Volume 6 Number 8 (Aug. 2011)
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JSW 2011 Vol.6(8): 1611-1618 ISSN: 1796-217X
doi: 10.4304/jsw.6.8.1611-1618

Automatic Extraction of Drainage Networks from DEMs Base on Heuristic Search

Kun Hou1, 2, Jigui Sun1, Wei Yang2, 3, Tieli Sun1, Ying Wang3, Sijun Ma4
1Jilin University/College of Computer Science and Technology, Changchun, China
2Northeast Normal University/School of Computer Science and Information Technology, Changchun, China
3Changchun Normal University/College of Computer Science and Technology, Changchun, China
4Jinggangshan University/Art School, Jinggangshan, China

Abstract—Computer aided automatic Extraction of drainage networks from DEMs can promote the efficiency of regional water resource prospecting and assessment in GIS. Extracting drainage networks from raster DEMs is a necessary requirement in many applications of GIS, and determining surface water flow direction is a fundamental problem. In a raster environment, surface water flow direction of each cell can be directed to the neighboring cell with the steepest downslope drop (The basic D8, deterministic eight-neighbour method), which is inadequate for routing flow over pits and flat areas. Several improved methods are proposed to assign flow direction of pits and flats, which typically use entirely different procedures for processing pits and flats without heuristic information. Being different from others, a method to treat pits and flats is proposed in this paper. The method is based on heuristic search, which can effectively handle both conditions. This method is implemented in Pascal and experiments are carried out on actual DEM data. The experimental results show that this approach are robust, computationally efficient, and avoid many of the problems associated with other methods.

Index Terms—GIS, pit, flat areas, drainage networks


Cite: Kun Hou, Jigui Sun, Wei Yang, Tieli Sun, Ying Wang, Sijun Ma, "Automatic Extraction of Drainage Networks from DEMs Base on Heuristic Search," Journal of Software vol. 6, no. 8, pp. 1611-1618, 2011.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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