标题: An enhanced method for estimating snow water equivalent in the central part of the Tibetan Plateau using raster segmentation and eigenvector spatial filtering regression model

作者: Cheng, QS (Cheng Qi-shan); Chen, YM (Chen Yu-min); Yang, JX (Yang Jia-xin); Chen, YJ (Chen Yue-jun); Xiong, ZX (Xiong Zhe-xin); Zhou, AN (Zhou An-nan)

来源出版物: JOURNAL OF MOUNTAIN SCIENCE卷: 19期: 9页: 2570-2586 DOI: 10.1007/s11629-022-7361-2出版年: SEP 2022

摘要: Snow water equivalent (SWE) is an important factor reflecting the variability of snow. It is important to estimate SWE based on remote sensing data while taking spatial autocorrelation into account. Based on the segmentation method, the relationship between SWE and environmental factors in the central part of the Tibetan Plateau was explored using the eigenvector spatial filtering (ESF) regression model, and the influence of different factors on the SWE was explored. Three sizes of 16 x 16, 24 x 24 and 32 x 32 were selected to segment raster datasets into blocks. The eigenvectors of the spatial adjacency matrix of the segmented size were selected to be added into the model as spatial factors, and the ESF regression model was constructed for each block in parallel. Results show that precipitation has a great influence on SWE, while surface temperature and NDVI have little influence. Air temperature, elevation and surface temperature have completely different effects in different areas. Compared with the ordinary least square (OLS) linear regression model, geographically weighted regression (GWR) model, spatial lag model (SLM) and spatial error model (SEM), ESF model can eliminate spatial autocorrelation with the highest accuracy. As the segmentation size increases, the complexity of ESF model increases, but the accuracy is improved.

作者关键词: Snow water equivalent; Tibetan Plateau; Raster segmentation; Parallel eigenvector spatial filtering

地址: [Cheng Qi-shan; Chen Yu-min; Yang Jia-xin; Chen Yue-jun; Xiong Zhe-xin; Zhou An-nan] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Cheng Qi-shan] Guangzhou Urban Planning & Design Survey Res Inst, Guangzhou 510060, Peoples R China.

通讯作者地址: Chen, YM (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

电子邮件地址: qishancheng@whu.edu.cn; ymchen@whu.edu.cn; yangjiaxin@whu.edu.cn; chenyuejun@whu.edu.cn; 2016301110034@whu.edu.cn;zhouannan2016@whu.edu.cn

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