Generating and Evaluation Leaf Area Index (LAI) from MODIS MultiAngle Implementation of Atmospheric Correction (MAIAC) Surface Reflectance Dataset

Abstract:

This study generates and evaluates prototype Leaf Area Index (LAI) product based on MODerate resolution Imaging Spectroradiometer’s (MODIS) Bidirectional Reflectance Factor (BRF, commonly known as surface reflectance) which is a product of MultiAngle Implementation of Atmospheric Correction (MAIAC) package. LAI is a key parameter of vegetation in characterizing interactions of energy and mass between the Earth's surface and atmosphere. On the other hand, MAIAC BRF is retrieved from a new atmospheric correction algorithm, which has higher spatial resolution and is believed to have more reliable cloud/aerosol detection technique than standard MODIS BRF product. Two main objectives of this study are: 1). Maintaining the radiative transfer theory based LAI algorithm’s look up table (LUT) unchanged, to compare LAI product retrieved from different versions of BRF products (MODIS collection 5, collection 6 and MAIAC); 2). To adjust the LUT to resolve LAI’s possible systematic discrepancies resulting from atmospheric correction methods within the input BRF other than our LAI algorithm. Before the LUT adjusting, comparing to standard MODIS products shows that MAIAC LAI product will overestimate among herbaceous biome types which have low LAI values, while underestimate among woody biome types which have relatively higher values. Based on the theory of radiative transfer of canopy spectral invariants, two biome and MAIAC specific configurable parameters (Single Scattering Albedo and Uncertainty) in the LUT are adjusted to minimize the inconsistency due to input BRFs. Experiments shows that our new result: 1). has good agreement with field measured data (e.g. DIRECT); 2) is consistent with standard MODIS LAI product.