Intercalibration of vegetation indices from different sensor systems

被引:332
作者
Steven, MD [1 ]
Malthus, TJ
Baret, F
Xu, H
Chopping, MJ
机构
[1] Univ Nottingham, Sch Geog, Nottingham NG7 2RD, England
[2] Univ Edinburgh, Sch Geosci, Edinburgh EH8 9XP, Midlothian, Scotland
[3] INRA, Unite Bioclimatol, F-84194 Avignon 9, France
[4] NOAA, NESDIS, ORA, IMSG, Camp Springs, MD 20746 USA
[5] USDA ARS, Las Cruces, NM 88003 USA
关键词
vegetation index; sensor systems; spectroradiometric measurements;
D O I
10.1016/j.rse.2003.08.010
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Spectroradiometric measurements were made over a range of crop canopy densities, soil backgrounds and foliage colour. The reflected spectral radiances were convoluted with the spectral response functions of a range of satellite instruments to simulate their responses. When Normalised Difference Vegetation Indices (NDVI) from the different instruments were compared, they varied by a few percent, but the values were strongly linearly related, allowing vegetation indices from one instrument to be intercalibrated against another. A table of conversion coefficents is presented for AVHRR, ATSR-2, Landsat MSS, TM and ETM+, SPOT-2 and SPOT-4 HRV, IRS, IKONOS, SEAWIFS, MISR, MODIS, POLDER, Quickbird and MERI S (see Appendix A for glossary of acronyms). The same set of coefficients was found to apply, within the margin of error of the analysis, for the Soil Adjusted Vegetation Index SAVI. The relationships for SPOT vs. TM and for ATSR-2 vs. AVHRR were directly validated by comparison of atmospherically corrected image data. The results indicate that vegetation indices can be interconverted to a precision of 1-2%. This result offers improved opportunities for monitoring crops through the growing season and the prospects of better continuity of long-term monitoring of vegetation responses to environmental change. (C) 2003 Elsevier Inc. All rights reserved.
引用
收藏
页码:412 / 422
页数:11
相关论文
共 29 条
[1]  
[Anonymous], 1990, PRINCIPLES ENV PHYS
[2]  
BEGNI G, 1982, PHOTOGRAMM ENG REM S, V48, P1613
[3]  
CHOPPING MJ, 1998, THESIS U NOTTINGHAM
[4]  
GALLO KP, 1988, PHOTOGRAMM ENG REM S, V54, P485
[5]   DIFFERENCES IN VEGETATION INDEXES FOR SIMULATED LANDSAT-5 MSS AND TM, NOAA-9 AVHRR, AND SPOT-1 SENSOR SYSTEMS [J].
GALLO, KP ;
DAUGHTRY, CST .
REMOTE SENSING OF ENVIRONMENT, 1987, 23 (03) :439-452
[6]   An adequate band positioning to enhance NDVI contrasts among green vegetation, senescent biomass, and tropical soils [J].
Galvao, LS ;
Vitorello, I ;
Pizarro, MA .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2000, 21 (09) :1953-1960
[7]   MODIS NDVI optimization to fit the AVHRR data series spectral considerations [J].
Gitelson, AA ;
Kaufman, YJ .
REMOTE SENSING OF ENVIRONMENT, 1998, 66 (03) :343-350
[8]   Multi-sensor analysis of NDVI, surface temperature and biophysical variables at a mixed grassland site [J].
Goetz, SJ .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 1997, 18 (01) :71-94
[9]   OBJECTIVE ASSESSMENT OF THE NOAA GLOBAL VEGETATION INDEX DATA PRODUCT [J].
GOWARD, SN ;
DYE, DG ;
TURNER, S ;
YANG, J .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 1993, 14 (18) :3365-3394
[10]   EFFECT OF RADIOMETRIC CORRECTIONS ON NDVI-DETERMINED FROM SPOT-HRV AND LANDSAT-TM DATA [J].
GUYOT, G ;
GU, XF .
REMOTE SENSING OF ENVIRONMENT, 1994, 49 (03) :169-180