The long-time series vegetation index data set of China is mainly aimed at the normalized vegetation index (NDVI), which is based on the spectral reflectance of four bands synthesized every 10 days with a spatial resolution of 1km from April 1, 1998 to December 31, 2011 and the 10 day maximum NDVI data set.
The long-time series vegetation index data set of China is mainly aimed at the normalized vegetation index (NDVI), which is based on the spectral reflectance of four bands synthesized every 10 days with a spatial resolution of 1km from April 1, 1998 to December 31, 2011 and the 10 day maximum NDVI data set. The spot-vegetation-ndvi dataset contains. Zip compressed files with ten day time resolution from April 1, 1998 to December 31, 2011. Decompress esri-grid file every 10 days. The naming rule of spo-vegetation-ndvi dataset is: v-yymmdd, where V is the abbreviation of vegetation, yymmdd means the date of the day of the file, and it is also the main identification to distinguish other files.
Vegetation sensor was launched from SPOT-4 in March 1998, and received the sp0t VGT data for global vegetation coverage observation from April 1998. It has a very perfect and efficient image ground processing mechanism system. Vegetation data is mainly received by Kiruna ground station in Sweden, image quality monitoring center in Toulouse in France is responsible for image quality and providing relevant parameters (such as calibration coefficient). Finally, image processing and archiving center of Vito Research Institute in Belgium is responsible for global vegetation data archiving and user orders. Among them, vgt-p (prototype) data products mainly provide researchers with high-quality physical quantity prototype data to facilitate their research and construction of algorithms and application models. After strict system error correction and resampling, the data is projected by the longitude and latitude net. The pixel resolution is LKM, and the pixel brightness value is the reflectivity of the ground object on the top of the atmosphere. In addition to providing the original data of four bands, it also provides relevant auxiliary parameters according to the user's needs, such as the atmospheric conditions, system information (the sun's sky bottom angle, azimuth angle, field angle and receiving time) and terrain data. Vgt-s (synthesis) products provide atmospheric corrected surface reflectance data, and use multi band synthesis technology to obtain LKM resolution normalized vegetation index (W) data set. Vgi-s products include four band spectral reflectance and NDVI data set (S1) synthesized every day, four band spectral reflectance synthesized every 10 days and 10 day maximum NDVI data set (S10) to reduce the impact of cloud and BRDF, while S10 is also resampled into 4km resolution (s10.4) and 8km resolution (s10.8) data set. Vgt-s products are widely used for their high time resolution. This dataset contains the spectral reflectance of four bands synthesized every 10 days and the 10 day maximum NDVI dataset (S10). The preprocessing of spot source data includes atmospheric correction, radiometric correction and geometric correction. The NDVI data of 10 d maximum synthesis is generated, and the value from - 1 to - 0.1 is set to - 0.1, and then the formula is used
An important feature of vegetation index products is that they can be converted into canopy biophysical parameters. Vegetation index (Ⅵ) also plays an "intermediate variable" role in the acquisition of biophysical parameters of vegetation (such as Lai, green cover, and fAPAR). At present, the relationship between vegetation index and biophysical parameters of vegetation is being studied by using the data sets of representative ground, aircraft and satellite observations. These data can be used to evaluate the performance of VI algorithm before satellite launch, and also provide the conversion coefficient between vegetation index products and canopy biophysical characteristics. The use of biophysical data is part of the vegetation index validation program. Vegetation index products will play a major role in several earth observation system of systems (EOS) studies, and are also part of global and regional biosphere model products in recent years.
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