Enhanced Vegetation Index (EVI) is improved out of Normalized Vegetation Index (NDVI), a comprehensive atmospheric correction based on the image factors included in the atmospheric correction atmospheric molecules, aerosols, thin clouds, water vapor, and ozone, etc., EVI atmospheric correction is divided into three steps, and the first step is the de-clouded processing. The second step is the atmospheric correction processing, the correction includes atmospheric molecules, aerosols, water vapor and so on, in addition to the Rayleigh scattering and ozone that already exist in NDVI. The third step is further processing of residual aerosol effects by means of the difference between blue and red light passing through the aerosol. Since the input NIR, Red, and Blue have been subjected to relatively stringent atmospheric corrections, there is no need to use a vegetation index based on the NIR/Red ratio in order to eliminate multiplicative noise when designing the vegetation index equations, and thus the resulting problems of easy saturation of the vegetation index and the lack of a linear relationship with the actual vegetation cover have been solved.
EVI is more sensitive to changes in canopy structure including leaf area index (LAI), canopy type, vegetation phase and canopy structure.
Based on the MODIS MOD13A2.005 Enhanced Vegetation Index (EVI) dataset, the split-format images covering the Weihe River Basin were processed by batch splicing, projection transformation, cropping, etc., using the MRT tool and the Python language code, to generate the MODIS MOD13A2 EVI data of the Weihe River Basin for the years 2000-2020. The spatial resolution of this dataset is 1 km. The spatial resolution of this dataset is 1 km, and the temporal resolution is 16 days.
The data source for this dataset is MOD13A2.v005 version data from the official NASA website (https://ladsweb.modaps.eosdis.nasa.gov).
(1) Trial run the MRT tool to generate prm files for MOD13A2 EVI data splicing and projection conversion with 1000 m spatial resolution.
(2) Generate the batch file for calling MRT tool using MATLAB language program and run it.
(3) Using the vector boundaries of the Weihe River Basin, steps such as Python batch cropping were used, and finally the output was saved in GeoTIFF format.
This dataset is consistent in quality with the source dataset MODIS MOD13A2.005. The data has a valid range of -2000 to 10000, a scaling factor of 0.0001, and a fill value of -3000.
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CSTR:11738.11.ncdc.WRiver.2021.21
10.12072/ncdc.WRiver.db0023.2021