Article ; Online: Fine-grained urban blue-green-gray landscape dataset for 36 Chinese cities based on deep learning network.
2024 Volume 11, Issue 1, Page(s) 266
Abstract: Detailed and accurate urban landscape mapping, especially for urban blue-green-gray (UBGG) continuum, is the fundamental first step to understanding human-nature coupled urban systems. Nevertheless, the intricate spatial heterogeneity of urban landscapes ...
Abstract | Detailed and accurate urban landscape mapping, especially for urban blue-green-gray (UBGG) continuum, is the fundamental first step to understanding human-nature coupled urban systems. Nevertheless, the intricate spatial heterogeneity of urban landscapes within cities and across urban agglomerations presents challenges for large-scale and fine-grained mapping. In this study, we generated a 3 m high-resolution UBGG landscape dataset (UBGG-3m) for 36 Chinese metropolises using a transferable multi-scale high-resolution convolutional neural network and 336 Planet images. To train the network for generalization, we also created a large-volume UBGG landscape sample dataset (UBGGset) covering 2,272 km |
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Language | English |
Publishing date | 2024-03-04 |
Publishing country | England |
Document type | Dataset ; Journal Article |
ZDB-ID | 2775191-0 |
ISSN | 2052-4463 ; 2052-4463 |
ISSN (online) | 2052-4463 |
ISSN | 2052-4463 |
DOI | 10.1038/s41597-023-02844-2 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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