Arctic tundra ice-wedge landscape characterization by active contours without edges and structural analysis using high-resolution satellite imagery

Remote Sensing Letters

Volumn 4, Issue 11, 2013, Pages 1077-1086

  Skurikhin, Alexei N ^a   Gangodagamage, Chandana ^a   Rowland, Joel C ^a   Wilson, Cathy J ^a  

^a LOS ALAMOS NATIONAL LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE CONTOURS WITHOUT EDGES; CLASSIFICATION RESULTS; DISTANCE TRANSFORMS; HIGH RESOLUTION SATELLITE IMAGERY; HIGH SPATIAL RESOLUTION SATELLITE IMAGERY; LANDSCAPE CHARACTERIZATION; OBJECT CATEGORIZATION; STRUCTURAL CHARACTERISTICS;

IMAGE SEGMENTATION; LAKES; LANDFORMS;

SATELLITE IMAGERY;

IMAGE CLASSIFICATION; IMAGE RESOLUTION; LANDSCAPE STRUCTURE; MULTISPECTRAL IMAGE; SATELLITE IMAGERY; STRUCTURAL ANALYSIS; TUNDRA;

ARCTIC OCEAN;

EID: 84886659631     PISSN: 2150704X     EISSN: 21507058     Source Type: Journal    
DOI: 10.1080/2150704X.2013.840404     Document Type: Article

References (33)

1. CHAN, T.F, SANDBERG, B.Y. and VESE, L.A., 2000, Active contours without edges for vectorvalued images. Journal of Visual Communications and Image Representation, 11, pp. 130-141.
2. CHAN, T.F. and VESE, L.A., 2001, Active contours without edges. IEEE Transactions on Image Processing, 10, pp. 266-277.
3. CHAPIN, F.S., STURM, M., SERREZE, M.C., MCFADDEN, J.P., KEY, J.R., LLOYD, A.H., MCGUIRE, A.D., RUPP, T.S., LYNCH, A.H., SCHIMEL, J.P., BERINGER, J., CHAPMAN, W.L., EPSTEIN, H.E., EUSKIRCHEN, E.S., HINZMAN, L.D., JIA, G., PING, C.-L., TAPE, K.D., THOMPSON, C.D.C., WALKER, D.A. and WELKER, J.M., 2005, Role of land-surface changes in Arctic summer warming. Science, 310, pp. 657-660.
4. CHRISTOPHE, E., INGLADA, J. and MAUDLIN, J., 2010, Crowd-sourcing satellite image analysis. In IEEE International Geoscience and Remote Sensing Symposium, 25-30 July, Honolulu, HI. doi:10.1109/IGARSS.2010.5648833
5. CONGALTON, R.G. and MEAD, R.A., 1983, A quantitative method to test for consistency and correctness in photointerpretation. Photogrammetic Engineering and Remote Sensing, 49, pp. 69-74.
6. FROHN, R.C., HINKEL, K.M. and EISNER,W.R., 2005, Satellite remote sensing classification of thaw lakes and drained thaw lake basins on the North Slope of Alaska. Remote Sensing of Environment, 97, pp. 116-126.
7. GAO, J., 2009, Digital Analysis of Remote Sensed Imagery, pp. 497-525 (New York: McGraw-Hill).
8. GROSSE, G., ROMANOVSKY, V., WALTER, K., MORGENSTERN, A., LANTUIT, H. and ZIMOV, S., 2008, Distribution of thermokarst lakes and ponds at three yedoma sites in Siberia. In 9th International Conference on Permafrost, Kane, D.L. and Hinkel, K.M. (Eds.), June 29-July 3, Fairbanks, AK (Fairbanks, AK: Institute of Northern Engineering UAF), pp. 551-556.
9. GROSSE, G., SCHIRRMEISTER, L., KUNITSKY, V.V. and HUBBERTEN, H.W., 2005, The use of CORONA images in remote sensing of periglacial geomorphology: an illustration from the NE Siberian coast. Permafrost and Periglacial Processes, 16, pp. 163-172.doi:10.1002/ppp.509
10. GROSSE, G., SCHIRRMEISTER, L. andMALTHUS, T.J., 2009, Application of Landsat-7 satellite data and a DEM for the quantification of thermokarst-affected terrain types in the periglacial Lena-Anabar coastal lowland. Polar Research, 25, pp. 51-67.
11. HINKEL, K.M., JONES, B.M., EISNER, W.R., CUOMO, C.J., BECK, R.A. and FROHN, R., 2007, Methods to assess natural and anthropogenic thaw lake drainage on the western Arctic coastal plain of northern Alaska. Journal of Geophysical Research-Earth Surface, 112, F02S16. doi:10.1029/2006JF000584
12. HUBBARD, S.S., GANGODAGAMAGE, C., DAFFLON, B., WAINWRIGHT, H., PETERSON, J., GUSMEROLI, A., ULRICH, C., WU, Y., WILSON, C., ROWLAND, J., TWEEDIE, C. and WULLSCHLEGER, S.D., 2013, Quantifying and relating land-surface and subsurface variability in permafrost environments using LiDAR and surface geophysical datasets. Hydrogeology Journal, 21, pp. 149-169.doi:10.1007/s10040-012-0939
13. LABEN, C.A. and BROWER, B.V., 2000, Process for Enhancing the Spatial Resolution of Multispectral Imagery Using Pan-Sharpening. Technical Report.U.S. Patent # 6,011,875 (Rochester, NY: Eastman Kodak Company).
14. LILJEDAHL, A.K., HINZMAN, L.D. and SCHULLA, J., 2012, Ice-wedge polygon type controls low-gradient watershed hydrology. In Proceedings of the Tenth International Conference on Permafrost, 25-29 June 2012, Salekhard.
15. MARKON, C.J. and DERKSEN, D.V., 1994, Identification of tundra land cover near Teshekpuk lake, Alaska using SPOT satellite data. Arctic, 47, pp. 222-231.
16. MATLAB version 8.0.0, 2012, Natick, MA: The MathWorks Inc.
17. MAURER, C.R., QI, R. and RAGHAVAN, V., 2003, A linear time algorithm for computing exact Euclidean distance transforms of binary images in arbitrary dimensions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25, pp. 265-270.
18. MUMFORD, D. and SHAH, J., 1989, Optimal approximation by piecewise smooth functions and associated variational problems. Communications on Pure and Applied Mathematics, 42, pp. 577-685.
19. MUSTER, S., LANGER, M., HEIM, B., WESTERMANN, S. and BOIKE, J., 2012, Subpixel heterogeneity of ice-wedge polygonal tundra: a multi-scale analysis of land cover and evapotranspiration in the Lena River Delta, Siberia. Tellus B, 64. doi:10.3402/tellusb. v64i0.17301
20. OSHER, S. and SETHIAN, J.A., 1988, Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations. Journal of Computational Physics, 79, pp. 12-49.
21. OSTENDORF, B. and REYNOLDS, J.F., 1998, A model of arctic tundra vegetation derived from topographic gradients. Landscape Ecology, 13, pp. 187-201.
22. PAGLIERONI, D.W., 1992, Distance transforms: properties and machine vision applications. Computer Vision, Graphics, and Image Processing: Graphical Models and Image Processing, 54, pp. 56-74.
23. PERONA, P. and MALIK, J., 1990, Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12, pp. 629-639.
24. PING, C.L.,MICHAELSON, G.J., JORGENSON, M.T., KIMBLE, J.M., EPSTEIN, H., ROMANOVSKY, V.E. and WALKER, D.A., 2008, High stocks of soil organic carbon in the North American Arctic region. Nature Geoscience, 1, pp. 615-619.
25. REGMI, P., GROSSE, G., JONES, M.C., JONES, B.M. and ANTHONY, K.W., 2012, Characterizing post-drainage succession in thermokarst lake basins on the Seward peninsula, Alaska with TerraSAR-X backscatter and Landsat-based NDVI data. Remote Sensing, 4, pp. 3741-3765.doi:10.3390/rs4123741
26. SACHS, T., GIEBELS, M., BOIKE, J. and KUTZBACH, L., 2010, Environmental controls on CH4 emission from polygonal tundra on the microsite scale in the Lena river delta, Siberia. Global Change Biology, 16, pp. 3096-3110.
27. SACHS, T., WILLE, C., BOIKE, J. and KUTZBACH, L., 2008, Environmental controls on ecosystem-scale CH4 emission from polygonal tundra in the Lena river delta, Siberia. Journal of Geophysical Research, 113. doi:10.1029/2007JG000505
28. SAPIRO, G., 2001, Geometric Partial Differential Equations and Image Analysis, (Cambridge: Cambridge University Press).
29. SKURIKHIN, A.N., 2008, Proximity graphs based multi-scale image segmentation. Lecture Notes in Computer Science, 5358, pp. 298-307.doi:10.1007/ 978-3-540-89639-5-29
30. SKURIKHIN, A.N., GARRITY, S.R., MCDOWELL, N.G. and CAI, D.M., 2013, Automated tree crown detection and size estimation using multi-scale analysis of high-resolution satellite imagery. Remote Sensing Letters, 4, pp. 465-474.doi:10.1080/2150704X.2012. 749361
31. TURNER, D.P., OLLINGER, S.V. and KIMBALL, J.S., 2004, Integrating remote sensing and ecosystem process models for landscape-to regional-scale analysis of the carbon cycle. BioScience, 54, pp. 573-584.
32. ULRICH, M., GROSSE, G., CHABRILLAT, S. and SCHIRRMEISTER, L., 2009, Spectral characterization of periglacial surfaces and geomorphological units in the Arctic Lena delta using field spectrometry and remote sensing. Remote Sensing of Environment, 113, pp. 1220-1235.doi:10.1016/j.rse.2009.02.009
33. WOLF, A.F., 2012, UsingWorldview-2 Vis-NIR multispectral imagery to support land mapping and feature extraction using normalized difference index ratios. In Proceedings SPIE, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, vol. 8390, Shen, S.S. and Lewis, P.E. (Eds.), 23-27 April 2012, Baltimore, MD, 83900N. doi:10.1117/12.917717