基于二次平均状态的土地砾化程度监测评估研究
收稿日期: 2024-01-19
修回日期: 2024-05-09
网络出版日期: 2025-01-21
基金资助
内蒙古自治区科技计划项目(2020GG0092);内蒙古自治区科技计划项目(2021GG0307);内蒙古自治区气象局防灾减灾专项资助
Monitoring and evaluation of land gravel coverage based on secondary average state
Received date: 2024-01-19
Revised date: 2024-05-09
Online published: 2025-01-21
关键词: 砾化土地; 地表砾石覆盖度; 地表单位面积砾石质量; 二次平均状态; 仿生态学
叶虎 , 裴浩 , 苗百岭 , 姜艳丰 , 徐丽娜 , 贾成朕 . 基于二次平均状态的土地砾化程度监测评估研究[J]. 干旱区地理, 2025 , 48(1) : 85 -93 . DOI: 10.12118/j.issn.1000-6060.2024.045
To enhance the accuracy of monitoring and assessing surface gravel coverage throughout the sampling, measurement, and evaluation process, Alagxa League and Bayannur City in the western Inner Mongolian Plateau, China, were selected as the study area. Various sample sizes were designed, and research on the sampling method of the secondary average state was conducted. The optimal measurement method for small sample gravel coverage was determined by comparing the measurement disk method with the ground measurement method. The most suitable evaluation method for large sample gravel coverage was identified by analyzing the statistical characteristics of the average and median gravel coverage values in small samples. The same methodology was applied to evaluate the gravel coverage in sample plots. Additionally, the necessity and preliminary considerations for constructing imitative ecology are discussed. The results showed that: (1) The secondary average state method enhances sample representativeness through two pathways—reducing sample sizes while increasing sample quantities. Consequently, the size of the measurement disk is reduced, which further improves the accuracy of surface gravel coverage measurements. (2) Data dispersion decreases, and the characteristics of right-skewed and peaked distributions become more prominent progressively for small samples, large samples, and sample plots. This indicates that the overall characteristics of gravelized land in the study area become increasingly distinct. Gravel coverage is strongly correlated with the surface gravel mass per unit area, demonstrating that the secondary average state sampling yields highly accurate and stable results. These findings can significantly improve the procedures and accuracy of land gravelization measurement and enhance the efficiency of fieldwork.
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