analysis of Urban Historic Landscapes Based on Semiautomatic Point Cloud Classification with RandLA-Net Model—Taking the Ancient City of Fangzhou in Huangling County as an Example Land historic urban landscape cultural heritage preservation RandLA-Net point cloud classification three-dimensional spatial analysis |
| title | Spatial Analysis of Urban Historic Landscapes Based on Semiautomatic Point Cloud Classification with RandLA-Net Model—Taking the Ancient City of Fangzhou in Huangling County as an Example |
| title_full | Spatial Analysis of Urban Historic Landscapes Based on Semiautomatic Point Cloud Classification with RandLA-Net Model—Taking the Ancient City of Fangzhou in Huangling County as an Example |
| title_fullStr | Spatial Analysis of Urban Historic Landscapes Based on Semiautomatic Point Cloud Classification with RandLA-Net Model—Taking the Ancient City of Fangzhou in Huangling County as an Example |
| title_full_unstemmed | Spatial Analysis of Urban Historic Landscapes Based on Semiautomatic Point Cloud Classification with RandLA-Net Model—Taking the Ancient City of Fangzhou in Huangling County as an Example |
| title_short | Spatial Analysis of Urban Historic Landscapes Based on Semiautomatic Point Cloud Classification with RandLA-Net Model—Taking the Ancient City of Fangzhou in Huangling County as an Example |
| title_sort | spatial analysis of urban historic landscapes based on semiautomatic point cloud classification with randla net model taking the ancient city of fangzhou in huangling county as an example |
| topic | historic urban landscape cultural heritage preservation RandLA-Net point cloud classification three-dimensional spatial analysis |
| url | https://www.mdpi.com/2073-445X/14/6/1156 |
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