标题: A graph autoencoder network to measure the geometric similarity of drainage networks in scaling transformation

作者: Yu, HF (Yu, Huafei); Ai, TH (Ai, Tinghua); Yang, M (Yang, Min); Huang, WM (Huang, Weiming); Harrie, L (Harrie, Lars)

来源出版物: INTERNATIONAL JOURNAL OF DIGITAL EARTH 卷: 16 期: 1 页: 1828-1852 DOI: 10.1080/17538947.2023.2212920 出版年: DEC 31 2023

摘要: Similarity measurement has been a prevailing research topic in geographic information science. Geometric similarity measurement in scaling transformation (GSM_ST) is critical to ensure spatial data quality while balancing detailed information with distinctive features. However, GSM_ST is an uncertain problem due to subjective spatial cognition, global and local concerns, and geometric complexity. Traditional rule-based methods considering multiple consistent conditions require subjective adjustments to characteristics and weights, leading to poor robustness in addressing GSM_ST. This study proposes an unsupervised representation learning framework for automated GSM_ST, using a Graph Autoencoder Network (GAE) and drainage networks as an example. The framework involves constructing a drainage graph, designing the GAE architecture for GSM_ST, and using Cosine similarity to measure similarity based on the GAE-derived drainage embeddings in different scales. We perform extensive experiments and compare methods across 71 drainage networks during five scaling transformations. The results show that the proposed GAE method outperforms other methods with a satisfaction ratio of around 88% and has strong robustness. Moreover, our proposed method also can be applied to other scenarios, such as measuring similarity between geographical entities at different times and data from different datasets.

作者关键词: Geometric similarity measurement; drainage network; scaling transformation; graph autoencoder network

地址: [Yu, Huafei; Ai, Tinghua; Yang, Min] Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.

[Yu, Huafei; Harrie, Lars] Lund Univ, Dept Phys Geog & Ecosyst Sci, Lund, Sweden.

[Huang, Weiming] Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore, Singapore.

通讯作者地址: Ai, TH (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.

电子邮件地址: tinghuaai@whu.edu.cn

影响因子：4.606