Derivation of soil line influence on two-band vegetation indices and vegetation Isolines

Remote Sensing

Volumn 1, Issue 4, 2009, Pages 842-857

  Yoshioka, Hiroki ^a   Miura, Tomoaki ^b   Demattê, José A M ^c   Batchily, Karim ^d   Huete, Alfredo R ^e  

^a AICHI PREFECTURAL UNIVERSITY   (Japan)

^b UNIVERSITY OF HAWAII AT MANOA   (United States)

^c UNIVERSITY OF SÃO PAULO   (Brazil)

^d USDA NRCS   (United States)

^e UNIVERSITY OF ARIZONA   (United States)

Author keywords

Soil line; Soil noise; Spectral vegetation index; Vegetation isoline

Indexed keywords

BIAS ERROR; BIOPHYSICAL PARAMETERS; EXTERNAL DATA SOURCES; LINEAR COMBINATIONS; LINEAR FUNCTIONS; MODEL EQUATIONS; NEAR INFRARED REFLECTANCE; SOIL LINE; SOIL MAPS; SOIL PARAMETERS; SOIL SURFACES; SPECTRAL VEGETATION INDICES; VEGETATION INDEX; VEGETATION ISOLINE;

REFLECTION; VEGETATION;

SOILS;

EID: 80051765361     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs1040842     Document Type: Article

References (42)

1. Brown, J.;Wardow, B.; Tabesse, T.; Hayes, M.; Reed, B. T. The Vegetation Drought Response Index (VegDRI): A New Integrated Approach for Monitoring Drought Stress in Vegetation. GIScience and Remote Sens. 2008, 45, 16-46.
2. Li, A.N.; Liang, S.L.; Wang, A.S.; Qin, J. Estimating crop yield from multi-temporal satellite data using multivariate regression and neural network techniques. Photogramm. Engi. Remote Sens. 2007, 73, 1149-1157.
3. National Research Council. Issues in the integration of research and operational satellite systems for climate research: I. science and design; National Academy Press: Washington D.C., 2000.
4. National Research Council. Issues in the integration of research and operational satellite systems for climate research: II. implementation; National Academy Press: Washington D.C., 2000.
5. Gilabert, M.A.; González-Piqueras, J.; Garciá, F.J.; Meliá, J. A generalized soil-adjusted vegetation index. Remote Sens. Environ. 2002, 82, 303-310.
6. Major, D.J.; Baret, F.; Guyot, G.; A ratio vegetation index adjusted for soil brightness. Int. J. Remote Sens. 1990, 11(5), 727-40.
7. Huete, A.R.; Jackson, R.D.; Post, D.F. Spectral response of a plant canopy with different soil backgrounds. Remote Sens. Environ. 1985, 17, 37-54.
8. Huete, A.R. A soil-adjusted vegetation index (SAVI). Remote Sens. Environ. 1988, 25, 295-309.
9. Pinty, B.; Verstraete, M. M. GEMI: a non-linear index to monitor global vegetation from satellites. Vegetatio 1992, 101, 15-20.
10. Qi, J.; Chehbouni, A.; Huete, A.R.; Kerr, Y.H.; Sorooshian, S. A modified soil adjusted vegetation index. Remote Sens. Environ. 1994, 48, 119-126.
11. Richardson, A.J.; Wiegand, C.L. Distinguishing vegetation from soil background information. Photogramm. Eng. Remote Sens. 1977, 43, 1541-1552.
12. Galvao, L.S.; Vitorello, I. Variability of laboratory measured soil lines of soils from southeastern Brazil. Remote Sens. Environ. 1998, 63, 166-181.
13. Huete, A.R.; Jackson, R.D.; Post, D.F. Soil spectral effects on 4-space vegetation discrimination. Remote Sens. Environ. 1984, 15, 155-165.
14. Huete, A.R. Separation of soil plant spectral mixtures by factor analysis. Remote Sens. Environ. 1986, 61, 24-33.
15. Huete, A.R. Soil influences in remotely sensed vegetation-canopy spectra. In Theory and Applications of Optical Remote Sensing; Asrar, G., Ed.; Wiley: New York, 1989; pp.107-141.
16. Huete, A.R.; Tucker, C.J. Investigation of soil influences in AVHRR red and near-infrared vegetation index imagery, Int. J. Remote Sens. 1991, 12, 1223-1242.
17. Donohue, R.J.; Roderick, M.L.; McVicar, R.R. Deriving consistent long-term vegetation information from AVHRR reflectance data using a cover-triangle-based framework. Remote Sens. Environ. 2008, 112, 2938-2949.
18. Stabile, M.C.C.; Searcy, S.W. Validation of the soil line transformation technique. Trans. ASABE 2009, 52, 633-640.
19. Fox, G.A.; Sabbagh, G.J.; Searcy, S.W.; Yang, C. An automated soil line identification routine for remotely sensed images. Soil Sci. Soc. Am. J. 2004, 68, 1326-1331.
20. Baret, F.; Jackquemoud, S.; Hanocq, J.F. About the soil line concept in remote sensing. Remote Sens. Rev. 1993, 5, 281-284.
21. Fox, G.A.; Sabbagh, G.J. Estimation of soil organic matter from Red and Near-Infrared remotely sensed data using a soil line euclidean distance technique. Soil Sci. Soc. Am. J. 2002, 66, 1922-1929.
22. Fox, G.A.; Metla, R. Soil property analysis using principal components analysis, soil line, and regression models. Soil Sci. Soc. Am. J. 2005, 69, 1782-1788.
23. Nanni, M.R.;Demattê, J.A.M. Spectral reflectance methodology in comparison to traditional soil analysis. Soil Sci. Soc. Am. J. 2006, 70, 393-407.
24. Jordan, C.F. Derivation of leaf area index from quality of light on the forest floor. Ecology 1969, 50, 663-666.
25. Tucker, C.J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 1979, 8, 127-150.
26. Clevers, J.G.P.W. The application of a weighted infrared-red vegetation index for estimating leaf area index by correcting for soil moisture. Remote Sens. Environ. 1989, 29, 25-37.
27. Demattê, J.A.M.; Huete, A.R.; Guimaraes, L.; Nanni, M.R.; Alves, M.C.; Fiorio, P.R. Methodology for bare soil detection and discrimination by Landsat-TM image. Open Remote Sens. J. 2009, 2, 24-35.
28. Elvidge, C.D.; Lyon, R.J.P. Influence of rock-soil spectral variation on the assessment of green biomass. Remote Sens. Environ. 1985, 17, 265-269.
29. Yoshioka, H.; Huete, A.R.; Miura, T. Derivation of vegetation isoline equations in red-NIR reflectance space. IEEE Trans. Geosci. Remote. Sens. 2000, 38, 838-848.
30. Yoshioka, H.; Miura, T.; Huete, A.R.; Ganapol, B.D. Analyses of vegetation isoline equations in red-NIR reflectance space. Remote Sens. Environ. 2000, 74, 313-326.
31. Ben-Dor, E.; Irons, J.R.; Epema, G.F. Remote sensing for the earth science. In Manual of remote sensing vol.3; Rencz, A.N., Ed.; Wiley: New York, 1999; pp.111-188.
32. Valeriano, M.M.; Epiphanio, J.C.N.; Formaggio, A.R.; Oliveira, J.B. Bidirectional reflectance factor of 14 soil classes from Brazil. Int. Journal of Remote Sens. 1995, 16, 113-128.
33. Elvidge, C.D.; Chen, Z. Comparison of broad-band and narrow-band red and near-infrared vegetation indices. Remote Sens. Environ. 1995, 51, 38-48.
34. Gitelson, A.A.; Kaufman, Y.J. MODIS NDVI optimization to fit the AVHRR data series-spectral considerations. Remote Sens. Environ. 1998, 66, 343-350.
35. Gobron, N.; Pinty, B.; Verstraete, M.M.; Widlowski, J. Advanced vegetation indices optimized for up-coming sensors: design, performance, and applications. IEEE Trans. Geosci. Remote Sens. 2000, 38, 2489-2505.
36. Clevers, J.G.P.W. The derivation of a simplified reflectance model for the estimation of leaf area index. Remote Sens. Environ. 1988, 25, 53-69.
37. Verhoef, W. Light scattering by leaf layers with application to canopy reflectance modeling: the SAIL model. Remote Sens. Environ. 1984, 16, 125-141.
38. Verhoef, W. Earth observation modeling based on layer scattering matrices. Remote Sens. Environ. 1984, 17, 165-78.
39. Cooper, K.; Smith, J.A.; Pitts, D. Reflectance of a vegetation canopy using the adding method. Applied Optics 1982, 21(22), 4112-4119.
40. Van de Hulst, H.C. Multiple light scattering: tables, formulas, and applications, 1; Academic Press: New York, 1980.
41. Baret, F.; Guyot, G. Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sens. Environ. 1991, 35, 161-173.
42. Verstraete, M.M.; Pinty, B. Designing optimal spectral indices for remote sensing applications. IEEE Trans. Geosci. Remote Sens. 1996, 34, 1254-1265.