Assessment of sediment connectivity from vegetation cover and topography using remotely sensed data in a dryland catchment in the Spanish Pyrenees

Journal of Soils and Sediments

Volumn 14, Issue 12, 2014, Pages 1982-2000

  Foerster, Saskia ^a   Wilczok, Charlotte ^b   Brosinsky, Arlena ^a,b   Segl, Karl ^a  

^a GFZ GERMAN RESEARCH CENTRE FOR GEOSCIENCES   (Germany)

^b UNIVERSITY OF POTSDAM   (Germany)

Author keywords

Fractional cover; Imaging spectroscopy; Index of connectivity; North eastern Spain; Sediment connectivity; Spectral unmixing

Indexed keywords

EID: 84922080120     PISSN: 14390108     EISSN: 16147480     Source Type: Journal    
DOI: 10.1007/s11368-014-0992-3     Document Type: Article

References (80)

1. Adams JB, Smith MO, Gillespie AR (1993) Imaging spectroscopy: interpretation based on spectral mixture analysis. In: Pieters CM, Englert PAJ (eds) Remote geochemical analysis: elemental and mineralogical composition. Cambridge University Press, Cambridge, pp 145–166
2. Antoine M, Javaux M, Bielders C (2009) What indicators can capture runoff relevant connectivity properties of the micro-topography at the plot scale? Adv Water Resour 32:1297–1310
3. Antronico L, Coscarelli R, Terranova O (2005) Surface erosion assessment in two Calabrian basins (southern Italy). In: Batalla RJ, Garcia C (eds) Geomorphological processes and human impacts in River Basins. IAHS Publ 299. IAHS Press, Wallingford, pp 16–22
4. Asner GP, Heidebrecht KB (2002) Spectral unmixing of vegetation, soil and dry carbon cover in arid regions: comparing multispectral and hyperspectral observations. Int J Remote Sens 23:3939–3958
5. Bachmann M (2007) Automatisierte Ableitung von Bodenbedeckungsgraden durch MESMA-Entmischung. PhD thesis, Julius-Maximilians-Universität Würzburg, Würzburg, http://opus.bibliothek.uni-wuerzburg.de/frontdoor.php?source_opus=2633&la=de. Accessed August 2013
6. Bauer M (2013) Skalenübergreifende Analyse von Fließwegen auf Basis von Geländemodellen (LiDAR und ASTER) am Beispiel des Isábenaeinzugsgebietes in Nordost Spanien. Unpublished diploma thesis, University of Potsdam, Potsdam
7. Ben-Dor E, Chabrillat S, Demattê JAM, Taylor GR, Hill J, Whiting ML, Sommer S (2009) Using imaging spectroscopy to study soil properties. Remote Sens Environ 113:S38–S55
8. Borselli L, Cassi P, Torri D (2008) Prolegomena to sediment and flow connectivity in the landscape: a GIS and field numerical assessment. Catena 75:268–277
9. Bracken LJ, Croke J (2007) The concept of hydrological connectivity and its contribution to understanding runoff-dominated geomorphic systems. Hydrol Process 21:1749–1763
10. Bracken LJ, Wainwright J, Ali GA, Tetzlaff D, Smith MW, Reaney SM, Roy AG (2013) Concepts of hydrological connectivity: research approaches, pathways and future agendas. Earth-Sci Rev 119:17–34
11. Bronstert A, de Araújo JC, Batalla RJ, Cunha Costa A, Delgado JM, Francke T, Foerster S, Güntner A, López-Tarazón JA, Mamede G, Medeiros PH, Mueller EN, Vericat D (2014) Process-based modeling of erosion, sediment transport and reservoir siltation in meso-scale semi-arid catchments. J Soils Sediments (this issue)
12. Brosinsky A, Segl K, López-Tarazón J, Bronstert A, Foerster S (2014) Spectral fingerprinting: characterising suspended sediment sources by the use of VNIR-SWIR spectral information. J Soils Sediments. doi:10.1007/s11368-014-0927-z (this issue)
13. Cavalli M, Trevisani S, Comiti F, Marchi L (2013) Geomorphometric assessment of spatial sediment connectivity in small Alpine catchments. Geomorphology 188:31–41
14. Clark RN, Roush TL (1984) Reflectance spectroscopy: quantitative analysis techniques for remote sensing applications. J Geophys Res 89:6329–6340
15. Coulloudon B, Eshelman K, Gianola J, Habich N, Hughes L, Johnson C, Pellant M, Podborny P, Rasmussen A, Robles B, Shaver P, Spehar J, Willoughby J (1999) Sampling vegetation attributes. Interagency Technical Reference/U.S. Department of the Interior, Bureau of Land Management, Denver, Colorado, USA
16. De Asis AM, Omasa K (2007) Estimation of vegetation parameter for modeling soil erosion using linear spectral mixture analysis of Landsat ETM data. ISPRS J Photogramm 62:309–324
17. De Jong SM, Epema GF (2006) Imaging spectrometry for surveying and modelling land degradation. In: Van der Meer FD, De Jong SM (eds) Imaging spectrometry: basic principles and prospective applications. Kluwer Academic Publishers, Dordrecht, pp 65–86
18. De Vente J, Poesen J, Bazoffi P, Van Rompaey A, Verstraeten G (2006) Predicting catchment sediment yield in Mediterranean environments: the importance of sediment sources and connectivity in Italian drainage basins. Earth Surf Process Landf 31:1017–1034
19. Dennison PE, Roberts DA (2003) Endmember selection for multiple endmember spectral mixture analysis using endmember average RMSE. Remote Sens Environ 87:123–135
20. Dissmeyer GE, Foster GR (1981) Estimating the cover-management factor (C) in the universal soil loss equation for forest conditions. J Soil Water Conserv 36:235–240
21. Elmore AJ, Mustard JF, Manning SJ, Lobell DB (2000) Quantifying vegetation change in semiarid environments: precision and accuracy of spectral mixture analysis and the normalized difference vegetation index. Remote Sens Environ 73:87–102
22. Foody GM, Mathur A, Sanchez-Hernandez C, Boyd D (2006) Training set size requirements for the classification of a specific class. Remote Sens Environ 104:1–14
23. Francke T, Werb S, Sommerer E, López-Tarazón JA (2014) Analysis of runoff, sediment dynamics and sediment yield of subcatchments in the highly erodible Isábena catchment, Central Pyrenees. J Soils Sediments (this issue)
24. Gallart F, Solé A, Puigdefábregas J, Lázaro R (2002) Badland systems in the Mediterranean. In: Bull LJ, Kirkby MJ (eds) Dryland rivers: hydrology and geomorphology of semi-arid channels. Wiley, Chichester, pp 299-326
25. Gill T, Phinn S (2009) Improvements to ASTER-derived fractional estimates of bare ground in a Savanna Rangeland. IEEE T Geosci Remote 47:662–670
26. Goetz A (2009) Three decades of hyperspectral remote sensing of the Earth: a personal view. Remote Sens Environ 113:5–16
27. Guyot G, Guyon D, Riom J (1989) Factors affecting the spectral response of forest canopies: a review. Geocarto Intern 4:3–18
28. Kercher SM, Frieswyk CB, Zedler JB (2003) Effects of sampling teams and estimation methods on the assessment of plant cover. J Veg Sci 14:899–906
29. King C, Baghdadi N, Lecomte V, Cerdan O (2005) The application of remote-sensing data to monitoring and modelling of soil erosion. Catena 62:79–93
30. Kouli M, Soupios P, Vallianatos F (2009) Soil erosion prediction using the revised universal soil loss equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, Greece. Environ Geol 57:483–497
31. Kreeb KH (1983) Vegetationskunde. Methoden und Vegetationsformen unter Berücksichtigung Ökosystemischer Aspekte. Ulmer, Stuttgart
32. Laflen JM, Foster GR, Onstad CA (1985) Simulation of individual-storm soil loss for modeling the impact of soil erosion on crop productivity. In: El-Swaify SA, Moldenhauer WC, Lo A (eds) Soil erosion and conservation. Soil Conserv Soc Amer, Ankeny, pp 285–295
33. Lesschen JP, Cammeraat LH, Kooijman AM, Van Wesemael B (2008) Development of spatial heterogeneity in vegetation and soil properties after land abandonment in a semi-arid ecosystem. J Arid Environ 72:2082–2092
34. Lexartza-Artza I, Wainwright J (2009) Hydrological connectivity: linking concepts with practical implications. Catena 79:146–152
35. López-Tarazón JA, Batalla RJ, Vericat D, Francke T (2009) Suspended sediment transport in a highly erodible catchment: the river Isábena (Southern Pyrenees). Geomorphol 109:201–221
36. López-Tarazón JA, Batalla RJ, Vericat D, Francke T (2012) The sediment budget of a highly dynamic catchment. The River Isábena. Geomorphol 138:15–28
37. López-Vicente JA, Navas A, Machín J (2008) Identifying erosive periods by using RUSLE factors in mountain fields of the Central Spanish Pyrenees. Hydrol Earth Syst Sci 12:523–535
38. López-Vicente JA, Poesen J, Navas A, Gaspar L (2013) Predicting runoff and sediment connectivity and soil erosion by water for different land use scenarios in the Spanish Pre-Pyrenees. Catena 102:62–73
39. Ludwig JA, Wilcox BP, Breshears DD, Tongway DJ, Imeson AC (2005) Vegetation patches and runoff-erosion as interacting ecohydrological processes in semiarid landscapes. Ecol 86:288–297
40. MARM (Ministerio de Medio Ambiente y Medio Rural y Marino) (2008) Mapa de cultivos y aprovechamientos 1:50,000, GeoPortal, Madrid, Spain
41. McGwire K, Minor T, Fenstermaker L (2000) Hyperspectral mixture modeling for quantifying sparse vegetation cover in arid environments. Remote Sens Environ 72:360–374
42. Meusburger K, Konz N, Schaub M, Alewell C (2010) Soil erosion modeled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment. Int J Appl Earth Obs Geoinformation 12:208–215
43. Mueller EN, Francke T, Batalla RJ, Bronstert A (2009) Modelling the effects of land-use change on runoff and sediment yield for a meso-scale catchment in the Southern Pyrenees. Catena 79:288–296
44. Mueller EN, Güntner A, Francke T, Mamede G (2010) Modelling water availability, sediment export and reservoir sedimentation in drylands with the WASA-SED model. Geosci Model Develop 3:275–291
45. Muñoz-Robles C, Frazier P, Tighe M, Reid N, Briggs SV, Wilson B (2012) Assessing ground cover at patch and hillslope scale in semi-arid woody vegetation and pasture using fused Quickbird data. Intern J Appl Earth Obs Geoinformation 14:94–102
46. Natural Environment Research Council (NERC) (2011) Lidar data quality overview, http://arsf-dan.nerc.ac.uk/trac/wiki/Reports. Accessed August 2013
47. Numata I, Roberts DA, Chadwick OA, Schimel J, Sampaio FR, Leonidas FC, Soares JV (2007) Characterization of pasture biophysical properties and the impact of grazing intensity using remotely sensed data. Remote Sens Environ 109:314–327
48. Okin GS, Roberts DA, Murray B, Okin WJ (2001) Practical limits on hyperspectral vegetation discrimination in arid and semiarid environments. Remote Sens Environ 77:212–225
49. Painter TH, Roberts DA, Green RO, Dozier J (1998) The effect of grain size on spectral mixture analysis of snow-covered area from AVIRIS data. Remote Sens Environ 65:320–332
50. Peterson SH, Stow DA (2003) Using multiple image endmember spectral mixture analysis to study chaparral regrowth in southern California. Int J Remote Sens 24:4481–4504
51. Pierce FJ, Larson WE, Dowdy RH (1986) Soil conservation: an assessment of the National Resources Inventory, vol 2. National Academy Press, Washington DC
52. Plaza A, Benediktsson JA, Boardman JW, Brazile J, Bruzzone L, Camps-Valls G, Chanussot J, Fauvel M, Gamba P, Gualtieri A, Marconcini M, Tilton JC, Triann G (2009) Recent advances in techniques for hyperspectral image processing. Remote Sens Environ 113:110–122
53. Puigdefábregas J (2005) The role of vegetation patterns in structuring runoff and sediment fluxes in drylands. Earth Surf Process Landf 30:133–147
54. Rabe A, van der Linden S, Hostert P (2010) imageSVM, Version 2.1, software, available at www.hu-geomatics.de and www.enmap.org. Accessed August 2013
55. Rashed T, Weeks JR, Roberts DA, Rogan J, Powell RL (2003) Measuring the physical composition of urban morphology using multiple endmember spectral mixture models. Photogramm Eng Rem S 69:1011–1020
56. Reaney SM, Bracken LJ, Kirkby MJ (2014) The importance of surface controls on overland flow connectivity in semi-arid environments: results from a numerical experimental approach. Hydrol Process 28:2116–2128
57. Reid SC, Lane SN, Montgomery DR, Brookes CJ (2007) Does hydrological connectivity improve modelling of coarse sediment delivery in upland environments? Geomorphol 90:263–282
58. Renard KG, Foster GR, Weesies GA, McCool DK, Yoder DC (1997) Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation, Agricultural Handbook, US Department of Agriculture, Washington, 703, 404 pp
59. Richards JA (1999) Remote sensing digital image analysis: an introduction. Springer-Verlag, Berlin, p 240
60. Richter R, Schlaepfer D (2002) Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: atmospheric/topographic correction. Intern J Remote Sens 23:2631–2649
61. Roberts DA, Gardner M, Church R, Ustin S, Scheer G, Green RO (1998a) Mapping chaparral in the Santa Monica Mountains using multiple endmember spectral mixture models. Remote Sens Environ 65:267–279
62. Roberts DA, Batista GT, Pereira LG, Waller EK, Nelson BW (1998b) Change identification using multitemporal spectral mixture analysis: applications in Eastern Amazonia. In: Lunetta RS, Elvidge CD (eds) Remote sensing change detection: environmental monitoring methods and applications. Ann Arbor Press, Chelsea, pp 137–161
63. Sabol DE, Adams JB, Smith MO (1992) Quantitative subpixel spectral detection of targets in multispectral images. J Geophys Res 97:2659–2672
64. Savitzky A, Golay MJ (1964) Smoothing and differentiation of data by simplified least squares procedures. Anal Chem 36:1627–1639
65. Schaepman ME, Ustin SL, Plaza AJ, Painter TH, Verrelst J, Liang S (2009) Earth system science related imaging spectroscopy—an assessment. Remote Sens Environ 113:S123–S137
66. Schiettecatte W, D’Hondt L, Cornelis WM, Acosta ML, Leal Z, Lauwers N, Almoza Y, Alonso GR, Díaz J, Ruíz M, Gabriels D (2008) Influence of landuse on soil erosion risk in the Cuyaguateje watershed (Cuba). Catena 74:1–12
67. Sougnez N, Van Wesemael B, Vanacker V (2011) Low erosion rates measured for steep, sparsely vegetated catchments in southeast Spain. Catena 84:1–11
68. Tarboton (1997) A new method for the determination of flow directions and upslope areas in grid digital elevation models. Water Resour Res 33:309–319
69. Turnbull L, Wainwright J, Brazier RE (2008) A conceptual framework for understanding semi-arid land degradation: ecohydrological interactions across multiple-space and time scales. Ecohydrology 1:23–34
70. Ustin S, Roberts D, Gamon J, Asner G, Green R (2004) Using imaging spectroscopy to study ecosystem processes and properties. Bioscience 54:523–534
71. Valero-Garcés BL, Navas A, Machín J, Walling D (1999) Sediment sources and siltation in mountain reservoirs: a case study from the Central Spanish Pyrenees. Geomorphol 28:23–41
72. Van Nieuwenhuyse BHJ, Antoine M, Wyseure G, Govers G (2011) Pattern-process relationships in surface hydrology: hydrological connectivity expressed in landscape metrics. Hydrol Process 25:3760–3773
73. Verstraeten G, Van Oost K, Van Rompaey A, Pesen J, Govers G (2002) Integraal landen waterbeheer in landelijke gebieden met og op het beperken van ersosie en modderoverlast (proefproject gemeente Gingelom), Ministry of the Flemish Community, ANIMAL, Department Land, 69 pp
74. Verstraeten G, Bazzoffi P, Lajczak A, Radoane M, Rey F, Poesen J, de Vente J (2006) Reservoir and pond sedimentation in Europe. In: Boardman J, Poesen J (eds) Soil erosion in Europe. Wiley, Chichester, 855 pp
75. Vigiak O, Borselli L, Newham LTH, McInnes J, Roberts AM (2012) Comparison of conceptual landscape metrics to define hillslope-scale sediment delivery ratio. Geomorphol 138:74–88
76. Vrieling A (2006) Satellite remote sensing for water erosion assessment: a review. Catena 65:2–18
77. WCD (2000) Dams and development. A new framework for decision making. Report of the World Commission on Dams. Earth-scan Publications, London
78. Weltz MA, Renard KG, Simanton JR (1987) Revised universal soil loss equation for western rangelands, US/Mexico Symposium on Strategies for Classification and Management of Native Vegetation for Food Production in Arid Zones. US Forest Serv Gen Tech Rep RM-150:104–111
79. Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses: a guide to conservation planning. US Department of Agriculture, Agricultural Handbook Number, 537th edn. Government Printing Office, Washington DC
80. Wu B, Zhou Y, Huang J, Tian Y, Huang W (2004) Spatial pattern of soil and water loss and its affecting factors analysis in the upper basin of Miyun reservoir. IEEE 7:4700–4702