Feature Recognition of Urban Industrial Land Renewal Based on POI and RS Data: The Case of Beijing
Urban renewal has increasingly become a hot topic in international urban sustainable development management, and many countries have also carried out a lot of practice. However, there is still a lack of fast and effective methods for how quickly identifying the spatial characteristics of urban renew...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-05-01
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| Series: | Frontiers in Environmental Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2022.890571/full |
| _version_ | 1811252040190394368 |
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| author | Ruirui Liu Huafu Zhao Huafu Zhao Chun Yang Hongyi Yang |
| author_facet | Ruirui Liu Huafu Zhao Huafu Zhao Chun Yang Hongyi Yang |
| author_sort | Ruirui Liu |
| collection | DOAJ |
| description | Urban renewal has increasingly become a hot topic in international urban sustainable development management, and many countries have also carried out a lot of practice. However, there is still a lack of fast and effective methods for how quickly identifying the spatial characteristics of urban renewal to dynamically grasp the renewal effect. The purpose of this study is to identify the renewal characteristics of urban industrial land based on the POI (Points of Interest) data and RS data of the Internet map, and to provide an innovative method for better understanding the renewal effect of urban industrial land and its spatiotemporal evolution characteristics. The results show that: 1) Since the decentralization of non-capital functions in Beijing, industrial development has spread from a high degree of agglomeration to the whole area. The number of high-density areas has decreased from nine to five, and the number of medium-density areas has increased significantly.2) Land-use types in the six districts of Beijing have changed, warehousing and logistics land and industrial land have been reduced greatly, and the number and area of park green space have greatly increased.3) The level of matching between RS image interpretation and POI data is uneven. RS interpretation is accurate for large-scale feature recognition, and POI data are sensitive to small-scale industries. In conclusion, In the process of identifying the renewal feature of urban industrial land, POI and RS data can respectively obtain certain results. The integration of POI and RS can better identify the temporal and spatial changes of the industry. |
| first_indexed | 2024-04-12T16:28:58Z |
| format | Article |
| id | doaj.art-159be95e11a8443fa3db3e89cd3155cd |
| institution | Directory Open Access Journal |
| issn | 2296-665X |
| language | English |
| last_indexed | 2024-04-12T16:28:58Z |
| publishDate | 2022-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Environmental Science |
| spelling | doaj.art-159be95e11a8443fa3db3e89cd3155cd2022-12-22T03:25:15ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2022-05-011010.3389/fenvs.2022.890571890571Feature Recognition of Urban Industrial Land Renewal Based on POI and RS Data: The Case of BeijingRuirui Liu0Huafu Zhao1Huafu Zhao2Chun Yang3Hongyi Yang4School of Land Science and Technology, China University of Geosciences Beijing, Beijing, ChinaSchool of Land Science and Technology, China University of Geosciences Beijing, Beijing, ChinaKey Laboratory of Consolidation and Rehabilitation Ministry of Natural Resources, Beijing, ChinaSchool of Land Science and Technology, China University of Geosciences Beijing, Beijing, ChinaSchool of Land Science and Technology, China University of Geosciences Beijing, Beijing, ChinaUrban renewal has increasingly become a hot topic in international urban sustainable development management, and many countries have also carried out a lot of practice. However, there is still a lack of fast and effective methods for how quickly identifying the spatial characteristics of urban renewal to dynamically grasp the renewal effect. The purpose of this study is to identify the renewal characteristics of urban industrial land based on the POI (Points of Interest) data and RS data of the Internet map, and to provide an innovative method for better understanding the renewal effect of urban industrial land and its spatiotemporal evolution characteristics. The results show that: 1) Since the decentralization of non-capital functions in Beijing, industrial development has spread from a high degree of agglomeration to the whole area. The number of high-density areas has decreased from nine to five, and the number of medium-density areas has increased significantly.2) Land-use types in the six districts of Beijing have changed, warehousing and logistics land and industrial land have been reduced greatly, and the number and area of park green space have greatly increased.3) The level of matching between RS image interpretation and POI data is uneven. RS interpretation is accurate for large-scale feature recognition, and POI data are sensitive to small-scale industries. In conclusion, In the process of identifying the renewal feature of urban industrial land, POI and RS data can respectively obtain certain results. The integration of POI and RS can better identify the temporal and spatial changes of the industry.https://www.frontiersin.org/articles/10.3389/fenvs.2022.890571/fullnon-capital function decentralizationindustrial decentralizationRS interpretationPOIconstruction land extractionurban renewal |
| spellingShingle | Ruirui Liu Huafu Zhao Huafu Zhao Chun Yang Hongyi Yang Feature Recognition of Urban Industrial Land Renewal Based on POI and RS Data: The Case of Beijing Frontiers in Environmental Science non-capital function decentralization industrial decentralization RS interpretation POI construction land extraction urban renewal |
| title | Feature Recognition of Urban Industrial Land Renewal Based on POI and RS Data: The Case of Beijing |
| title_full | Feature Recognition of Urban Industrial Land Renewal Based on POI and RS Data: The Case of Beijing |
| title_fullStr | Feature Recognition of Urban Industrial Land Renewal Based on POI and RS Data: The Case of Beijing |
| title_full_unstemmed | Feature Recognition of Urban Industrial Land Renewal Based on POI and RS Data: The Case of Beijing |
| title_short | Feature Recognition of Urban Industrial Land Renewal Based on POI and RS Data: The Case of Beijing |
| title_sort | feature recognition of urban industrial land renewal based on poi and rs data the case of beijing |
| topic | non-capital function decentralization industrial decentralization RS interpretation POI construction land extraction urban renewal |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2022.890571/full |
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