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I/O-Efficient Algorithms for Problems on Grid-Based Terrains
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Source Journal of Experimental Algorithmics (JEA) archive
Volume 6 ,  (2001) table of contents
Article No. 1  
Year of Publication: 2001
ISSN:1084-6654
Authors
Lars Arge  Duke University
Laura Toma  Duke University
Jeffrey Scott Vitter  Duke University
Publisher
ACM  New York, NY, USA
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ABSTRACT

The potential and use of Geographic Information Systems is rapidly increasing due to the increasing availability of massive amounts of geospatial data from projects like NASA's Mission to Planet Earth. However, the use of these massive datasets also exposes scalability problems with existing GIS algorithms. These scalability problems are mainly due to the fact that most GIS algorithms have been designed to minimize internal computation time, while I/O communication often is the bottleneck when processing massive amounts of data. In this paper, we consider I/O-efficient algorithms for problems on grid-based terrains.Detailed grid-based terrain data is rapidly becoming available for much of the earth's surface. We describe [EQUATION] I/O algorithms for several problems on [EQUATION] grids for which only O(N) algorithms were previously known. Here M denotes the size of the main memory and B the size of a disk block.We demonstrate the practical merits of our work by comparing the empirical performance of our new algorithm for the flow accumulation problem with that of the previously best known algorithm. Flow accumulation, which models flow of water through a terrain, is one of the most basic hydrologic attributes of a terrain. We present the results of an extensive set of experiments on real-life terrain datasets of different sizes and characteristics. Our experiments show that while our new algorithm scales nicely with dataset size, the previously known algorithm "breaks down" once the size of the dataset becomes bigger than the available main memory. For example, while our algorithm computes the flow accumulation for the Appalachian Mountains in about three hours, the previously known algorithm takes several weeks.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
NASA Earth Observing System (EOS) project, http://eos.nasa.gov/.
 
2
NASA Shuttle Radar Topography Mission (SRTM). http://www-radar.jpl.nasa.gov/srtm/.
 
3
U.S. Geological Survey: Five minute Gridded Earth Topography Data (ETOPO5). http://edewww.cr.usgs.gov/Webglis/glisbin/guide.pl/glis/hyper/guide/etopo5.
 
4
U.S. Geological Survey: Global thirty arc second Elevation Dataset (GTOPO30). http://edcwww.er.usgs.gov/landdaac/gtopo30/gtopo30.html.
 
5
U.S. Geological Survey (USGS) digital elevation models. http://mcmcweb.er.usgs.gov/status/dem_stat.html.
 
6
 
7
8
 
9
ARC/INFO. 1993. Understanding GIS--the ARC/INFO method. ARC/INFO. Rev. 6 for workstations.
 
10
 
11
 
12
ARGE, L., BARVE, R., PROCOPIUC, O., TOMA, L., VENGROFF, D. E., AND WICKEREMESINGHE, R. 1999. TPIE User Manual and Reference (edition 0.9.01a). Duke University. The manual and software distribution are available on the web at http://www.cs.duke.edu/TPIE/.
 
13
 
14
 
15
 
16
 
17
 
18
DIJKSTHA, E.W. 1969. A note on two problems in connection with graphs. Numerische Mathematik.
 
19
FAIRFIELD, J. AND LEYMARIE, P. 1991. Drainage network from grid digital elevation model. Water Resource Research 27, 709-717.
 
20
 
21
FRANK, A. U., PALMER, B., AND ROBINSON, V.B. 1986. Formal methods for the accurate definition of some fundamental terms in physical geography. In Proc. 2nd Int. Syrup. on Spatial Data Handling (1986), pp. 583-599.
 
22
 
23
HUTCHINSON, D., MAHESHWARI, A., AND ZEH, N. 1999. An external memory data structure for shortest path queries. In Proc. 5th Annual Int. Conf. Computing and Combinatorics, Number 1627 in LNCS (July 1999). Springer-Verlag.
 
24
 
25
KREVELD, M.V. 1997. Digital elevation models: overview and selected TIN algorithms. In M. VAN KREVELD, J. NIEVERGELT, T. ROOS, AND P. WIDMAYER Eds., Algorithmic Foundations of GIS. Springer-Verlag, Lecture Notes in Computer Science 1340.
 
26
 
27
MAHESHWARI, A. AND ZEH, N. 1999. External memory algorithms for outerplanar graphs. Manuscript.
 
28
MOORE, I.D. 1996. Hydrologic Modeling and GIS, Chapter 26, pp. 143-148. GIS World Books. Boulder.
 
29
MOORE, I. D., GRAYSON, R. B., AND LADSON, A.R. 1991. Digital terrain modelling: a review of hydrological, geomorphological and biological aplications. Hydrological Processes 5, 3-30.
 
30
MOORE, I. D, TURNER, A. K., WILSON, J. P., JENSON, S. K., AND BAND, L.E. 1993. GIS and Environmental Modelling. Oxford University Press.
 
31
 
32
NODINE, M. H., GOODRICH, M. T., AND VITTER, J.S. 1996. Blocking for external graph searching. Algorithmica 16, 2, 181-214.
 
33
O'CALLAGHAN, J. F. AND MARK, D. M. 1984. The extraction of drainage networks from digital elevation data. Computer Vision, Graphics and Image Processing 28.
 
34
ULLMAN, J. D. AND YANNAKAKIS, M. 1991. The input/output complexity of transitive closure. Annals of Mathematics and Artificial Intellegence 3, 331-360.
 
35
VENGROFF, D.E. 1994. A transparent parallel I/O environment. In Proc. DAGS Symposium on Parallel Computation (1994).
36
 
37
WOLOCK, D. 1993. Simulating the variable-source-area of streamflow generation with the watershed model topmodel. Technical report, U.S. Department of the Interior.
 
38
YU, S., VAN KREVELD, M., AND SNOEYINK, J. 1996. Drainage queries on TINs: from local to global and back again. In Proc. 7th Int. Symp. on Spatial Data Handling (1996), pp. 13A.I-13A.14.

CITED BY  7

Collaborative Colleagues:
Lars Arge: colleagues
Laura Toma: colleagues
Jeffrey Scott Vitter: colleagues