The effect of surface anisotropy and viewing geometry on the estimation of NDVI from AVHRR

Abstract Terrestrial surfaces are observed routinely from space using the AVHRR instrument on the NOAA satellites. Observations in the red and near‐infrared spectral bands are used to compute vegetation indices (such as the NDVI), which are then interpreted in terms of various vegetation properties. Orbital and engineering constraints severely limit the range of illumination and viewing angles under which various ecosystems are observed. Since terrestrial surfaces are anisotropic, all spectral reflectance measurements obtained with a small instantaneous field of view instrument are specific to these angular conditions, and the value of the corresponding NDVI, computed from these bidirectional reflectances, is relative to the particular geometry of illumination and viewing at the time of the measurement. This paper documents the importance of these geometric effects through simulations of the AVHRR data acquisition process, and investigates the systematic biases that result from the combination of ecosyste...

[1]  H. Rahman,et al.  Coupled surface‐atmosphere reflectance (CSAR) model: 1. Model description and inversion on synthetic data , 1993 .

[2]  Bernard Pinty,et al.  Towards a quantitative interpretation of vegetation indices Part 1: Biophysical canopy properties and classical indices , 1993 .

[3]  B. Pinty,et al.  On the design and validation of surface bidirectional reflectance and albedo models , 1992 .

[4]  Garik Gutman,et al.  Vegetation indices from AVHRR: An update and future prospects , 1991 .

[5]  W. Dulaney,et al.  Normalized difference vegetation index measurements from the Advanced Very High Resolution Radiometer , 1991 .

[6]  F. Baret,et al.  validation d'un modèle de réflectance spectrale et directionnelle de sol , 1991 .

[7]  Ranga B. Myneni,et al.  Photon-Vegetation Interactions , 1991, Springer Berlin Heidelberg.

[8]  B. Pinty,et al.  A physical model of the bidirectional reflectance of vegetation canopies , 1990 .

[9]  R. Dickinson,et al.  A physical model of the bidirectional reflectance of vegetation canopies: 2. Inversion and validation , 1990 .

[10]  Piers J. Sellers,et al.  A Global Climatology of Albedo, Roughness Length and Stomatal Resistance for Atmospheric General Circulation Models as Represented by the Simple Biosphere Model (SiB) , 1989 .

[11]  R. Myneni,et al.  Estimation of plant-canopy attributes from spectral reflectance measurements , 1989 .

[12]  A. Kuusk,et al.  A reflectance model for the homogeneous plant canopy and its inversion , 1989 .

[13]  F. Baker,et al.  The International Geosphere-Biosphere Programme (IGBP): A Study of Global Change , 1988, Environmental Conservation.

[14]  Garik Gutman,et al.  The derivation of vegetation indices from AVHRR data , 1987 .

[15]  Y. J. Kaufman,et al.  The effect of subpixel clouds on remote sensing , 1987 .

[16]  Paul N. Woessner,et al.  Polarization of light scattered by clover , 1987 .

[17]  P. Sellers.  Canopy reflectance, photosynthesis, and transpiration. II. the role of biophysics in the linearity of their interdependence , 1987 .

[18]  Christopher O. Justice,et al.  Monitoring East African vegetation using AVHRR data , 1986 .

[19]  B. Holben.  Characteristics of maximum-value composite images from temporal AVHRR data , 1986 .

[20]  C. J. Tucker,et al.  Relationship between atmospheric CO2 variations and a satellite-derived vegetation index , 1986, Nature.

[21]  P. Sellers.  Canopy reflectance, photosynthesis and transpiration , 1985 .

[22]  A. Henderson‐sellers,et al.  A global archive of land cover and soils data for use in general circulation climate models , 1985 .

[23]  D. Kimes.  Modeling the directional reflectance from complete homogeneous vegetation canopies with various leaf-orientation distributions , 1984 .

[24]  L. Biehl,et al.  Soybean canopy reflectance modeling data sets , 1984 .

[25]  E. Matthews.  Global Vegetation and Land Use: New High-Resolution Data Bases for Climate Studies , 1983 .

[26]  J. A. Gatlin,et al.  Monitoring vegetation in the Nile Delta with NOAA-6 and NOAA-7 AVHRR imagery , 1982 .

[27]  C. Tucker.  Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[28]  J. Goudriaan,et al.  Crop Micrometeorology: A Simulation Study , 1977 .

[29]  D. Deering.  Measuring forage production of grazing units from Landsat MSS data , 1975 .

[30]  L. D. Miller,et al.  Remote mapping of standing crop biomass for estimation of the productivity of the shortgrass prairie, Pawnee National Grasslands, Colorado , 1972 .