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An integrated method for calculating DEM-based RUSLE LS

机译:一种计算基于DEM的RUSLE LS的集成方法

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The improvement of resolution of digital elevation models (DEMs) and the increasing application of the Revised Universal Soil Loss Equation (RUSLE) over large areas have created problems for the efficiency of calculating the LS factor for large data sets. The pretreatment for flat areas, flow accumulation, and slope-length calculation have traditionally been the most time-consuming steps. However, obtaining these features are generally usually considered as separate steps, and calculations still tend to be time-consuming. We developed an integrated method to improve the efficiency of calculating the LS factor. The calculation model contains algorithms for calculating flow direction, flow accumulation, slope length, and the LS factor. We used the Deterministic 8 method to develop flow-direction octrees (FDOTs), flat matrices (FMs) and first-in-first-out queues (FIFOQs) tracing the flow path. These data structures were much more time-efficient for calculating the slope length inside the flats, the flow accumulation, and the slope length linearly by traversing the FDOTs from their leaves to their roots, which can reduce the search scope and data swapping. We evaluated the accuracy and effectiveness of this integrated algorithm by calculating the LS factor for three areas of the Loess Plateau in China and SRTM DEM of China. The results indicated that this tool could substantially improve the efficiency of LS-factor calculations over large areas without reducing accuracy.
机译:改善数字高度模型(DEMS)的分辨率和越来越多的大面积修正的通用土壤丢失方程(风格)的应用已经为计算大数据集的LS因子的效率而产生的问题。传统上是平坦区域,流量积累和斜坡长度计算的预处理是最耗时的步骤。然而,获得这些特征通常通常被认为是单独的步骤,并且计算仍然往往是耗时的。我们开发了一种提高计算LS因子的效率的集成方法。计算模型包含用于计算流动方向,流量,斜率长度和LS系数的算法。我们使用了确定性的8方法来开发流动方向八字(FDOTS),扁平矩阵(FMS)和追踪流动路径的首先第一输出队列(FIFOQs)。这些数据结构对于计算平面内的斜率,流量积聚和斜坡长度来线性地进行线性,通过将叶片从它们的叶子挖出到它们的根部,这可以减少搜索范围和数据交换。通过计算中国黄土高原的三个地区的LS因子和中国的SRTM DEM,评估了这种集成算法的准确性和有效性。结果表明,该工具可以大大提高大面积的LS系列计算的效率而不降低精度。

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