Retrieval of temporal profiles of reflectances from simulated and real NOAA-AVHRR data over heterogeneous landscapes

To carry out functioning and dynamic vegetation studies, a temporal analysis is needed. So far, only data provided by the National Oceanic and Atmospheric Administration (NOAA) satellites with Advanced Very High Resolution Radiometer (AVHRR) sensors offer the required temporal resolution, but their spatial resolution is coarse (1.1 km). But, in many situations, the vegetation cover is heterogeneous and the 1.1 km AVHRR pixel contains several types of land use radiometrically different and is, in fact, a mixed pixel. Thus, the reflectance and consequently deduced parameters (NDVI, LAI, etc.) measured by AVHRR is actually average value and does not represent a value for each vegetation class present in the pixel. The objective is to extract the reflectance of each vegetation class from the mixed pixel using NOAA-AVHRR data and SPOT-HRV data simultaneously which give the proportions of each type of vegetation inside the mixed pixel through a classification map. The paper presents a method for radiometrically unmixing coarse resolution signals through the inversion of linear mixture modelling on heterogeneous regions of natural vegetation (Bidi-Bahn) in Burkina-Faso and in Niger (Hapex site). In a first step, simulated coarse resolution data (NOAA-AVHRR) obtained from the degradation of SPOT images are used to assess the method. In a second step, real NOAA-AVHRR data are used and some elements of validation are given by comparing the results to airborne reflectance measurements.

[1]  P. Jarvis,et al.  CHAPTER 1 – PREDICTING EFFECTS OF VEGETATION CHANGES ON TRANSPIRATION AND EVAPORATION , 1983 .

[2]  F. Woodward.  Climate and plant distribution , 1987 .

[3]  S. Running,et al.  A general model of forest ecosystem processes for regional applications I. Hydrologic balance, canopy gas exchange and primary production processes , 1988 .

[4]  J. C. Price.  Using spatial context in satellite data to infer regional scale evapotranspiration , 1990 .

[5]  C. Valentin,et al.  Land surface conditions of the Niamey region: ecological and hydrological implications , 1997 .

[6]  R. R. Lamacraft,et al.  Calibration of LANDSAT data for sparsely vegetated semi-arid rangelands , 1986 .

[7]  Guy Flouzat,et al.  Robustness of linear mixture modeling using low spatial resolution data , 1995, Remote Sensing.

[8]  B. Huntley,et al.  Ecology of Tropical Savannas , 1987, Ecological Studies.

[9]  J. Settle,et al.  Linear mixing and the estimation of ground cover proportions , 1993 .

[10]  C. Vignolles,et al.  Validation of the use of multiple linear regression as a tool for unmixing coarse spatial resolution images , 1994 .

[11]  Stephen D. Prince,et al.  Spectral modelling of multicomponent landscapes in the Sahel , 1991 .

[12]  G. Asrar,et al.  Estimating Absorbed Photosynthetic Radiation and Leaf Area Index from Spectral Reflectance in Wheat1 , 1984 .

[13]  J. C. Price,et al.  Estimating leaf area index from satellite data , 1993, IEEE Trans. Geosci. Remote. Sens..

[14]  S. Cherchali,et al.  Linear mixture modelling applied to AVHRR data for monitoring vegetation , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[15]  D. Vidal-Madjar,et al.  Evapotranspiration over an agricultural region using a surface flux/temperature model based on NOAA-AVHRR data , 1986 .

[16]  M. R. Raupach.  Vegetation-atmosphere interaction in homogeneous and heterogeneous terrain: some implications of mixed-layer dynamics , 1991 .