Detecting landforms using quantitative radar roughness characterization and spectral mixing analysis

Studies in Computational Intelligence

Volumn 348, Issue , 2011, Pages 225-249

  Taramelli, Andrea ^a  

^a INSTITUTE FOR ENVIRONMENTAL PROTECTION AND RESEARCH ISPRA   (Italy)

Author keywords

Alluvial Fan; Curvature; Elevation; Fuzzy Logic; Roughness; SMA

Indexed keywords

EID: 79954559144     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-19733-8_13     Document Type: Article

References (72)

1. Adams, J.B., Smith, M.O., Johnson, P.E.: Spectral mixture modeling; a new analysis of rock and soil types at the Viking Lander 1 site. JGR 91, 8098-8122 (1986)
2. Adams, J.B., Sabol, D.E., Kapos, V., Filho, R.A., Roberts, D.A., Smith, M.O., Gillespie, A.R.: Classification of multispectral images based on fractions of endmembers: Application to land cover change in the Brazilian Amazon. RSE 52, 137-154 (1995) (Pubitemid 26438386)
3. Adams, J.B., Smith, M.O., Gillespie, A.R.: Imaging Spectroscopy: Interpretation based on spectral mixture analysis. In: Pieters, C.M., Englert, P. (eds.) Remote Geochemichal Analysis: Element and Mineralogical Composition, pp. 145-166. Cambridge University Press, New York (1993)
4. Allievi, J., Ambrosi, C., Cerini, M., Colesanti, C., Crosta, G.B., Ferretti, A., Fossati, D.: Monitoring slow mass movements with the Permanent Scatterers technique, pp. 07803-79306. IEEE, Los Alamitos (2003)
5. Ahamed, T.R., Gopal Rao, K., Murthy, J.S.R.: GIS-based fuzzy membership model for crop-land suitability analysis. Agric. Syst. 63, 75-95 (2000) (Pubitemid 30213478)
6. Antonello, G., Casagli, N., Farina, P., Leva, D., Nico, G., Sieber, A.J., Tarchi, D.: Ground-based SAR interferometry for monitoring mass movements. Lands. 1, 21-28 (2004)
7. Argialas, D.P., Tzotsos, A.: Geomorphological feature extraction from a digital elevation model trough fuzzy knowledge-based classification. In: Ehlers, M. (ed.) Proc. SPIE, Remote Sensing for environmental monitoring, gis application and geology, 2, vol. 4886, pp. 516-527 (2003)
8. th ICCD Conference on Human and Nature - Working tighter for sustainable development of Drylands, Beijing, China, February 25-28, pp. 387-397. ICARDA, Aleppo (2007)
9. Band, L.E., Moore, I.D.: Scale: landscape attributes and Geographical Information Systems. Hydrol. Porces. 9, 401-422 (1995) (Pubitemid 26438432)
10. Benallegue, M., Taconet, O., Vidal-Madjar, D., Normand, M.: The Use of Radar Backscat-tering Signals for Measuring Soil Moisture and Surface Roughness. RSE 53(1), 61-68 (1995) (Pubitemid 26438343)
11. Blumberg, D.G.: Analysis of large Aeolian (wind-blown) bedforms using the SRTM digital elevation data. RSE 100, 179-189 (2006) (Pubitemid 43084806)
12. th Canadian Symposium on Remote Sensing, pp. 2069-2072 (1989)
13. Boardman, J.W.: Automating spectral unmixing of AVIRIS data using convex geometry concepts. In: Green, R.O. (ed.) Fourth Airborne visible/infrared Imaging Spectrometer (Aviris) Airborne Geoscience Workshop, pp. 11-14. Jet Propulsion Laboratory, Pasadena (1993)
14. th Thematic Conference on Geologic Remote Sensing, pp. I407-I418. Environmental Research Institute of Michigan, Ann Arbor (1994)
15. Burrough, P.A., MacMillan, R.A., Van Deursen, W.: Fuzzy classification methods for determining land suitability from soil profile observations. J. Soil Science 43, 193-210 (1992) (Pubitemid 23374055)
16. Burrough, P.A., van Gaans, P., Hootsmans, R.: Continuous classification in soil survey: Spatial correlation, confusion and boundaries. Geoderma 77, 115-135 (1997)
17. Bull, W.B.: The alluvial fan environment. Progres. Physic. Geo. 1, 222-270 (1977)
18. Cobb, M., Petry, F., Robinson, V.: Special issue: uncertainty in geographic information systems and spatial data. Fuzzy Set and System 113(1), 1-159 (2003)
19. Cross, V., Firat, A.: Fuzzy objects for geographical information systems. Fuzzy Set and System 113(1), 19-36 (2000)
20. Dehn, M., Gärtner, H., Dikau, R.: Principles of Semantic Modeling of Landform Structures. Comp. & Geosc. 27, 1005-1010 (2001) (Pubitemid 32621204)
21. Dierking, W.: Quantitative Roughness Characterization of Geological Surfaces and Implications for Radar Signature Analysis. IEEE 7(5), 2397-2412 (1999) (Pubitemid 30518326)
22. Dikau, R.: The application of a digital relief model to landform analysis in geomorphology. In: Raper, J. (ed.) Three-Dimensional Applications in Geographical Information Systems, pp. 51-77. Taylor and Francis, London (1989)
23. Dubois, D., Prade, H.: What are fuzzy rules and how to use them. Fuzzy Set and System 84(2) (1996)
24. Elmore, A.J., Mustard, J.F., Manning, S.J., Lobell, D.B.: Quantifying vegetation change in semiarid environments: Precision and accuracy of spectral mixture analysis and the normalized difference vegetation index. RSE 73, 87-102 (2000) (Pubitemid 30446187)
25. Fairbridge, R.W.: The ecyclopedia of Geomorphology. Reinhold Book Corp., New York (1968)
26. Fisher, P.F.: Fuzzy modeling. In: Openshaw, S., Abrahart, R., Harris, T. (eds.) Geocomput-ing. pp. 161-186. Taylor and Francis, London (2000)
27. Fisher, P.F.: Sorties paradox and vague geographies. Fuzzy Set and System 113, 7-18 (2000)
28. Gillespie, A.R., Smith, M.O., Adams, J.B., Willis, S.C., Fischer III, A.F., Sabol, D.E.: Interpretation of residual images: Spectral mixture analysis of AVIRIS images. In: 2nd Airborne Visible/Infrared Imaging Spectrometer (Aviris) Airborne Geoscience Workshop, Owens Valley, California. NASA Jet Propulsion Laboratory, Pasadena (1990)
29. Greeley, R., Blumberg, D.G., McHone, J.F., Dobrovolkis, A., Iversen, J.D., Rasmussen, K.R., Wall, S.D., White, B.R.: Applications of spaceborne radar laboratory data to the study of aeolian processes. JGR 102(10), 971-983 (1997)
30. Greeley, R., Blumberg, D.G., Dobrovolskis, A.R., Gaddis, L.R., Iversen, J.D., Lancaster, N., Rasmussen, K.R., Saunders, R.S., Wall, S.D., White, B.R.: Potential transport of windblown sand: Influence of surface roughness and assessment with radar data. In: Tchakerian, V.P. (ed.) Desert Aeolian Processes, pp. 75-99. Chapman & Hall, London (1995)
31. Johnson, P.E., Smith, M.O., Taylor-George, S., Adams, J.B.: A semiempirical method for analysis of the reflectance spectra of binary mineral mixtures. JGR 88, 3557-3561 (1983) (Pubitemid 13554178)
32. Imhoff, M.L., Vermillion, C., Story, M.H., Choudhury, A.M., Gafoor, A., Polcyn, F.: Monsoon flood boundary delineation and damage assessment using spaceborne imaging radar and Landsat data. Photog. Eng. and rem. Sens. 53(4), 405-413 (1987) (Pubitemid 17571709)
33. Irvin, B.J., Ventura, S.J., Slater, B.K.: Fuzzy and isodata classification of landform elements from digital terrain data in Pleasant Valley, Wisconsin. Geoderma 77, 137-154 (1997)
34. Kobrick, M.: On the toes of Giants - How SRTM was born. Photog. Eng. and rem. Sens. 3, 206-210 (2006) (Pubitemid 43334217)
35. Laurent, B., Marticorena, B., Bergametti, G., Chazette, P., Maignan, F., Schmechtig, C.: Simulation of the mineral dust emission frequencies from desert areas of China and Mongolia using an aerodynamic roughness length map derived from the POLDER/ADEOS I surface products. Jour. Gephys. Res. 110, 21 (2005), doi:10.1029/2004JD005013 (Pubitemid 41582672)
36. Ladner, R., Petry, F., Cobb, M.: Fuzzy set approaches to spatial data mining of association rules. Transaction in GIS 7(1), 123-138 (2000)
37. Leeder, M.R.: Sedimentary basins: tectonic recorders of sediment discharge from drainage catchments. Earth surf. Proces. Landf. 22, 229-237 (1977)
38. Li, L., Ustin, S.L., Lay, M.: Application of multiple endmember spectral mixture analysis (MESMA) to AVIRIS imagery for coastal salt marsh mapping: a case study in China Camp, CA, USA. Int. Journ. of Rem. Sens. 26(23), 5193-5207 (2005) (Pubitemid 43878408)
39. Lu, D., Weng, Q.: Spectral mixture analysis of ASTER images for examining the relationship between urban thermal features and biophysical descriptors in Indianapolis, Indiana, USA. RSE 104, 57-167 (2006)
40. Nemec, W., Steel, R.J.: What is a fan delta and how we recognize it? In: Nemec, W., Steel, R.J. (eds.) Fan Deltas: sedimentology and tectonic settings. pp. 3-13. Blackie and Son, Glasgow & London (1988)
41. McBratney, A.B., De Gruijter, J.J.: A continuum approach to soil classification by modified fuzzy k-mean with extragrades. J. Soil Scince 43, 159-175 (1992)
42. McBratney, A.B., Odeh, I.O.A.: Application of fuzzy sets in soil science: Fuzzy logic, fuzzy measurements and fuzzy decisions. Geoderma 77, 85-113 (1997)
43. MacMillan, R.A., Pettapiece, W.W., Nolan, S.C., Goddard, T.W.: A generic procedure for automatically segmenting landforms into landform elements using DEMs, heuristic rules and fuzzy logic. Fuzzy Set and System 113, 81-109 (2000)
44. Melelli, L., Taramelli, A.: An example of debris-flows hazard modeling using GIS. Nat. Haz. Erath Syst. Scien. 4, 347-358 (2004) (Pubitemid 39266947)
45. Nash, E.B., Conel, J.E.: Spectral reflectance systematics for mixtures of powdered hyper-sthene, labradorite and ilmenite. JGR 79, 1615-1621 (1974)
46. Pike, R.J.: Geomorphometry - diversity in quantitative surface analysis. Prog. In Phy. Geogr. 24, 1-20 (2000) (Pubitemid 30203444)
47. Prigent, C., Tegen, I., Aires, F., Marticorena, B., Zribi, M.: Estimation of aerodynamic roughness length in arid and semi-arid regions over the globe with the ERS scatterome-ter. JGR 110, 12 (2005), doi:10.1029/2004JD005370 (Pubitemid 40923952)
48. Rabus, B., Eineder, M., Roth, A., Bamler, R.: The shuttle radar topography mission- a new class of digital elevation models acquired by spaceborne radar. Jour. of Photog. and Rem. Sens. 57, 241-262 (2003) (Pubitemid 36224754)
49. Roberts, D.A., Batista, G., Pereira, J., Waller, E., Nelson, B.: Change Identification using Multitemporal Spectral Mixture Analysis: Applications in Eastern Amazonia. In: Elvidge, C., Lunetta, R. (eds.) Remote Sensing Change Detection: Environmental Monitoring Applications and Methods, pp. 137-161. Ann Arbor Press, Ann Arbor (1998a)
50. Roberts, D.A., Gardner, M., Church, R., Ustin, S., Scheer, G., Green, R.O.: Mapping chap-paral in the Santa Monica mountains using multiple endmember spectral mixture models. RSE 65, 267-279 (1998b) (Pubitemid 29360703)
51. Robinson, V.B.: A Perspective on Geographic Information Systems and Fuzzy Sets. IEEE, 1-6 (2002), 0-7803-74614102
52. Robinson, V.B.: Some implications of fuzzy set theory applied to geographic databases Computers. Environment and Urban Systems 12, 89-97 (1988)
53. Sainsbury, R.M.: What is a vague object? Analysis 49, 99-103 (1989)
54. Settle, J.J., Drake, N.A.: Linear mixing and the estimation of ground cover proportions. Int. Journ. of Rem. Sens. 14(6), 1159-1177 (1993) (Pubitemid 23384230)
55. th Lunar and Planetary Science Conference, AGU, pp. 1835-1848 (1979)
56. Small, C.: Estimation of urban vegetation abundance by spectral mixture analysis. Int. Journ. of Rem. Sens. 22(7), 1305-1334 (2001) (Pubitemid 32418346)
57. Small, C.: The Landsat ETM+ Spectral Mixing Space. RSE 93, 1-17 (2004) (Pubitemid 39234706)
58. Smith, M.O., Johnson, P.E., Adams, J.B.: Quantitative determination of mineral types and abundances from reflectance spectra using principal component analysis. JGR 90, 792-804 (1985)
59. Smith, M.O., Ustin, S.L., Adams, J.B., Gillespie, A.R.: Vegetation in deserts: I. A regional measure of abundance from multispectral images. RSE 31, 1-26 (1990)
60. Speight, J.G.: The role of topography in controlling through-flow generation: a discussion. Earth Surf. Proces. Landf. 5, 187-191 (1984)
61. Taramelli, A., Melelli, L.: Contribution of the Landsat ETM+ Spectral Mixing Space and SRTM analysis to characterize Deep Seated Gravitational Slope Deformations in central Apennines (Italy). Int. Journ. of Rem. Sens. 30(2), 357-387 (2009)
62. Taramelli, A., Melelli, L.: Detecting alluvial fans using quantitative roughness characterization and fuzzy logic analysis. In: Gervasi, O., Murgante, B., Laganà, A., Taniar, D., Mun, Y., Gavrilova, M.L. (eds.) ICCSA 2008, Part I. LNCS, vol. 5072, pp. 1-15. Springer, Heidelberg (2008a)
63. Taramelli, A., Melelli, L.: Detecting alluvial fans using quantitative roughness characterization and fuzzy logic analysis using the SRTM data. IJCSST (2008b) (invited Paper) (in press)
64. Ulaby, F.T., Moore, R.K., Fung, A.K.: Microwave remote sensing, vol. 2. Addison-Wesley, Reading (1982)
65. Usery, E.L.: A conceptual framework and fuzzy set implementation for geographic features. In: Burrough, P.A., Frank, A. (eds.) Geographic Objects With Indeterminate Boundaries, pp. 87-94. Taylor & Francis, London (1996)
66. Wang, F.: A fuzzy grammar and possibility theory-based natural language user interface for spatial queries. Fuzzy Set and System 113(1), 147-159 (2000)
67. Wood, W.F., Snell, J.B.: A quantitative system for classifying landforms. U.S. Army Quartermaster Research and Engineering Center, Natick, MA, Tech. Rep. EP-124 (1960)
68. Zadeh, L.A.: Toward a perception-based theory of probabilistic reasoning with imprecise probabilities. Jour. Stat. Plann. and Inference 105(1), 105-119 (2002)
69. Zhu, A.X.: A similarity model for representing soil spatial information. Geoderma 77, 217-242 (1997a)
70. Zhu, A.X.: Measuring uncertainty in class assignment for natural resource maps using a similarity model. Photog. Eng. and Rem. Sens. 63, 1195-1202 (1997b)
71. Zhu, A.X., Band, L.E., Vertessy, R., Dutton, B.: Deriving soil property using a soil land inference model (SoLIM). Soil Sci. Soc. Am. J. 61, 523-533 (1997)
72. Zhu, A.X., Band, L.E., Dutton, B., Nimlos, T.: Automated soil inference under fuzzy logic Ecol. Modell 90, 123-145 (1996)