Keith Price Bibliography DEM, Surface Analysis for Ridges and Streams, Drainage, Depressions

22.5.2 DEM, Surface Analysis for Ridges and Streams, Drainage, Depressions

Chapter Contents (Back)
Curvature Analysis. See also Curvature and Features of Surfaces and Range Data.

Peucker, T.K., Douglas, D.H.,
Detection of Surface-Specific Points by Local Parallel Processing of Discrete Terrain Elevation Data,
CGIP(4), 1975, pp. 375-387. BibRef 7500

Johnston, E.G., Rosenfeld, A.,
Digital Detection of Pits, Peaks, Ridges, and Ravines,
SMC(5), July 1975, pp. 472-480. BibRef 7507

Haralick, R.M., Campbell, J.B., Wang, S.,
Automatic Inference of Elevation and Drainage Models from a Satellite Image,
PIEEE(73), 1985, pp. 1040-1053. Recognize Drainage Networks. BibRef 8500

Haralick, R.M., Wang, S., Shapiro, L.G., Campbell, J.B.,
Extraction of Drainage Networks by Using the Consistent Labeling Technique,
RSE(18), No. 10, October, 1985, pp. 163-175. BibRef 8510

Haralick, R.M., Wang, S., and Elliott, D.B.,
Spatial Reasoning to Determine Stream Network from LANDSAT Imagery,
ICPR82(502-514). This paper uses a lot of different other algorithms to do the basic processing but finally determines surface orientations which can give ridge and valley locations. The basic processing is to eliminate effects of known LANDSAT noise, use ratios of images to classify into any number of classes, use the classes to determine regions of the same object, use the intensity average for a class to get the average intensity, the rest is caused by the surface orientation differences. Darker and brighter regions are slopes, these then give valleys and ridge lines. Then compute approximate elevation data from the slopes. It produces interesting results. See also Topographic Classification of Digital Image Intensity Surfaces Using Generalized Splines and the Discrete Cosine Transform. BibRef 8200

Wang, S., Haralick, R.M., and Campbell, J.B.,
Relative Elevation Determination from Landsat Imagery,
CVWS84(150-157). Has some of the same properties as the stream network paper above. Generate an approximation of the elevation based on the shadows, etc. BibRef 8400

Haralick, R.M., Zhang, M.C., and Campbell, J.B.,
Automatic Delineation of Drainage Basins Within Digital Elevation Data Using the Topographic Primal Sketch,
Mathematical Geology(22), No. 2, 1990, pp. 189-209. BibRef 9000

Laffey, T.J.[Thomas J.], Haralick, R.M.[Robert M.], and Watson, L.T.[Layne T.],
The Topographic Primal Sketch and its Application to Passive Navigation,
DARPA83(304-317). Computing ridges and valleys, then using these in the navigation experiment. BibRef 8300

O'Callaghan, J.F., and Mark, D.M.,
The Extraction of Drainage Networks from Digital Elevation Data,
CVGIP(28), No. 3, December 1984, pp. 323-344. Recognize Drainage Networks. Uses digital terrain data for input. BibRef 8412

Soille, P., Gratin, C.,
An Efficient Algorithm for Drainage Network Extraction on DEMs,
JVCIR(5), 1994, pp. 181-189. BibRef 9400

Seemuller, W.W.,
The Extraction of Ordered Vector Drainage Networks form Elevation Data,
CVGIP(47), No. 1, July 1989, pp. 45-58.
WWW Version. Convert raster data to vectors with gaps, structure the results to get the networks. BibRef 8907

Monga, O., and Benayoun, S.,
Using Partial Derivatives of 3D Images to Extract Typical Surface-Features,
CVIU(61), No. 2, March 1995, pp. 171-189.
WWW Version. BibRef 9503
Earlier:
Using Differential Geometry in R4 to Extract Typical Features in 3D Images,
CVPR93(684-685).
IEEE Abstract. IEEE Top Reference. BibRef
Earlier:
Using Differential Geometry in R4 to Extract Typical Features in 3D Density Images,
ICPR92(I:379-382).
WWW Version. BibRef

Monga, O., Benayoun, S., and Faugeras, O.D.,
From Partial Derivatives of 3D Density Images to Ridge Lines,
CVPR92(354-359).
IEEE Abstract. IEEE Top Reference. Curvature analysis of range images. BibRef 9200

Monga, O., Armande, N., Montesinos, P.,
Thin Nets and Crest Lines: Application to Satellite Data and Medical Images,
CVIU(67), No. 3, September 1997, pp. 285-295. 9710
WWW Version. BibRef
Earlier: ICIP95(II: 468-471).
WWW Version. 9510 See also Thin Nets Extraction Using a Multi-scale Approach. BibRef

Fua, P.[Pascal],
Fast, Accurate and Consistent Modeling of Drainage and Surrounding Terrain,
IJCV(26), No. 3, March 1998, pp. 215-234.
WWW Version. 9804 BibRef
Earlier:
Model-Based Approach to Accurate and Consistent 3-D Modeling of Drainage and Surrounding Terrain,
CVPR97(903-908).
IEEE Abstract. IEEE Top Reference.
WWW Version. 9704 BibRef
And:
3-D Modeling of Drainage Patterns,
SRI-TN- No. 555, September 23, 1996. See also Model-Based Optimization: An Approach to Fast, Accurate and Consistent Site Modeling. BibRef

Kweon, I.S., Kanade, T.,
Extracting Topographic Terrain Features from Elevation Maps,
CVGIP(59), No. 2, March 1994, pp. 171-182.
WWW Version. BibRef 9403

Wladis, D.[David],
Automatic Lineament Detection Using Digital Elevation Models with Second Derivative Filters,
PhEngRS(65), No. 4, April 1999, pp. 453-458. BibRef 9904

Wilson, R.C.[Richard C.], Hancock, E.R.[Edwin R.],
Consistent topographic surface labelling,
PR(32), No. 7, July 1999, pp. 1211-1223.
WWW Version. BibRef 9907

Lopez, A.M., Lumbreras, F., Serrat, J., Villanueva, J.J.,
Evaluation of Methods for Ridge and Valley Detection,
PAMI(21), No. 4, April 1999, pp. 327-335.
IEEE Abstract. IEEE Top Reference.
WWW Version. Primarily drainage patterns, but apply to other line (maximum) detection problems. Has several references to the general problem from the 1800s. BibRef 9904

Jones, K.H.[Kevin H.],
Comparison of Two Approaches to Ranking Algorithms Used to Compute Hill Slopes,
GeoInfo(2), No. 3, October 1998, pp. 235-256.
WWW Version. BibRef 9810

Eberly, D., Gardner, R., Morse, B., Pizer, S., and Scharlach, C.,
Ridges for Image Analysis,
JMIV(4), 1994, pp. 353-373. Multiscale ridge detection. BibRef 9400

Sagar, B.S.D.[B. S. Daya], Venu, M., Srinivas, D.,
Morphological operators to extract channel networks from digital elevation models,
JRS(21), No. 1, January 2000, pp. 21. 9911 BibRef

Baudemont, F., Parrot, J.F.,
Structural Analysis of DEM's by Intersection of Surface Normals in a Three-Dimensional Accumulator Space,
GeoRS(38), No. 3, May 2000, pp. 1191-1198.
IEEE Top Reference. 0006 BibRef

Cronin, T.M.[Terrence M.],
Classifying Hills and Valleys in Digitized Terrain,
PhEngRS(66), No. 9, September 2000, pp. 1129-1138. Use the elevation-based containment properties of a contour map. 0010 BibRef

Miliaresis, G.C., Argialas, D.P.,
Extraction and Delineation of Alluvial Fans from Digital Elevation Models and Landsat Thematic Mapper Images,
PhEngRS(66), No. 9, September 2000, pp. 1093-1102. A region-growing segmentation algorithm. 0010 BibRef

Thibault, D.[David], Gold, C.M.[Christopher M.],
Terrain Reconstruction from Contours by Skeleton Construction,
GeoInfo(4), No. 4, December 2000, pp. 349-373.
WWW Version. 0101 BibRef

Kenward, T.[Tracey], Lettenmaier, D.P.[Dennis P.], Wood, E.F.[Eric F.], Fielding, E.[Eric],
Effects of Digital Elevation Model Accuracy on Hydrologic Predictions,
RSE(74), No. 3, 2000, pp. 432- 444. 0102 BibRef

Ahmadzadeh, M.R., Petrou, M.,
Error statistics for slope and aspect when derived from interpolated data,
GeoRS(39), No. 9, September 2001, pp. 1823-1833.
IEEE Top Reference. 0111 BibRef

Bittner, T.[Thomas], Stell, J.G.[John G.],
Vagueness and Rough Location,
GeoInfo(6), No. 2, June 2002, pp. 99-121.
WWW Version. Description of location of vague GIS objects (i.e. a valley). BibRef 0206

Mizukoshi, H.[Hiroko], Aniya, M.[Masamu],
Use of Contour-Based DEMs for Deriving and Mapping Topographic Attributes,
PhEngRS(68), No. 1, January 2002, pp. 83-93. The methods to calculate slope gradient and aspect and to classify slope form using contour-based DEMs are presented.
WWW Version. 0201 BibRef

Dillabaugh, C.R.[Craig R.], Niemann, K.O.[K. Olaf], Richardson, D.E.[Dianne E.],
Semi-Automated Extraction of Rivers from Digital Imagery,
GeoInfo(6), No. 3, September 2002, pp. 263-284.
WWW Version. 0208 BibRef

Yokoyama, R.[Ryuzo], Shirasawa, M.[Michio], Pike, R.J.[Richard J.],
Visualizing Topography by Openness: A New Application of Image Processing to Digital Elevation Models,
PhEngRS(68), No. 3, March 2002, pp. 257-266. Maps of positive and negative openness, computed at a DEM point from zenith or nadir angles constrained by neighboring points, aid topographic interpretation by emphasizing ridges, drainages, and convexities and concavities.
WWW Version. 0204 BibRef

Arge, L.[Lars], Chase, J.S.[Jeffrey S.], Halpin, P.[Patrick], Toma, L.[Laura], Vitter, J.S.[Jeffrey S.], Urban, D.[Dean], Wickremesinghe, R.[Rajiv],
Efficient Flow Computation on Massive Grid Terrain Datasets,
GeoInfo(7), No. 4, December 2003, pp. 283-313.
WWW Version. 0309 BibRef

Clarke, S.[Sharon], Burnett, K.[Kelly],
Comparison of Digital Elevation Models for Aquatic Data Development,
PhEngRS(69), No. 12, December 2003, pp. 1367-1376. Slopes, streams, and hydrologic units generated from 10-meter drainage-enforced digital elevation models and 30-meter digital elevation models are compared.
WWW Version. 0401 BibRef

Di, K.C.[Kai-Chang], Ma, R.J.[Rui-Jin], Li, R.X.[Rong-Xing],
Geometric Processing of Ikonos Stereo Imagery for Coastal Mapping Applications,
PhEngRS(69), No. 8, August 2003, pp. 873-880. The results of photogrammetric mapping of a Lake Erie coastal area from 1-m-resolution Ikonos Geo stereo images.
WWW Version. 0401 BibRef

Kim, K.M.[Kyoung Min], Park, J.J.[Joong Jo], Song, M.H.[Myung Hyun], Kim, I.C.[In Cheol], Suen, C.Y.[Ching Y.],
Detection of ridges and ravines using fuzzy logic operations,
PRL(25), No. 6, 19 April 2004, pp. 743-751.
WWW Version. 0405 BibRef

Aguilar, F.J.[Fernando J.], Ag��era, F.[Francisco], Aguilar, M.A.[Manuel A.], Carvajal, F.[Fernando],
Effects of Terrain Morphology, Sampling Density, and Interpolation Methods on Grid DEM Accuracy,
PhEngRS(71), No. 7, July 2005, pp. 805-816. Effects of terrain morphology, sampling density, and scattered data interpolation methods on the accuracy of interpolated Grid Elevation Models.
WWW Version. 0509 BibRef

Baker, M.E.[Matthew E.], Weller, D.E.[Donald E.], Jordan, T.E.[Thomas E.],
Comparison of Automated Watershed Delineations: Effects on Land Cover Areas, Percentages, and Relationships to Nutrient Discharge,
PhEngRS(72), No. 2, February 2006, pp. 159-168.
WWW Version. A comparison of manual and automated watershed delineation procedures and their effects on a multi-regional analysis of land-cover and stream nutrient concentration. 0602 BibRef

Lindsay, J.B.[John B.], Creed, I.F.[Irena F.],
Sensitivity of Digital Landscapes to Artifact Depressions in Remotely-Sensed DEMs,
PhEngRS(71), No. 9, September 2005, pp. 1029-1036.
WWW Version. 0602The effectiveness of inadequate representation of surfaces by grids and random errors in elevations to cause artifact depressions in digital elevation models of a range of landscape types is quantified. BibRef

Kim, J.R.[Jung Rack], Muller, J.P.[Jan-Peter], van Gasselt, S.[Stephan], Morley, J.G.[Jeremy G.], Neukum, G.[Gerhard], Team, t.H.C.[the HRSC CoI],
Automated Crater Detection, A New Tool for Mars Cartography and Chronology,
PhEngRS(71), No. 10, October 2005, pp. 1205-1217.
WWW Version. 0602An automated crater detection algorithm exploiting image data with potential for chronological research and geological analysis. BibRef