EFFECT OF RADIOMETRIC CORRECTIONS ON NDVI-DETERMINED FROM SPOT-HRV AND LANDSAT-TM DATA

被引:64
|
作者
GUYOT, G
GU, XF
机构
关键词
D O I
10.1016/0034-4257(94)90012-4
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The normalized difference vegetation index (NDVI), which is generally considered as an index minimizing the radiometric errors on image data has to be corrected radiometrically when a quantitative analysis is performed. In this article, the main factors affecting NDVI are analyzed: proper characteristics (MTF) and absolute calibration of the satellite sensor, Sun zenith angle, Earth-Sun distance, and atmospheric condition. The effects of these factors are theoretically and practically analyzed on two SPOT-HRV and Landsat-TM images acquired the same day over the same area in southeast France. Some simplified correction methods are proposed. The results show that: i) The conversion of digital counts into apparent reflectance is the most important step for NDVI correction. Without this correction, a relatively constant error affects NDVI depending on the sensor considered (- 0.18 for SPOT-HRV and - 0.10 for Landsat TM). ii) The MTF correction does not affect the average NDVI value; its interest is to restore the radiometric level of individual pixels that have a large contrast with their surroundings. iii) The atmospheric effects are similar in the homologous spectral bands of SPOT-HRV and Landsat TM. Their correction increases the dynamic range of NDVI variation (around 24% in the example presented) and consequently the contrast between different targets. The effect of the noncoincidence of SPOT-HRV and Landsat-TM spectral bands is also studied. This effect can be considered either as a source of error or as a supplementary source of information. An example shows that the combination of the spectral information given by the two satellites can be used to improve the discrimination of some targets such as bare soil and soil with a low vegetation density.
引用
收藏
页码:169 / 180
页数:12
相关论文
共 41 条
  • [21] Twelve years of vegetation cover monitoring from Landsat-TM data in Languedoc, southern France
    Caraux-Garson, D
    Hoff, C
    Lacaze, B
    Sommer, S
    Mehl, W
    Hill, J
    OPERATIONAL REMOTE SENSING FOR SUSTAINABLE DEVELOPMENT, 1999, : 45 - +
  • [22] ANALYSIS OF VEGETATION INDEXES FROM LANDSAT TM AND SPOT XS DATA
    MOREIRA, MA
    NITZSCHE, RP
    PESQUISA AGROPECUARIA BRASILEIRA, 1991, 26 (10) : 1583 - 1588
  • [23] On the Use of the Principal Component Analysis (PCA) for Evaluating Vegetation Anomalies from LANDSAT-TM NDVI Temporal Series in the Basilicata Region (Italy)
    Lanorte, Antonio
    Manzi, Teresa
    Nole, Gabriele
    Lasaponara, Rosa
    COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2015, PT IV, 2015, 9158 : 204 - 216
  • [24] Comparison of the potential of IRS-1C, SPOT and Landsat-TM multispectral and panchromatic data for forest area classification in northeastern Switzerland
    Kellenberger, TW
    IGARSS '98 - 1998 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS 1-5: SENSING AND MANAGING THE ENVIRONMENT, 1998, : 870 - 872
  • [25] COMPARATIVE-ANALYSIS OF LANDSAT-5 TM AND SPOT HRV-1 DATA FOR USE IN MULTIPLE SENSOR APPROACHES
    HILL, J
    AIFADOPOULOU, D
    REMOTE SENSING OF ENVIRONMENT, 1990, 34 (01) : 55 - 70
  • [26] The forest-savanna dynamics from multi-date Landsat-TM data in Sierra Parima, Venezuela
    Guerra, F
    Puig, H
    Chaume, R
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 1998, 19 (11) : 2061 - 2075
  • [27] Monitoring daily evapotranspiration at a regional scale from Landsat-TM and ETM+ data:: Application to the Basilicata region
    Sanchez, J. M.
    Scavone, G.
    Caselles, V.
    Valor, E.
    Copertino, V. A.
    Telesca, V.
    JOURNAL OF HYDROLOGY, 2008, 351 (1-2) : 58 - 70
  • [28] Roughness parameter derivation from ERS-1 and Landsat-TM satellite data for the agglomeration of Basel/Switzerland
    Scherer, D
    Parlow, E
    Beha, HD
    PROGRESS IN ENVIRONMENTAL REMOTE SENSING RESEARCH AND APPLICATIONS, 1996, : 325 - 329
  • [29] STRUCTURAL CHARACTERIZATION OF CANOPIES OF Eucalyptus spp. USING RADIOMETRIC DATA FROM TM/Landsat 5
    Ferraz Pacheco, Ludmila Roque
    Ponzoni, Flavio Jorge
    dos Santos, Sandra Benfica
    Andrades Filho, Clodis de Oliveira
    Mello, Marcio Pupin
    Campos, Rogerio Costa
    CERNE, 2012, 18 (01) : 105 - 116
  • [30] Evaluation of fuzzy and texture-based classification approaches for mapping regenerating tropical forest classes from landsat-TM data
    Palubinskas, G.
    Lucas, R.M.
    Foody, G.M.
    Curran, P.J.
    International Journal of Remote Sensing, 1995, 16 (04)