表面光洁度
表面粗糙度
耕作
分形
土壤科学
分形维数
环境科学
遥感
分形分析
渗透(HVAC)
土壤质地
土壤水分
地质学
材料科学
数学
地理
气象学
数学分析
生态学
复合材料
生物
作者
Kamal Marandskiy,Mihai Ivanovici
标识
DOI:10.1109/isscs58449.2023.10190895
摘要
Irregularities of soil are defined by the term soil surface roughness and various factors affect it such as tillage operations, land management, soil texture, etc. Soil roughness impacts water infiltration and surface storage level, as well as wind and water erosion. We used two classical methods for soil roughness estimation based on chain and pinboard and tested their effectiveness in lab and in situ measurements. However, we concluded that even though these two methods are perfectly correlated when they are aligned on the same line over the sample surface, in-field results showed the opposite. Thus, we propose a new soil surface roughness measurement method based on fractal analysis of digital images of the soil surface, acquired using a camera obscura-based technique. We show that the 2D fractal analysis gives more pertinent results compared to the other methods designed for 1D measurements.
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