Multiscale Geoscene Segmentation for Extracting Urban Functional Zones from VHR Satellite Images
Urban functional zones, such as commercial, residential, and industrial zones, are basic units of urban planning, and play an important role in monitoring urbanization. However, historical functional-zone maps are rarely available for cities in developing countries, as traditional urban investigatio...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-02-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2072-4292/10/2/281 |
| _version_ | 1798025964800704512 |
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| author | Xiuyuan Zhang Shihong Du Qiao Wang Weiqi Zhou |
| author_facet | Xiuyuan Zhang Shihong Du Qiao Wang Weiqi Zhou |
| author_sort | Xiuyuan Zhang |
| collection | DOAJ |
| description | Urban functional zones, such as commercial, residential, and industrial zones, are basic units of urban planning, and play an important role in monitoring urbanization. However, historical functional-zone maps are rarely available for cities in developing countries, as traditional urban investigations focus on geographic objects rather than functional zones. Recent studies have sought to extract functional zones automatically from very-high-resolution (VHR) satellite images, and they mainly concentrate on classification techniques, but ignore zone segmentation which delineates functional-zone boundaries and is fundamental to functional-zone analysis. To resolve the issue, this study presents a novel segmentation method, geoscene segmentation, which can identify functional zones at multiple scales by aggregating diverse urban objects considering their features and spatial patterns. In experiments, we applied this method to three Chinese cities—Beijing, Putian, and Zhuhai—and generated detailed functional-zone maps with diverse functional categories. These experimental results indicate our method effectively delineates urban functional zones with VHR imagery; different categories of functional zones extracted by using different scale parameters; and spatial patterns that are more important than the features of individual objects in extracting functional zones. Accordingly, the presented multiscale geoscene segmentation method is important for urban-functional-zone analysis, and can provide valuable data for city planners. |
| first_indexed | 2024-04-11T18:27:22Z |
| format | Article |
| id | doaj.art-399932c358e5433381f24abc1856cff7 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-11T18:27:22Z |
| publishDate | 2018-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-399932c358e5433381f24abc1856cff72022-12-22T04:09:35ZengMDPI AGRemote Sensing2072-42922018-02-0110228110.3390/rs10020281rs10020281Multiscale Geoscene Segmentation for Extracting Urban Functional Zones from VHR Satellite ImagesXiuyuan Zhang0Shihong Du1Qiao Wang2Weiqi Zhou3Institute of Remote Sensing and GIS, Peking University, Beijing 100871, ChinaInstitute of Remote Sensing and GIS, Peking University, Beijing 100871, ChinaSatellite Environment Center, Ministry of Environmental Protection, Beijing 100094, ChinaState Key Laboratory of Urban and Regional Ecology, Research center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, ChinaUrban functional zones, such as commercial, residential, and industrial zones, are basic units of urban planning, and play an important role in monitoring urbanization. However, historical functional-zone maps are rarely available for cities in developing countries, as traditional urban investigations focus on geographic objects rather than functional zones. Recent studies have sought to extract functional zones automatically from very-high-resolution (VHR) satellite images, and they mainly concentrate on classification techniques, but ignore zone segmentation which delineates functional-zone boundaries and is fundamental to functional-zone analysis. To resolve the issue, this study presents a novel segmentation method, geoscene segmentation, which can identify functional zones at multiple scales by aggregating diverse urban objects considering their features and spatial patterns. In experiments, we applied this method to three Chinese cities—Beijing, Putian, and Zhuhai—and generated detailed functional-zone maps with diverse functional categories. These experimental results indicate our method effectively delineates urban functional zones with VHR imagery; different categories of functional zones extracted by using different scale parameters; and spatial patterns that are more important than the features of individual objects in extracting functional zones. Accordingly, the presented multiscale geoscene segmentation method is important for urban-functional-zone analysis, and can provide valuable data for city planners.http://www.mdpi.com/2072-4292/10/2/281urban landscapefunctional zoneobject-based image analysismultiscale image segmentationVHR images |
| spellingShingle | Xiuyuan Zhang Shihong Du Qiao Wang Weiqi Zhou Multiscale Geoscene Segmentation for Extracting Urban Functional Zones from VHR Satellite Images Remote Sensing urban landscape functional zone object-based image analysis multiscale image segmentation VHR images |
| title | Multiscale Geoscene Segmentation for Extracting Urban Functional Zones from VHR Satellite Images |
| title_full | Multiscale Geoscene Segmentation for Extracting Urban Functional Zones from VHR Satellite Images |
| title_fullStr | Multiscale Geoscene Segmentation for Extracting Urban Functional Zones from VHR Satellite Images |
| title_full_unstemmed | Multiscale Geoscene Segmentation for Extracting Urban Functional Zones from VHR Satellite Images |
| title_short | Multiscale Geoscene Segmentation for Extracting Urban Functional Zones from VHR Satellite Images |
| title_sort | multiscale geoscene segmentation for extracting urban functional zones from vhr satellite images |
| topic | urban landscape functional zone object-based image analysis multiscale image segmentation VHR images |
| url | http://www.mdpi.com/2072-4292/10/2/281 |
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