Toward standardization of vegetation indices

Remotely Sensed Data Characterization, Classification, and Accuracies

Volumn 1, Issue , 2015, Pages 175-193

  Steven, Michael D ^a   Malthus, Timothy J ^b   Baret, Frédéric ^c  

^a UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^b CSIRO   (Australia)

^c CEMAGREF   (France)

Author keywords

[No Author keywords available]

Indexed keywords

INFRARED DEVICES; REFLECTION; REMOTE SENSING; STANDARDIZATION;

ANATOMICAL CHARACTERISTICS; ENVIRONMENTAL VARIABLES; REFLECTANCE SPECTRUM; REFLECTED SPECTRUM; SCATTERING MEDIUM; SPECTRAL FEATURE; SPECTRAL SIGNATURE; VEGETATION CANOPY;

VEGETATION;

EID: 85020731000     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1201/b19294     Document Type: Chapter

References (96)

1. Agapiou, A., D. G. Hadjimitsis, and D. D. Alexakis. 2012. Evaluation of broadband and narrowband vegetation indices for the identification of archaeological crop marks. Remote Sens 4:3892-3919.
2. Bacour, C., F. M. Bréon, and F. Maignan. 2006. Normalization of the directional effects in NOAA-AVHRR reflectance measurements for an improved monitoring of vegetation cycles. Remote Sens Environ 102:402-413.
3. Baret, F. and G. Guyot. 1991. Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sens Environ35:161-173.
4. Berk, A., L. S. Bernstein, G. P. Anderson, P. K. Acharya, D. C. Robertson, J. H. Chetwynd, and S. M. Adler-Golden. 1998. MODTRAN cloud and multiple scattering upgrades with application to AVIRIS. Remote Sens Environ 65:367-375.
5. Bowers, S. A. and R. J. Hanks. 1965. Reflection of radiant energy from soil. Soil Sci 100:130-138.
6. Boyd, D. S., S. Almond, J. Dash, P. J. Curran, and R. A. Hill. 2011. Phenology of vegetation in Southern England from Envisat MERIS terrestrial chlorophyll index (MTCI) data. Int J Remote Sens 32:8421-8447.
7. Boyd, D. S. and G. M. Foody. 2011. An overview of recent remote sensing and GIS based research in ecological informatics. Ecol Informatics 6:25-36.
8. Brown, M., J. E. Pinzón, K. Didan, J. T. Morisette, and C. J. Tucker. 2006. Evaluation of the consistency of long-term NDVI time series derived from AVHRR, SPOT-Vegetation, SeaWiFS, MODIS, and Landsat ETM+ sensors. IEEE Trans Geosci Remote Sens 44:1787-1793.
9. Callieco, F. and F. Dell’Acqua. 2011. A comparison between two radiative transfer models for atmospheric correction over a wide range of wavelengths. Int J Remote Sens 32:1357-1370.
10. CEOS. 2006. The CEOS virtual constellation concept V0.4, Committee on Earth Observation Satellites. http://igos-cryosphere.org/docs/CEOS_constellations.doc (accessed July 25, 2014).
11. D’Odorico, P., A. Gonsamo, A. Damm, and M. E. Schaepman. 2013. Experimental evaluation of Sentinel-2 spectral response functions for NDVI time-series continuity. IEEE Trans Geosci Remote Sens 51:1336-1348.
12. D’Odorico, P., A. Gonsamo, B. Pinty, N. Gobron, N. Coops, E. Mendez, and M. E. Schaepman. 2014. Intercomparison of fraction of absorbed photosynthetically active radiation products derived from satellite data over Europe. Remote Sens Environ 142:141-154.
13. Fensholt, R., I. Sandholt, and S. Stisen. 2006. Evaluating MODIS, MERIS, and VEGETATION vegetation indices using in situ measurements in a semiarid environment. IEEE Trans Geosci Remote Sens 44:1774-1786.
14. Fisher, J. B., K. P. Tu, and D. D. Baldocchi. 2008. Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites. Remote Sens Environ 112:901-919.
15. Gallo, K., L. Ji, B. Reed, J. Eidenshink, and J. Dwyer. 2005. Multiplatform comparisons of MODIS and AVHRR normalized difference vegetation index data. Remote Sens Environ 99:221-231.
16. Gallo, K. P. and C. S. T. Daughtry. 1987. Differences in vegetation indices for simulated Landsat-5 MSS and TM, NOAA-9 AVHRR and SPOT-1 sensor systems. Remote Sens Environ23:439-452.
17. Gates, D. M., H. J. Keegan, J. C. Schleter, and V. R. Weidner. 1965. Spectral properties of plants. Appl Opt 4:11-20.
18. Gausman, H. W. and W. A. Allen. 1973. Optical parameters of leaves of 30 plant species. Plant Physiol 52:57-62.
19. Gobron, N., B. Pinty, O. Aussedat, M. Taberner, O. Faber, F. Melin, T. Lavergne, M. Robustelli, and P. Snoeij. 2008. Uncertainty estimates for the FAPAR operational products derived from MERIS—Impact of top-of-atmosphere radiance uncertainties and validation with field data. Remote Sens Environ112:1871-1883.
20. Gonsamo, A. and J. M. Chen. 2013. Spectral response function comparability among 21 satellite sensors for vegetation monitoring. IEEE Trans Geosci Remote Sens 51:1319-1335.
21. Goward, S. N., D. G. Dye, S. Turner, and J. Yang. 1993. Objective assessment of the NOAA global vegetation index data product. Int J Remote Sens 14:3365-3394.
22. APAR, and net primary production of terrestrial ecosystems. Remote Sens Environ 70:29-51.
23. Gutman, G. 1991. Vegetation indices from AVHRR: an update and future prospects. Remote Sens Environ 35:121-136.
24. Guyot, G. 1990. Optical properties ofvegetation canopies. In M. D. Steven and J. A. Clark (eds), Applications of Remote Sensing in Agriculture. Butterworths, London, U.K., pp. 19-43.
25. Guyot, G. and X. F. Gu. 1994. Effect of radiometric corrections on NDVI—Determined from SPOT HRV and Landsat TM data. Remote Sens Environ 49:169-180.
26. Hadjimitsis, D. G., G. Papdavid, A. Agapiou, K. Themistocleous, M. G. Hadjimitsis, A. Retalis, S. Michaelides, N. Chrysoulakis, L. Toulios, and C. R. I. Clayton. 2010. Atmospheric correction for satellite remotely sensed data intended for agricultural applications: impact on vegetation indices. Nat Hazards Earth Syst Sci 10:89-95.
27. Heller, J. 1961. Catch 22. Simon and Schuster, New York.
28. Hill, J. and D. Aifadopoulou. 1990. Comparative analysis of Landsat-5 TM and SPOT HRV-1 data for use in multiple sensor approaches. Remote Sens Environ 34:55-70.
29. Holben, B. N., C. J. Tucker, and C. J. Fan. 1980. Spectral assessment of soybean leaf area and leaf biomass. Photogramm Eng Remote Sens 46:651-656.
30. Huete, A. R. 1988. A soil adjusted vegetation index (SAVI). Int J Remote Sens 9:295-309.
31. Huete, A. R. and H. Q. Liu 1994. An error and sensitivity analysis of the atmospheric- and soil-correcting variants of the NDVI for the MODIS-EOS. IEEE Trans Geosci Remote Sens32:897-905.
32. Huete, A. R., H. Q. Liu, K. Batchily, and W. van Leeuwen. 1997. A comparison of vegetation indices over a global set of TM images for EOSMODIS. Remote Sens Environ59:440-451.
33. Jacquemoud, S., W. Verhoef, F. Baret, C. Bacour, P. J. Zarco-Tejada, G. P. Asner, C. François, and S. L. Ustin. 2009. PROSPECT + SAIL models: a review of use for vegetation characterization. Remote Sens Environ 113:S56-S66.
34. Jaggard, K. W. and C. J. Clark. 1990. Remote sensing to predict the yield of sugar beet in England. In M. D. Steven and J. A. Clark (eds), Applications of Remote Sensing in Agriculture. Butterworths, London, U.K., pp. 201-208.
35. Ji, L., K. Gallo, J. C. Eidenshink, and J. Dwyer. 2008. Agreement evaluation of AVHRR and MODIS 16-day composite NDVI data sets. Int J Remote Sens 29:4839-4861.
36. Lee, K-S., W. B. Cohen, R. E. Kennedy, T. K. Maiersperger, and S. T. Gower. 2004. Hyperspectral versus multispectral data for estimating leaf area index in four different biomes. Remote Sens Environ 91:508-520.
37. Le Maire, G., C. François, and E. Dufrêne. 2004. Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements. Remote Sens Environ 89:1-28.
38. Mahiny, A. S. and B. Turner. 2007. A comparison of four common atmospheric correction methods. Photogramm Eng Remote Sens 73:361-368.
39. Martinez-Beltran, C., M. A. O. Jochum, A. Calera, and J. Melia. 2009. Multisensor comparison of NDVI for a semi-arid environment in Spain. Int J Remote Sens 30:1355-1384.
40. Maselli, F., S. Romanelli, L. Bottai, and G. Maracchi. 2000. Processing of GAC NDVI data for yield forecasting in the Sahelian region. Int J Remote Sens 21:3509-3523.
41. Miura, T., A. Huete, and H. Yoshioka. 2006. An empirical investigation of cross-sensor relationships of NDVI and red/near-infrared reflectance using EO-1 Hyperion data. Remote Sens Environ 100:223-236.
42. Miura, T., J. P. Turner, and A. R. Huete. 2013. Spectral compatibility of the NDVI across VIIRS, MODIS and AVHRR: an analysis of atmospheric effects using EO-1 Hyperion. IEEE Trans Geosci Remote Sens 51:1349-1359.
43. Monteith, J. L. 1977. Climate and the efficiency of crop production in Britain. Philos Trans R Soc Lond Ser B, 281:277-294.
44. Monteith, J. L. and M. H. Unsworth. 1990. Principles of Environmental Physics, 2nd edn., Edward Arnold, London, U.K.
45. Moura, Y. M., L. S. Galvao, J. R. dos Santos, D. A. Roberts, and F. M. Breunig. 2012. Use of MISR/Terra data to study intra-and inter-annual EVI variations in the dry season of tropical forest. Remote Sens Environ 127:260-270.
46. Munyati, C. and G. Mboyeni. 2013. Variation in NDVI values with change in spatial resolution for semi-arid vegetation: a case study in Northwestern South Africa. Int J Remote Sens34:2253-2267.
47. Nagol, J., E. F. Vermote, and S. D. Prince. 2009. Effects of atmospheric variation on AVHRR NDVI data. Remote Sens Environ 113:392-397.
48. Obata, K., T. Miura, and H. Yoshioka. 2012. Analysis of the scaling effects in the area-averaged fraction of vegetation cover retrieved using an NDVI-isoline-based linear mixture model. Remote Sens 4:2156-2180.
49. Ouyang, W., F. H. Hao, A. K. Skidmore, T. A. Groen, A. G. Toxopeus, and T. Wang. 2012. Integration of multi-sensor data to assess grassland dynamics in a Yellow River subwatershed. Ecol Indic 18:163-170.
50. Ouyang, W., F. H. Hao, C. Zhao, and C. Lin. 2010. Vegetation response to 30 years hydropower cascade exploitation in upper stream of Yellow River. Commun Nonlinear Sci Numer Simul 15:128-1941.
51. Penuelas, J. and I. Filella. 1998. Visible and near-infrared techniques for diagnosing plant physiological status. Trends Plant Sci 3:151-156.
52. Perry, C. R. and L. F. Lautenshlager. 1984. Functional equivalence of spectral vegetation indices. Remote Sens Environ 14:169-182.
53. Pettorelli, N., J. O. Vik, A. Mysterud, J-M. Gaillard, C. J. Tucker, and N. C. Stenseth. 2005. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends Ecol Evol 20:503-510.
54. Picket-Heaps, C. A., J. G. Canadell, P. R. Briggs, N. Gobron, V. Haverd, M. J. Paget, B. Pinty, and M. R. Raupach. 2014. Evaluation of six satellite-derived Fraction of Absorbed Photosynthetic Active Radiation (FAPAR) products across the Australian continent. Remote Sens Environ140:241-256.
55. Pinter, P. J. 1993. Solar angle independence in the relationship between absorbed PAR and remotely sensed data for alfalfa. Remote Sens Environ 46:19-25.
56. Pouliot, D., R. Latifovic, and I. Olthof. 2009. Trends in vegetation NDVI from 1 km AVHRR data over Canada for the period 1985-2006. Int J Remote Sens 30:149-168.
57. Price J. C. 1987. Calibration of satellite radiometers and the comparison of vegetation indices. Remote Sens Environ 21:15-27.
58. Propastin, P. and S. Erasmi. 2010. A physically based approach to model LAI from MODIS 250 m data in a tropical region. Int J App Earth Obs Geoinf 12:47-59.
59. Qi, J., A. S. Chehbouni, A. R. Huete, Y. H. Kerr, and S. Sorooshian. 1994. A modified soil adjusted vegetation index. Remote Sens Environ 48:119-126.
60. Roder, A., T. Kuemmerle, and J. Hill. 2005. Extension of retrospective datasets using multiple sensors. An approach to radiometric intercalibration of Landsat TM and MSS data. Remote Sens Environ 95:195-210.
61. Rondeaux, G., M. D. Steven, and F. Baret. 1996. Optimization of soil adjusted vegetation indices. Remote Sens Environ55:95-107.
62. Samain, O., B. Geiger, and J-L. Roujean. 2006. Spectral normalisation and fusion of optical sensors for the retrieval of BRDF and Albedo: Application to VEGETATION, MODIS, and MERIS data sets. IEEE Trans Geosci Remote Sens 44:3166-3179.
63. Schluessel, G., R. E. Dickinson, J. L. Privette, W. J. Emery, and R. Kokaly. 1994. Modeling the bidirectional reflectance distribution function of mixed finite plant canopies and soil. J Geophys Res-Atmos 99(D5):10577-10600.
64. Shultis, J. K. 1991. Calculated sensitivities of several optical radiometric indices for vegetation canopies. Remote Sens Environ 38:211-228.
65. Sims, D. A., A. F. Rahman, E. F. Vermote, and Z. Jiang. 2011. Seasonal and inter-annual variation in view angle effects on MODIS vegetation indices at three forest sites. Remote Sens Environ 115:3112-3120.
66. Song, Y., M. Ma, and F. Veroustraete. 2010. Comparison and conversion of AVHRR GIMMS and SPOT VEGETATION NDVI data in China. Int J Remote Sens 31:2377-2392.
67. Soudani, K., C. François, G. le Maire, V. Le Dantec, and E. Dufrêne. 2006. Comparative analysis of IKONOS, SPOT, and ETM+ data for leaf area index estimation in temperate coniferous and deciduous forest stands. Remote Sens Environ 102:161-175.
68. Steven, M. D. 1977. Standard distributions of clear sky radiance. Q J Roy Meteorol Soc 103:457-465.
69. Steven, M. D. 1998. The sensitivity of the OSAVI vegetation index to observational parameters. Remote Sens Environ 63:49-60.
70. Steven, M. D. 2004. Correcting the effects of field of view and varying illumination in spectral measurements of crops. Precis Agric 5:51-68.
71. Steven, M. D., P. V. Biscoe, and K. W. Jaggard. 1983. Estimation of sugar beet productivity from reflection in the red and infrared spectral bands. Int J Remote Sens 4:325-334.
72. Steven, M. D., P. V. Biscoe, K. W. Jaggard, and J. Paruntu. 1986. Foliage cover and radiation interception. Field Crops Res13:75-87.
73. Steven, M. D., T. J. Malthus, and F. Baret. 2007. Intercalibration of vegetation indices—An update. In M. E. Schaepman, S. Liang, N. Groot, and M. Kneubuhler (eds), 10th International Symposium on Physical Measurements and Spectral Signatures in Remote Sensing, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVI, Part 7/C50, ISPRS, Davos (CH), pp. 1682-1777.
74. Steven, M. D., T. J. Malthus, F. Baret, H. Xu, and M. Chopping. 2003. Intercalibration of vegetation indices from different sensor systems. Remote Sens Environ 88:412-422.
75. Steven, M. D. and M. H. Unsworth. 1980. The angular distribution and interception of diffuse solar radiation below overcast skies. Q J Roy Met Soc 106:57-61.
76. Sun, Z., Q. Wang, Z. Ouyang, M. Watanabe, B. Matsushita, and T. Fukushima. 2007. Evaluation of MOD16 algorithm using MODIS and ground observational data in winter wheat field in North China plain. Hydrol Proc 21:1196-1206.
77. Swinnen, E. and F. Veroustraete. 2008. Extending the SPOTVEGETATION NDVI time series (1998-2006) back in time with NOAA-AVHRR data (1985-1998) for Southern Africa. IEEE Trans Geosci Remote Sens 46:558-572.
78. Tang, Q., S. Peterson, R. H. Cuenca, Y. Hagimoto, and D. P. Lettenmaier. 2009. Satellite-based near-real-time estimation of irrigated crop water consumption. J Geophys Res114:D05114, doi:10.1029/2008JD010854.
79. Tarnavsky, E., S. Garrigues, and M. Brown. 2008. Multiscale geostatistical analysis of AVHRR, SPOT-VGT, and MODIS global NDVI products. Remote Sens Environ 112:535-549.
80. Teillet, P. M., B. L. Markham, and R. R. Irish. 2006. Landsat crosscalibration based on near simultaneous imaging of common ground targets. Remote Sens Environ 102:264-270.
81. Teillet, P. M. and X. Ren. 2008. Spectral band difference effects on vegetation indices derived from multiple satellite sensor data. Can J Remote Sens 34:159-173.
82. Townshend, J. R. G. and C. O. Justice. 1986. Analysis of the dynamics of African vegetation using the normalised difference vegetation index. Int J Remote Sens 7:1435-1445.
83. Trishchenko, A. P., J. Cihlar, and Z. Li. 2002. Effects of spectral response function on surface reflectance and NDVI measured with moderate resolution satellite sensors. Remote Sens Environ 81:1-18.
84. Tucker, C. J. 1977. Spectral estimation of grass canopy variables. Remote Sens Environ 6:11-26.
85. Tucker, C. J., J. H. Elgin, and J. E. McMurtrey. 1979. Temporal spectral measurements of corn and soybean crops. Photogramm Eng Remote Sens 45:643-653.
86. Tucker, C. J., J. E. Pinzon, M. E. Brown, D. A. Slayback, E. W. Pak, R. Mahoney, E. F. Vermote, and N. El Saleous. 2005. An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. Int J Remote Sens26:4485-4498.
87. Van Leeuwen, W. J. D. 2006. Spectral vegetation indices and uncertainty: Insights from a user’s perspective. IEEE Trans Geosci Remote Sens 44:1931-1933.
88. Van Leeuwen, W. J. D., A. R. Huete, and T. W Laing. 1999. MODIS vegetation index compositing approach: A prototype with AVHRR data. Remote Sens Environ 69:264-280.
89. Van Leeuwen, W. J. D., B. J. Orr, S. E. Marsh, and S. M. Herrmann. 2006. Multi-sensor data continuity: uncertainties and implications for vegetation monitoring applications. Remote Sens Environ 100:67-81.
90. Verhoef, W. 1985. Light scattering by leaf layers with application to canopy reflectance modeling: the SAIL model. Remote Sens Environ 16:125-141.
91. Vermote, E., C. O. Justice, and F-M. Breon. 2009. Towards a generalised approach for correction of the BRDF effect in MODIS directional reflectances. IEEE Trans Geosci Remote Sens 47:898-908.
92. Vermote, E. F., D. Tanre, J. L. Deuze, M. Herman, and J. J. Morcrette. 1997. Second simulation of the satellite signal in the solar spectrum: an overview. IEEE Trans Geosci Remote Sens 35:675-686.
93. Verreslst, J., M. E. Schaepman, B. Koetz, and M. Kneubühler. 2008. Angular sensitivity analysis of vegetation indices derived from CHRIS/PROBA data. Remote Sens Environ112:2341-2353.
94. Wiegand, C. L., A. J. Richardson, D. E. Escobar, and A.H. Gerbermann. 1991. Vegetation indices in crop assessments. Remote Sens Environ 35:105-119.
95. Zhang, Y., M. Xu, J. Adams, and X. Wang. 2009. Can Landsat imagery detect tree line dynamics. Int J Remote Sens30:1327-1340.
96. Zhou, X., H. Guan, H. Xie, and J. L. Wilson. 2009. Analysis and optimization of NDVI definitions and areal fraction models in remote sensing of vegetation. Int J Remote Sens30:721-751.