论文标题
在存在空间相互作用的情况下，在栅格数据库中选择细胞以进行最大影响干预：多重与单个流动方向方法的计算复杂性
Selecting cells in a raster database for maximal impact intervention in the presence of spatial interaction: Computational complexity of a Multiple vs. a Single Flow Direction Method
论文作者
论文摘要
为了最大程度地减少以最小的努力或成本流向河流流域的沉积物，选择执行一定干预措施的最佳区域（例如，造林）很重要。 CAMF（基于细胞自动机的启发式启发式以最大化流量）是一种在栅格地理数据库环境中迭代执行此选择过程的方法。为了模拟流道，原始CAMF使用单个流动方向（SFD）算法。但是，SFD无法反映流动运输的真实本质，尤其是在浮雕低落的地区。本文介绍并分析了CAMF中多流动方向（MFD）算法的整合，以提供更现实的流动模拟。我们比较了CAMF-SFD和CAMF-MFD的计算复杂性，并讨论了可伸缩性W.R.T.涉及的细胞数量。我们评估了两个具有不同特性的流域中的造林的沉积物的行为，从而最大程度地减少了造林。
To minimize the sediment flowing to the outlet of a river catchment with minimal effort or cost, it is important to select the best areas to perform a certain intervention, e.g., afforestation. CAMF (Cellular Automata based heuristic for Minimizing Flow) is a method that performs this selection process iteratively in a raster geodatabase environment. To simulate the flow paths, the original CAMF uses a Single Flow Direction (SFD) algorithm. However, SFD fails to reflect the real nature of flow transport, especially in areas with low relief. This paper describes and analyzes the integration of a Multiple Flow Direction (MFD) algorithm in CAMF, in order to provide a more realistic flow simulation. We compare the computational complexity of CAMF-SFD and CAMF-MFD and we discuss the scalability w.r.t. the number of cells involved. We evaluate the behavior of both variants for sediment yield minimization by afforestation in two catchments with different properties.
