基于快速排序的数字高程模型分级填洼算法

数字高程模型（DEM）的填洼过程是水系提取中最耗费时间的过程，在Moran和Vezina提出的填洼思想（M&V填洼算法）的基础上，建立了基于快速排序的分级填洼算法，既能有效地减少填洼过程中的搜索路径，提高填洼效率，又能保证依此提取水系的完整与连贯。对于一个给定的DEM地形，传统的填洼算法的执行效率是固定的，而分级填洼的实际执行效率取决于分级数量，对于自然流域，一般200至500的分级量可使计算效率达到最高。通过在6个不同流域上的应用表明，在平均情况下，分级填洼算法的时间复杂度约为O(n1.29)，其执行效率远高于M&V填洼算法及Arcgis 9.2（采用改进Jenson&Domingue算法）的执行效率。

Ranked algorithm to fill sinks in digital elevation model based on quicksort

A new ranked algorithm to fill sinks in Digital Elevation Models ( DEM) was introduced, including an improved quicksort algorithm to rank DEM data in pieces and a filling algorithm first developed by Olivier Planchon and Frédéric Darboux in 2001 (The idea was first suggested by Moran and Vezina, so it's called the M&V algorithm). Since removing the depressions of a DEM is usually a time-consuming procedure, the new method keeps the integrity and continuity of the drainage networks extracted by the pits-removed DEM and well reduces the depth of seeking path in iteration to accelerate pits-removing process. Different from the constant time complexity of traditional algorithms, the time complexity of the new method is variable, and the best performance for a natural terrain appears to be in 200 to 500 divided-pieces. The application of the new method in 6 study areas shows a time complexity of about O(n~1.29) on average, which is more efficient than the M&V algorithm and Arcgis 9.2 (improved Jenson & Domingue algorithm).