Quantifying responses of spectral vegetation indices to dead materials in mixed grasslands

Remote Sensing

Volumn 6, Issue 5, 2014, Pages 4289-4304

  Yang, Xiaohui ^a   Guo, Xulin ^b  

^a UNIVERSITY OF LETHBRIDGE   (Canada)

^b UNIVERSITY OF SASKATCHEWAN   (Canada)

Author keywords

Dead material cover; Regression model; Remote sensing; Sensitivity analysis

Indexed keywords

CHARACTERIZATION; MATHEMATICAL MODELS; REFLECTION; REGRESSION ANALYSIS; REMOTE SENSING; SENSITIVITY ANALYSIS; VEGETATION;

DEAD MATERIAL COVER; GRASSLAND VEGETATION; QUANTITATIVE ESTIMATION; REGRESSION MODEL; REMOTELY SENSED DATA; SASKATCHEWAN , CANADA; SPECTRAL REFLECTANCES; SPECTRAL VEGETATION INDICES;

MATERIALS;

EID: 84901492922     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs6054289     Document Type: Article

References (38)

1. He, Y.; Guo, X.; Wilmshurst, J.F. Studying mixed grassland ecosystem I: Suitable hyperspectral vegetation indices. Can. J. Remote Sens. 2006, 32, 98-107.
2. Paruelo, J.M.; Epstein, H.E.; Lauenroth, W.K.; Burke, I.C. ANNP estimations from NDVI for the central grassland region of the United States. Ecology 1997, 7, 953-958.
3. Purevdorj, T.; Tateishi, R.; Ishiyama, T.; Honda, Y. Relationship between percent vegetation cover and vegetation indices. Int. J. Remote Sens. 1998, 19, 3519-3535.
4. Moreau, S.; Bosseno, R.; Gu, X.F.; Baret, F. Assessing the biomass dynamic of Andean bofedal and totora high-protein wetland grasses from NOAA/AVHRR. Remote Sens. Environ. 2003, 85, 516-529.
5. Jackson, R.D.; Huete, A.R. Interpreting vegetation indices. Prebentive Vet. Med. 1991, 11, 185-200.
6. Pickup, G.; Chewings, V.H.; Nelson, D.J. Estimating changes in vegetation cover over time in arid rangelands using Landsat MSS data. Remote Sens. Environ. 1993, 43, 243-263.
7. Guo, X.; Zhang, C.; Wilmshurst, J.F.; Sissons, R. Monitoring grassland health with remote sensing approaches. Prairie Perspect. 2005, 8, 11-22.
8. Zhang, C.; Guo, X. Monitoring northern mixed prairie health using broadband satellite imagery. Int. J. Remote Sens. 2008, 29, 2257-2271.
9. Yang, X.; Guo, X.; Fitzsimmons, M. Assessing light to moderate grazing effects on grassland production using satellite imagery. Int. J. Remote Sens. 2012, 33, 5087-5104.
10. Frank, A.B.; Aase, J.K. Residue effects on radiometric reflectance measurements of Northern Great Plains rangelands. Remote Sens. Environ. 1994, 49, 195-199.
11. Daughtry, C.S.T.; McMurtrey, J.E., III.; Nagler, P.L.; Kim, M.S.; Chappelle, E.W. Spectral Reflectance of Soil and Crop Residues. In Near Infrared Spectroscopy: The Future Waves; Davies, A.M.C., Williams, P., Eds.; NIR Publications: Chichester, UK, 1996; pp. 505-511.
12. Goward, S.N.; Huemmrich, K.F. Vgetation canopy PAR absorptance and the normalized difference vegetation index: An assessment using the SAIL model. Remote Sens. Environ. 1991, 39, 119-140.
13. Nagler, P.L.; Daughtry, C.S.T.; Goward, S.N. Plant litter and soil reflectance. Remote Sens. Environ. 2000, 71, 207-215.
14. Environment Canada, 2003, Canadian Climate Normals or Average 1971-2000. Available online: http://www.climate.weatheroffice.ec.gc.ca/climate_normals/index_e.html (accessed on 24 August 2009).
15. Michalsky, S.J.; Ellise, R.A. Vegetation of Grasslands National Parks; D.A. Westworth and Associates Ltd.: Calgary, AB, Canada, 1994.
16. Fargey, K.S.; Larson, S.D.; Grant, S.J.; Fargey, P.; Schmidt, C. Grasslands National Park Field Guide; Prairie Wind and Silver Sage-Friends of Grasslands Inc.: Val Marie, SK, Canada, 2000.
17. Zhang, C.; Guo, X. Measuring biological heterogeneity in the northern mixed prairie: A remote sensing approach. Can. Geogr. 2007, 51, 462-474.
18. Daubenmier, R. A canopy-coverage method of vegetational analysis. Northwest. Sci. 1959, 33, 43-64.
19. Jordan, C.F. Derivation of leaf area index from quality of light on the first floor. Ecology 1969, 50, 663-666.
20. Rouse, J.W.; Haas, R.H.; Schell, J.A.; Deering, D.W.; Harlan, J.C. Monitoring the Vernal Advancement of Retrogradation of Natural Vegetation; Type III, Final Report; National Aeronautics and Space Administration, Goddard Space Flight Centre (NASA/GSFC): Greenbelt, MD, USA, 1974; p. 371.
21. Liu, H.Q.; Huete, A.R. A feedback based modification of the NDVI to minimize canopy background and atmospheric noise. IEEE Trans. Geosci. Remote Sens. 1995, 33, 457-465.
22. Clevers, J.C.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.
23. Petoorelli, N.; Vik, J.O.; Mysterud, A.; Gaillard, J.; Tucker, C.J.; Stenseth, N.C. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends Ecol. Evol. 2005, 20, 503-510.
24. Huete, A.R. A soil-adjusted vegetation index (SAVI). Remote Sens. Environ. 1988, 25, 295-309.
25. Baret, F.; Guyot, G. Potential and limits of vegetation indices for LAI and APAR assessment. Remote Sens. Environ. 1991, 35, 161-173.
26. 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.
27. Broge, N.H.; Leblanc, E. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sens. Environ. 2000, 76, 156-172.
28. Ji, L.; Peters, A.J. Performance evaluation of spectral vegetation indices using a statistical sensitivity function. Remote Sens. Environ. 2007, 106, 59-65.
29. Yang, X.; Kovach, E.; Guo, X. Biophysical and spectral responses to various burn treatments in the northern mixed-grass prairie. Can. J. Remote Sens. 2013, 39, 175-184.
30. Huete, A.; Justice, C.; Liu, H. Development of vegetation and soil indices for MODIS-EOS. Remote Sens. Environ. 1994, 49, 224-234.
31. Van Leeuwen, W.J.D.; Huete, A.R. Effects of standing litter on the biophysical interpretation of plant canopies with spectral indices. Remote Sens. Environ. 1996, 55, 123-138.
32. Gitelson, A.A. Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation. J. Plant Physiol. 2003, 161, 165-173.
33. Schabenberger, O.; Pierce, F.J. Contemporary Statistical Models for the Plant and Soil Sciences; CRC Press: Boca Raton, FL, USA, 2002; p. 738.
34. Woolley, J.T. Reflectance and transmittance of light by leaves. Plant Physiol. 1971, 47, 656-662.
35. Paltridge, G.W.; Barber, J. Monitoring grassland dryness and fire potential in Australia with NOAA/AVHRR data. Remote Sens. Environ. 1988, 25, 381-394.
36. Aase, J.K.; Tanaka, D.L. Reflectance from four wheat residue cover sensitivities as influenced by three soil background. Agron. J. 1991, 83, 753-757.
37. Daughtry, C.S.T.; Hunt, E.; McMurtrey, J.E., III. Assessing crop residue cover using shortwave infrared reflectance. Remote Sens. Environ. 2004, 90, 126-134.
38. Wiegand, C.L.; Richardson, A.J. Relating spectral observations of the agricultural landscape to crop yield. Food Struct. 1992, 11, 249-258.