Sensing the multi-scale landscape functions heterogeneity by big geodata from parcel to urban agglomerations-a case of the Greater Bay Area, China
文献类型：期刊论文
| 作者 | Gao, Ku1; Yang, Xiaomei1; Wang, Zhihua1,5,6; Lai, Feilin4; Zhang, Huifang1; Shi, Tiezhu2,3; Li, He1; Zhang, Qingyang1 |
| 刊名 | INTERNATIONAL JOURNAL OF DIGITAL EARTH
 |
| 出版日期 | 2023-12-31 |
| 卷号 | 17期号:1页码:2300317 |
| 关键词 | Big geodata Multi-scale Landscape functions Urban agglomerations GBA |
| DOI | 10.1080/17538947.2024.2304073 |
| 产权排序 | 1 |
| 英文摘要 | Multi-scale landscape functions play a critical role in revealing intricate functional structures within large regions. However, previous studies on landscape functions have predominantly focused on a single macro or micro scale, impeding a holistic multi-scale understanding of the spatial distribution and heterogeneity of landscape functions. To address this gap, this study proposes a framework leveraging the power of big geodata to mine multi-scale landscape functions from parcel to entire urban agglomerations, as well as non-administrative divisions. Our study focuses on the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China. Firstly, we integrated multi-source big geodata to derive parcel-scale landscape functions. Subsequently, we employed the Normalized Revealed Comparative Advantage index to derive landscape functions at broader scales, including towns, counties and cities. The effectiveness of our approach is validated through in-field investigations and comparisons with established policy planning positions. The outcomes not only offer distinctive planning insights at various scales but also highlight the versatility of big geodata in extracting landscape functions across scales. This study demonstrates that big geodata is adept at uncovering multi-scale landscape functions irrespective of administrative boundaries, providing valuable insights for fostering multi-scale regional coordinated development. |
| WOS关键词 | LAND-USE ; DECISION-MAKING ; METRICS ; REGION ; COVER ; OPENSTREETMAP ; EVOLUTION ; DYNAMICS ; POINTS ; SPRAWL |
| WOS研究方向 | Physical Geography ; Remote Sensing |
| WOS记录号 | WOS:001143836900001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/201656]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Shenzhen Univ, MNR Key Lab Geoenvironm Monitoring Great Bay Area, State Key Lab Subtrop Bldg & Urban Sci, Shenzhen, Peoples R China 4.Shenzhen Univ, Sch Architecture & Urban Planning, Guangdong Hong Kong Macau Joint Lab Smart Cities, Shenzhen, Peoples R China 5.St Cloud State Univ, Dept Geog & Land Surveying, St Cloud, MN USA 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 7.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Gao, Ku,Yang, Xiaomei,Wang, Zhihua,et al. Sensing the multi-scale landscape functions heterogeneity by big geodata from parcel to urban agglomerations-a case of the Greater Bay Area, China[J]. INTERNATIONAL JOURNAL OF DIGITAL EARTH,2023,17(1):2300317. |
| APA | Gao, Ku.,Yang, Xiaomei.,Wang, Zhihua.,Lai, Feilin.,Zhang, Huifang.,...&Zhang, Qingyang.(2023).Sensing the multi-scale landscape functions heterogeneity by big geodata from parcel to urban agglomerations-a case of the Greater Bay Area, China.INTERNATIONAL JOURNAL OF DIGITAL EARTH,17(1),2300317. |
| MLA | Gao, Ku,et al."Sensing the multi-scale landscape functions heterogeneity by big geodata from parcel to urban agglomerations-a case of the Greater Bay Area, China".INTERNATIONAL JOURNAL OF DIGITAL EARTH 17.1(2023):2300317. |
入库方式： OAI收割
来源：地理科学与资源研究所
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