Soil erosion in the agricultural area of a hill slope is a fundamental issue for crop productivity and environmental sustainability. Building terrace is a very popular way to control soil erosion, and accurate assessment of the soil erosion rate is important for sustainable agriculture and environmental management. Currently, many soil erosion estimations are mainly based on the freely available medium or coarse resolution digital elevation model (DEM) data that neglect micro topographic modification of the agriculture terraces. The development of unmanned aerial vehicle (UAV) technology enables the development of high-resolution (centimeter level) DEM to present accurate topographic features. To demonstrate the sensitivity of soil erosion estimates to DEM resolution at this high-resolution level, this study tries to evaluate soil erosion estimation in the Middle Hill agriculture terraces in Nepal based on UAV derived high-resolution (5 × 5 cm) DEM data and make a comparative study for the estimates by using the DEM data aggregated into different spatial resolutions (5 × 5 cm to 10 × 10 m). Firstly, slope gradient, slope length, and topographic factors were calculated at different resolutions. Then, the revised universal soil loss estimation (RUSLE) model was applied to estimate soil erosion rates with the derived LS factor at different resolutions. The results indicated that there was higher change rate in slope gradient, slope length, LS factor, and soil erosion rate when using DEM data with resolution from 5 × 5 cm to 2 × 2 m than using coarser DEM data. A power trend line was effectively used to present the relationship between soil erosion rate and DEM resolution. The findings indicated that soil erosion estimates are highly sensitive to DEM resolution (from 5 × 5 cm to 2 × 2 m), and the changes become relatively stable from 2 × 2 m. The use of DEM data with pixel size larger than 2 × 2 m cannot detect the micro topography. With the insights about the influencing mechanism of DEM resolution on soil erosion estimates, this study provides important suggestions for appropriate DEM data selection that should be investigated first for accurate soil erosion estimation.

中文翻译：

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基于无人机观测的土壤侵蚀估算中DEM空间分辨率差异的敏感性评估：尼泊尔中山农业梯田试验

山坡农业地区的土壤侵蚀是作物生产力和环境可持续性的根本问题。建立梯田是控制水土流失的一种非常流行的方法，准确评估水土流失率对可持续农业和环境管理至关重要。当前，许多土壤侵蚀估算主要基于可免费获得的中度或粗分辨率数字高程模型（DEM）数据，而忽略了农业阶地的微地形修改。无人机技术（UAV）的发展使高分辨率（厘米级）DEM的开发得以呈现出准确的地形特征。为了证明在这种高分辨率水平下土壤侵蚀估计值对DEM分辨率的敏感性，这项研究试图根据无人机衍生的高分辨率（5×5 cm）DEM数据评估尼泊尔中山农业梯田的土壤侵蚀估算，并使用汇总为不同空间分辨率的DEM数据对估算进行比较研究（ 5×5厘米至10×10 m）。首先，以不同的分辨率计算坡度，坡长和地形因子。然后，将修正后的通用土壤流失估计（RUSLE）模型应用于估算土壤侵蚀率，并得出 和地形因子是在不同的分辨率下计算的。然后，将修正后的通用土壤流失估计（RUSLE）模型应用于估算土壤侵蚀率，并得出 和地形因子是在不同的分辨率下计算的。然后，将修正后的通用土壤流失估计（RUSLE）模型应用于估算土壤侵蚀率，并得出LS系数在不同的分辨率下。结果表明，坡度，坡长，LS变化率较高。与使用较粗的DEM数据相比，使用分辨率为5×5 cm到2×2 m的DEM数据时，土壤侵蚀速率和土壤侵蚀率更高。有效地使用了一条功率趋势线来表示土壤侵蚀速率与DEM分辨率之间的关系。研究结果表明，土壤侵蚀估计值对DEM分辨率高度敏感（从5×5 cm到2×2 m），并且变化从2×2 m变得相对稳定。像素大小大于2×2 m的DEM数据的使用无法检测到微观形貌。借助有关DEM分辨率对土壤侵蚀估算的影响机制的见解，本研究为选择合适的DEM数据提供了重要建议，应首先对其进行研究以进行准确的土壤侵蚀估算。