4.7 Article

Prototyping of MISR LAI and FPAR algorithm with POLDER data over Africa

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IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/36.868895

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fraction of photosynthetically active radiation; absorbed by vegetation (FPAR); leaf area index (LAI); multi-angle imaging spectroradiometer (MISR); multi-angle remote sensing; polarization and directionality of the Earth's; reflectance (POLDER); terra

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The multi-angle imaging spectroradiometer (MISR) instrument is designed to provide global imagery at nine discrete viewing angles and four visible/near-infrared spectral hands. The MISR standard products include vegetation canopy green leaf area index (LAI) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR), These products are produced using a peer-reviewed algorithm documented in the EOS-AMI (Terra) special issue of the Journal of Geophysical Research. This paper presents results on spatial distributions of LAI and FPAR of vegetated land surfaces derived from the MISR LAI/FPAR algorithm with bidirectional reflectance data from the polarization and directionality of the Earth's reflectance (POLDER) instrument over Africa. The results indicate that the proposed algorithm reflects the physical relationships between surface reflectances and biophysical parameters and demonstrates the advantages of using multi-angle data instead of single-angle data. A new method for evaluating bihemispherical reflectance (BHR) from multi-angle measurements of hemispherical directional reflectance factor (HDRF) was developed to prototype the algorithm with POLDER data. The accuracy of BHR evaluation and LAI/FPAR estimation is also presented, To demonstrate the advantages of using multi-angle data over single-angle data of surface reflectance, we demonstrate that: 1) the use of multi-angle data can decrease the dispersion and saturation of LAI, and increase the localization and quality of retrieved LAI and FPAR, 2) the use of multi-angle data can improve the accuracy of LAI retrievals in geometrically complex canopies such as shrubs, and 3) the use of multi-angle data can help determine biome or Land cover types correctly (by using the minimum value of LAI dispersion), For many other cases, we demonstrate that the use of multi-angle data does not lead to misevaluation, even if the land cover type is misidentified.

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