首页|Analysis of morphological characteristics of gravels based on digital image processing technology and self-organizing map

Analysis of morphological characteristics of gravels based on digital image processing technology and self-organizing map

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
  • 维普
A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring. However, traditional methods for studying gravels are low-efficiency and have many errors. This study researched the spatial distribution and cluster characteristics of gravels based on digital image processing technology combined with a self-organizing map (SOM) and multivariate statistical methods in the grassland of northern Tibetan Plateau. Moreover, the correlation of morphological parameters of gravels between different cluster groups and the environmental factors affecting gravel distribution were analyzed. The results showed that the morphological characteristics of gravels in northern region (cluster C) and southern region (cluster B) of the Tibetan Plateau were similar, with a low gravel coverage, small gravel diameter, and elongated shape. These regions were mainly distributed in high mountainous areas with large topographic relief. The central region (cluster A) has high coverage of gravels with a larger diameter, mainly distributed in high-altitude plains with smaller undulation. Principal component analysis (PCA) results showed that the gravel distribution of cluster A may be mainly affected by vegetation, while those in clusters B and C could be mainly affected by topography, climate, and soil. The study confirmed that the combination of digital image processing technology and SOM could effectively analyzed the spatial distribution characteristics of gravels, providing a new mode for gravel research.

self-organizing mapdigital image processingmorphological characteristicsmultivariate statistical methodenvironmental monitoring

XU Tao、YU Huan、QIU Xia、KONG Bo、XIANG Qing、XU Xiaoyu、FU Hao

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College of Earth Science,Chengdu University of Technology,Chengdu 610059,China

Beijing SuperMap Software Co.,Ltd.,Beijing 100015,China

Sichuan Real Estate Registration Center,Chengdu 610014,China

Chengdu Institute of Mountain Land and Disasters,Chinese Academy of Sciences,Chengdu 610041,China

School of Earth Systems and Sustainability,Southern Illinois University Carbondale,Carbondale,IL 62901,United States of America

Environmental Resources and Policy,Southern Illinois University Carbondale,Carbondale,IL 62901,United States of America

Sichuan Institute of Land and Space Ecological Restoration and Geohazard Prevention,Chengdu 610081,China

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National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaMajor Research and Development and Achievement Transformation Projects of Qinghai,ChinaStrategic Priority Research Program of the Chinese Academy of SciencesStrategic Priority Research Program of the Chinese Academy of Sciences

41971226418713572022-QY-224XDA28110502XDA19030303

2023

干旱区科学
中国科学院新疆生态与地理研究所,科学出版社

干旱区科学

CSTPCDCSCD北大核心
影响因子：1.743
ISSN：1674-6767
年,卷(期)：2023.15(3)
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