Modeling soil parameters using hyperspectral image reflectance insubtropical coastal wetlands

International Journal of Applied Earth Observation and Geoinformation

Volumn 33, Issue 1, 2014, Pages 47-56

  Anne, Naveen J P ^a   Abd Elrahman, Amr H ^a   Lewis, David B ^b   Hewitt, Nicole A ^a  

^a UNIVERSITY OF FLORIDA   (United States)

^b UNIVERSITY OF SOUTH FLORIDA   (United States)

Author keywords

Coastal wetlands; Hyperspectral remote sensing; Labile carbon; Labile nitrogen; Particulate organic matter; Soil properties

Indexed keywords

COASTAL WETLAND; HYPERION; IMAGE ANALYSIS; NDVI; NITROGEN; PARTICULATE ORGANIC MATTER; REGRESSION ANALYSIS; REMOTE SENSING; SOIL CARBON; SOIL PROPERTY; SOIL SCIENCE; SPECTRAL REFLECTANCE;

FLORIDA [UNITED STATES]; UNITED STATES;

EID: 84904738388     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2014.04.007     Document Type: Article

References (81)

1. Alongi, D., Trott, L, Wattayakorn, G., Clough, B., 2002. Below-ground nitrogen cycling in relation to net canopy production in mangrove forests of southern Thailand. Mar. Biol. 140 (4), 855-864.
2. Anderson, I.C., Tobias, C.R., Neikirk, B.B., Wetzel, R.L., 1997. Development of a process-based nitrogen mass balance model for a Virginia (USA) Spartina alterniflora salt marsh: implications for net DIN flux. Mar. Ecol. Prog. Ser. 159,13-27.
3. Baret, F., Guyot, G., 1991. Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sens. Environ. 35 (2-3), 161-173.
4. Bartholomeus, H., Kooistra, L, Stevens, A., van Leeuwen, M., van Wesemael, B., Ben-Dor, E., Tychon, B., 2011. Soil organic carbon mapping of partially vegetated agricultural fields with imaging spectroscopy. Int. J. Appl. Earth Obs. Geoinf. 13 (1), 81-88.
5. Ben-Dor, E., Patkin, K., Banin, A., Karnieli,A., 2002. Mapping of several soil properties using DAIS-7915 hyperspectral scanner data - a case study over clayey soils in Israel. Int. J. Remote Sens. 23 (6), 1043-1062.
6. Brown, D.J., Shepherd, K.D., Walsh, M.G., Dewayne Mays, M., Reinsch, T.G., 2006. Global soil characterization with VNIR diffuse reflectance spectroscopy. Geoderma 132 (3), 273-290.
7. Cahoon, D.R., 2006. A review of major storm impacts on coastal wetland elevations. Estuaries Coasts 29 (6), 889-898.
8. Castellano, M.J., Lewis, D.B., Kaye, J.P., 2013. Response of soil nitrogen retention to the interactive effects of soil texture, hydrology, and organic matter. J. Geophys. Res. Biogeosci. 118, 280-290.
9. Chabrillat, S., Goetz, A.F., Krosley, L., Olsen, H.W., 2002. Use of hyperspectral images in the identification and mapping of expansive clay soils and the role of spatial resolution. Remote Sens. Environ. 82 (2), 431-445.
10. Chang, C.W., Laird, DA, Mausbach, M.J., Hurburgh, C.R., 2001. Near-infrared reflectance spectroscopy-principal components regression analyses of soil properties. Soil Sci. Soc. Am. J. 65 (2), 480-490.
11. Chapin III, F.C., Matson, P.A., Vitousek, P.M., 2011. Decomposition and ecosystem carbon budgets. In: Chapin III, F.C., Matson, P.A., Vitousek, P.M. (Eds.), Principles of Terrestrial Ecosystem Ecology.,Second ed. Springer, New York, pp. 183-228, Chapter 7.
12. Curran, P.J., 1989. Remote sensing of foliar chemistry. Remote Sens. Environ. 30(3), 271-278.
13. Dalal, R.C., Henry, R.J., 1986. Simultaneous determination of moisture, organic carbon, and total nitrogen by near infrared reflectance spectrophotometry. Soil Sci. Soc. Am. J. 50 (1), 120-123.
14. Datt, B., 1999. Visible/near infrared reflectance and chlorophyll content in Eucalyptus leaves. Int. J. Remote Sens. 20 (14), 2741-2759.
15. Dunn, B.W., Batten, G.D., Beecher, H.G., Ciavarella, S., 2002. The potential of nearinfrared reflectance spectroscopy for soil analysis - a case study from the Riverine Plain of south-eastern Australia. Anim. Prod. Sci. 42 (5), 607-614.
16. Ehrenfeld,J.G., Ravit, B., Elgersma, K., 2005. Feedback in the plant-soil system. Annu. Rev. Environ. Resour. 30, 75-115.
17. EnMAP, 2014. Environmental Mapping and Analysis Programme (EnMAP), Deutsches Zentrum für Luft- und Raumfahrt (DLR) - German Aerospace Center, DLR, Linder Höhe 51147 Cologne, Germany, http://www.dlr.de/dlr/en/ desktopdefault.aspx/tabid-10379/567_read-421/#gallery/2671 (accessed 28.03.14).
18. Felde, G.W., Anderson, G.P., Cooley, T.W., Matthew, M.W., Berk, A., Lee, J., 2003. Analysis of Hyperion data with the FLAASH atmospheric correction algorithm. In: Geoscience and Remote Sensing Symposium, 2003. IGARSS'03. Proceedings. 2003 IEEE International, vol. 1, IEEE, pp. 90-92.
19. Gao, B.C., Montes, M.J., Davis, CO., Goetz, A.F.H., 2009. Atmospheric correction algorithms for hyperspectral remote sensing data of land and ocean. Remote Sens. Environ. 113, S17-S24.
20. Gessner, M.O., Chauvet, E., 1994. Importance of stream microfungi in controlling breakdown rates of leaf litter. Ecology 75 (6), 1807-1817.
21. Gitelson, A.A., Merzlyak, M.N., 1996. Signature analysis of leaf reflectance spectra: algorithm development for remote sensing of chlorophyll. J. Plant Physiol. 148 (3), 494-500.
22. Gitelson, A.A., Kaufman, Y.J., Merzlyak, M.N., 1996. Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sens. Environ. 58 (3), 289-298.
23. Gomez, C, Viscarra Rossel, R.A., McBratney, A.B., 2008. Soil organic carbon prediction by hyperspectral remote sensing and field vis-NIR spectroscopy: an australian case study. Geoderma 146 (3), 403-411.
24. Gong, P., Pu, R., Biging, G.S., Larrieu, M.R., 2003. Estimation of forest leaf area index using vegetation indices derived from Hyperion hyperspectral data. IEEE Trans. Geosci. Remote Sens. 41 (6), 1355-1362.
25. Hardisky, M.A., Gross, M.F., Klemas, V., 1986. Remote sensing of coastal wetlands. Bioscience 36 (7), 453-460.
26. Hbirkou,C.,Pätzold,S., Mahlein, A.K.,Welp,G., 2012. Airborne hyperspectral imaging of spatial soil organic carbon heterogeneity at the field-scale. Geoderma 175, 21-28.
27. Henderson, T.L., Baumgardner, M.F., Franzmeier, D.P., Stott, D.E., Coster, D.C., 1992. High dimensional reflectance analysis of soil organic matter. Soil Sci. Soc. Am. J. 56 (3), 865-872.
28. Hood-Nowotny, R., Umana, N.H.N., Inselbacher, E., Oswald-Lachouani, P., Wanek, W., 2010. Alternative methods for measuring inorganic, organic, and total dissolved nitrogen in soil. Soil Sci. Soc. Am. J. 74 (3), 1018-1027.
29. Huete, A.R., 2005. Estimation of soil properties using hyperspectral VIS/IR sensors. In: Encyclopedia of Hydrological Sciences. John Wiley & Sons, Inc, pp. 887-901.
30. HyspIRI, 2014. Hyperspectral Infrared Imager. Jet Propulsion Laboratory (JPL), California Institute of Technology (Caltech), Pasadena, CA, http://hyspiri.jpl.nasa.gov/ (accessed 28.03.14).
31. Jackson, R.D., Huete, A.R., 1991. Interpreting vegetation indices. Prev. Vet. Med. 11 (3-4), 185-200.
32. Janssens, I.A., Dieleman, W., Luyssaert, S., Subke, J.A., Reichstein, M., Ceulemans, R., Ciais, P., et al., 2010. Reduction of forest soil respiration in response to nitrogen deposition. Nat. Geosci. 3 (5), 315-322.
33. Jensen, J.R., 2005. Introductory Digital Image Processing: A Remote Sensing Perspective, 3rd ed. Prentice-Hall Inc., New Jersey, pp. 444.
34. Kalacska, M., Sanchez-Azofeifa, G.A. (Eds.), 2008. Hyperspectral Remote Sensing of Tropical and Sub-tropical Forests. CRC Press, Boca Raton.
35. Kaye,J., Barrett, J., Burke, I., 2002. Stable nitrogen and carbon pools in grassland soils of variable texture and carbon content. Ecosystems 5 (5), 461-471.
36. Kettler, T.A., Doran, J.W., Gilbert, T.L., 2001. Simplified method for soil particle-size determination to accompany soil-quality analyses. Soil Sci. Soc. Am. J. 65 (3), 849-852.
37. Kirwan, M.L., Mudd, S.M., 2012. Response of salt-marsh carbon accumulation to climate change. Nature 489(7417), 550-553.
38. Kooistra, L., Wanders, J., Epema, G.F., Leuven, R.S.E.W., Wehrens, R., Buydens, L.M.C., 2003. The potential of field spectroscopy for the assessment of sediment properties in river floodplains. Anal. Chim. Acta 484 (2), 189-200.
39. Kooistra, L, Salas, E.A.L., Clevers, J.G.P.W., Wehrens, R., Leuven, R.S.E.W., Nienhuis, P.H., Buydens, L.M.C., 2004. Exploring field vegetation reflectance as an indicator of soil contamination in river floodplains. Environ. Pollut. 127 (2), 281-290.
40. LABINS, 2012. Digital Orthographic Quarter Quad and High Resolution Images. Land Boundary Information System, Tallahassee, FL, http://data.labins.org/2003/MappingData/DOQQ/doqq.cfm (accessed 22.10.12).
41. Li, L., 2008. Quantifying lunar soil composition with partial least squares modeling of reflectance. Adv. Space Res. 42 (2), 267-274.
42. Li, D., Chen, X., Peng, Z., Chen, S., Chen, W., Han, L., et al., 2012. Prediction of soil organic matter content in a litchi orchard of south china using spectral indices. Soil Till. Res. 123, 78-86.
43. Liu, H., Zhang, Y., Zhang, B., 2009. Novel hyperspectral reflectance models for estimating black-soil organic matter in northeast china. Environ. Monit. Assess. 154 (1), 147-154.
44. López-Granados, F., Jurado-Expósito, M., Peña-Barragán,J.M., García-Torres, L, 2005. Using geostatistical and remote sensing approaches for mapping soil properties. Eur. J. Agron. 23 (3), 279-289.
45. Lu, P., Niu, Z., Li, L., 2012. Prediction of soil organic carbon by hyperspectral remote sensing imagery. In: 2012 Third Global Congress on Intelligent Systems (GCIS), IEEE, pp. 291-293.
46. MacLean, D.A., Wein, R.W., 1978. Weight loss and nutrient changes in decomposing litter and forest floor material in New Brunswick forest stands. Can. J. Bot. 56 (21), 2730-2749.
47. Martens, H.A., Dardenne, P., 1998. Validation and verification of regression in small data sets. Chemom. Intell. Lab. Syst. 44 (1), 99-121.
48. Martin, M.E., Aber, J.D., 1997. High spectral resolution remote sensing of forest canopy lignin, nitrogen, and ecosystem processes. Ecol. Appl. 7 (2), 431-443.
49. Middelburg, J.J., Klaver, G., Nieuwenhuize, J., Wielemaker, A., De Haas, W., Vlug, T., Van der Nat, J.F.W.A., 1996. Organic matter mineralization in intertidal sediments along an estuarine gradient. Mar. Ecol. Prog. Ser. 132 (1), 157-168.
50. Miller, J.R., Hare, E.W., Wu, J., 1990. Quantitative characterization of the vegetation red edge reflectance I. An inverted-Gaussian reflectance model. Int. J. Remote Sens. 11, 1755-1773.
51. Minasny, B., McBratney, A., Tranter, G., Murphy, B., 2008. Using soil knowledge for the evaluation of mid-infrared diffuse reflectance spectroscopy for predicting soil physical and mechanical properties. Eur. J. Soil Sci. 59 (5), 960-971.
52. Morra, M.J., Hall, M.H., Freeborn, L.L., 1991. Carbon and nitrogen analysis of soil fractions using near-infrared reflectance spectroscopy. Soil Sci. Soc. Am. J. 55 (1), 288-291.
53. Morris, J.T., Sundareshwar, P.V., Nietch, C.T., Kjerfve, B., Cahoon, D.R., 2002. Responses of coastal wetlands to rising sea level. Ecology 83 (10), 2869-2877.
54. Morris, J.T., Edwards, J., Crooks, S., Reyes, E., 2012. Assessment of carbon sequestration potential in coastal wetlands. In: Lal, R., Lorenz, K., Hüttl, R.F., Schneider, B.U., von Braun, J. (Eds.), Recarbonization of the Biosphere. Springer, The Netherlands, pp. 517-531.
55. Mulder, V., De Bruin, S., Schaepman, M., Mayr, T., 2011. The use of remote sensing in soil and terrain mapping - a review. Geoderma 162 (1), 1-19.
56. Mulder, V.L., de Bruin, S., Weyermann, J., Kokaly, R.F., Schaepman, M.E., 2013. Characterizing regional soil mineral composition using spectroscopy and geostatistics. Remote Sens. Environ. 139,415-429.
57. Nadelhoffer, K.J., 1990. Microlysimeter for measuring nitrogen mineralization and microbial respiration in aerobic soil incubations. Soil Sci. Soc. Am. J. 54 (2), 411-415.
58. Nedwell, D.B., Blackburn, T.H., Wiebe, W.J., 1994. Dynamic nature of the turnover of organic carbon, nitrogen and sulphur inthe sediments of aJamaican mangrove forest. Mar. Ecol. Prog. Ser. 110, 223-231.
59. NOAA, 2012. Quality Controlled Local Climatological Data. National Oceania and Atmospheric Administration, National Climatic Data Center, Ashville, North Carolina, http://cdo.ncdc.noaa.gov/qclcd/QCLCD?prior=N (accessed 12.10.12).
60. Ouerghemmi, W., Gomez, C, Naceur, S., Lagacherie, P., 2011. Applying blind source separation on hyperspectral data for clay content estimation over partially vegetated surfaces. Geoderma 163 (3), 227-237.
61. Palacios-Orueta, A., Ustin, S.L., 1998. Remote sensing of soil properties in the Santa Monica Mountains I. Spectral analysis. Remote Sens. Environ. 65 (2), 170-183.
62. Pande-Chhetri, R., Abd-Elrahman, A., 2013. Filtering high-resolution hyperspectral imagery in a maximum noise fraction transform domain using wavelet-based de-striping. Int. J. Remote Sens. 34 (6), 2216-2235.
63. Piekarczyk, J., Kazmierowski, C, Królewicz, S., 2012. Relationships between soil properties of the abandoned fields and spectral data derived from the advanced spaceborne thermal emission and reflection radiometer(ASTER). Adv. Space Res. 49 (2), 280-291.
64. Raich, J.W., Schlesinger, W.H., 1992. The global carbon dioxide flux in soil respiration and its relationship to vegetation and climate. Tellus B 44 (2), 81-99.
65. Rao, B.R.M., Dwivedi, R.S., Kushwaha, S.P.S., Bhattacharya, S.N., Anand, J.B., Dasgupta, S., 1999. Monitoring the spatial extent of coastal wetlands using ERS-1 SARdata. Int. J. Remote Sens. 20 (13), 2509-2517.
66. Read, J.J., Tarpley, L, McKinion, J.M., Reddy, K.R., 2002. Narrow-waveband reflectance ratios for remote estimation of nitrogen status in cotton. J. Environ. Qual. 31 (5), 1442-1452.
67. Robertson, G.P., Paul, E.A., 2000. Decomposition and soil organic matter dynamics. In: Methods in ecosystem science. Springer, New York, pp. 104-116.
68. Selige, T., Böhner, J., Schmidhalter, U., 2006. High resolution topsoil mapping using hyperspectral image and field data in multivariate regression modeling procedures. Geoderma 136 (1), 235-244.
69. Shepherd, K.D., Walsh, M.G., 2002. Development of reflectance spectral libraries for characterization of soil properties. Soil Sci. Soc. Am. J. 66 (3), 988-998.
70. Shi, X.Z., Lau, I.C., Aspandiar, M., 2014. Comparison of PLSR modelling and indicative mineral mapping of airborne hyperspectral imagery for acid sulphate soil assessment. Int. J. Remote Sens. 35 (4), 1309-1330.
71. Sollins, P., Homann, P., Caldwell, B.A., 1996. Stabilization and destabilization of soil organic matter: mechanisms and controls. Geoderma 74 (1), 65-105.
72. Stewart, C.E., Paustian, K., Conant, R.T., Plante, A.F., Six, J., 2007. Soil carbon saturation: concept, evidence and evaluation. Biogeochemistry 86 (1), 19-31.
73. Summers, D., Lewis, M., Ostendorf, B., Chittleborough, D., 2011. Visible near-infrared reflectance spectroscopy as a predictive indicator of soil properties. Ecol. Indicators 11 (1), 123-131.
74. Thenkabail, P.S., Enclona, E.A., Ashton, M.S., Legg, C, De Dieu, M.J., 2004. Hyperion, IKONOS, ALI, and ETM+ sensors in the study of African rainforests. Remote Sens. Environ. 90 (1), 23-43.
75. Tobias, R.D., Available online at http://www.sas.com/rnd/app/papers/pls.pdf (accessed 31.08.13, verified 31.08.13) 1995. An introduction to partial least squares analysis. In: Proceedings of the Twentieth Annual SAS Users Group International Conference, SAS Institute Inc., Cary, NC, pp. 1250-1257.
76. Uno, Y., Prasher, S., Patel, R., Strachan, I., Pattey, E., Karimi, Y., 2005. Development of field-scale soil organic matter content estimation models in eastern Canada using airborne hyperspectral imagery. Can. Biosyst. Eng. 47,1.9-1.14.
77. USGS, 2010. U.S. Geological Survey's Earth Resources Observation and Science (EROS) Center, EROS, San Diego, California. http://earthexplorer.usgs.gov/ (accessed 12.10.12).
78. Vaiphasa, C, Ongsomwang, S., Vaiphasa, T., Skidmore, A.K., 2005. Tropical mangrove species discrimination using hyperspectral data: a laboratory study. Estuar. Coast. Shelf Sci. 65 (1), 371-379.
79. Wang, F.M., Huang, J.F., Lou, Z.H., 2011. A comparison of three methods for estimating leafarea index of paddy rice from optimal hyperspectral bands. Precis. Agric. 12 (3), 439-447.
80. Wold, S., Sjöström, M., Eriksson, L., 2001. PLS-regression: a basic tool ofchemometrics. Chemom. Intell. Lab. Syst. 58 (2), 109-130.
81. Yitagesu, F.A., Van der Meer, F., Van der Werff, H., Hecker, C, 2011. Spectral characteristics of clay minerals inthe 2.5-14 (xm wavelength region. Appl. Clay Sci. 53 (4), 581-591.