Calculating NDVI for NOAA/AVHRR data after atmospheric correction for extensive images using 6S code: A case study in the Marsabit District, Kenya

摘要

A detailed atmospheric correction method for NOAA/AVHRR images using 6S code, easily accessible data sets, and the images themselves is proposed. The parameters that 6S requires (aerosol optical depth, precipitable water, ozone content, and elevation) were obtained using data from the images, the Total Ozone Mapping Spectrometer, and the GTOPO30 elevation data set, with reference to existing studies. The proposed methodology is validated through a case study of the Marsabit District, northern Kenya, which includes a broad range of precipitation, elevation, and vegetation types. The Normalized Difference Vegetation Index (NDVI) of desert, grassland, and forested areas from August 1987 to August 1988 was calculated after making the atmospheric correction. The intercept of the regression line, between the reflectance of before and after correction, is almost the same for each land cover type; while the slope is around 1.7 to 1.8 for grassland/bushland, it is smaller in the desert, where the range of the NDVI is limited. The NDVI in dense vegetation is more sensitive to the atmospheric correction, which is a result of the effect of path radiance. After the atmospheric correction, the range of NDVI increased, with the characteristic that the greater the NDVI, the larger was the atmospheric effect. In the case study, as well, the NDVI increased after the atmospheric correction, especially in pixels with initially high NDVI. A more detailed, entirely pixel-by-pixel, atmospheric correction requires individual pixel information for aerosol optical depth and precipitable water. This will be possible using data collected by the recent sensors such as MODIS.