Journal
COMPUTERS & GEOSCIENCES
Volume 90, Issue -, Pages 87-96Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cageo.2016.02.021
Keywords
Depression filling; Flow direction; DEM; Hydrological analysis
Funding
- National Natural Science Foundation of China [41371399, 41371341]
- Chinese State Key Basic Research Project [2013CB733406]
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Depressions are common features in raster digital elevation models (DEMs) and they are usually filled for the automatic extraction of drainage networks. Among existing algorithms for filling depressions, the Priority-Flood algorithm substantially outperforms other algorithms in terms of both time complexity and memory requirement. The Priority-Flood algorithm uses a priority queue to process cells. This study proposes an efficient variant of the Priority-Flood algorithm, which considerably reduces the number of cells processed by the priority queue by using region-growing procedures to process the majority of cells not within depressions or flat regions. We present three implementations of the proposed variant: two pass implementation, one-pass implementation and direct implementation. Experiments are conducted on thirty DEMs with a resolution of 3m. All three implementations run faster than existing variants of the algorithm for all tested DEMs. The one-pass implementation runs the fastest and the average speed-up over the fastest existing variant is 44.6%. (C) 2016 Elsevier Ltd. All rights reserved.
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