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Measuring surface roughness of agricultural soils: Measurement error evaluation and random component

本站小编 Free考研考试/2021-12-12

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论文题目: Measuring surface roughness of agricultural soils: Measurement error evaluation and random components separation
英文论文题目: Measuring surface roughness of agricultural soils: Measurement error evaluation and random components separation
第一作者: 郑兴明
英文第一作者: X. M. Zheng
联系作者: 郑兴明
英文联系作者: X. M. Zheng
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发表年度: 2021
卷: 404
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英文摘要: Soil surface roughness (SSR) is an important parameter for predicting soil erosion, modeling reflectivity in the optical and microwave bands, and estimating soil infiltration capacity. Influenced by the interactions of soil properties, human activities, and natural factors, the anisotropy and scale dependence of SSR make it difficult to obtain high precision measurement results. To quantify its measurement error and investigate its scale characteristics, six selected soil surfaces, each approximately 30 m x 30 m, with different roughness were scanned by the LiDAR (Light Detect and Ranging) technology. Their digital elevation models (DEM) at 1 cm spatial resolution was generated from scanned point cloud data. According to the random sampling theory and the spatial filtering method, the following results were obtained: 1) The root mean squared height (RMSH) of the six surfaces ranged between 2.08 and 5.2 cm, and an exponential function was more suitable to represent the spatial correlation of natural farmland surface; 2) SSR measurement error demonstrated 6 m segment length (L) and 20 repeated observations could obtain 80% accuracy for ridge structure soil surface. Non-ridge structure surfaces need shorter L (3 m) for the same SSR measurement accuracy compared with ridge structure surfaces; 3) The filter window size determination method based on correlation length (CL) could automatically estimate the random component of SSR, and a weakened anisotropy for the filtered SSR was found after filtering. The results of this study are beneficial to the determination of SSR measurement accuracy and the application of SSR in agriculture and remote sensing fields.
刊物名称: Geoderma
英文刊物名称: Geoderma
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参与作者: X. M. Zheng, L. Li, C. M. Wang, L. R. Han, T. Jiang, X. J. Li, X. F. Li, F. R. Liu, B. Z. Li and Z. Z. Feng
英文参与作者: X. M. Zheng, L. Li, C. M. Wang, L. R. Han, T. Jiang, X. J. Li, X. F. Li, F. R. Liu, B. Z. Li and Z. Z. Feng
相关话题/Measuring surface roughness