Inversion of aerosol optical depth in Agriculture region based on the support of Spectrum database

Vegetation Index (VI) and Leaf Area Index (LAI) are very important parameters for crop growth situation monitoring and crop yield estimation. However, it is not easy to get accurate VI or LAI. One of the reasons is because of the difficulty in the inversion of aerosol optical depth (AOD), which is the key factor in atmospheric correction. This study addresses an algorithm of AOD inversion in Agriculture region based on the support of Spectrum database. It is usually supposed that we can get the surface reflectance of blue band for most of the algorithm of AOD inversion. As the Dense Dark Vegetation (DDV) method, the surface reflectance in blue and red bands is calculated from the reflectance at 2.1 or 3.8 mum band. However, it is not easy to retrieve the AOD value of each pixel for a whole satellite image because of the unknown surface reflectance on some regions such as the sparse vegetation area. For agriculture area, the surface reflectance varies from bare soil, sparse vegetation, and then Dense Dark Vegetation, during the whole crop growth period. We have carried out a series of field spectrum measurement during different crop growth period and set up a crop spectrum database. By analyzing the soil, the leaf and the canopy spectra, we selected a set of models to calculate the surface reflectance of agriculture region during different crop growth period, which include bare soil model, sparse vegetation model and continuous vegetation model. Then, the surface condition is put to the atmospheric radiation transfer model to calculate Look-up Table (LUT) for MODIS bands, which is used to retrieve the AOD value of MODIS image. North China Plain is selected as the experiment area, the AOD value measured by sun-photometer is taken as true value to evaluate the inversion algorithm´s accuracy and the results show good agreement