The vegetation index mainly reflects the difference between vegetation reflection in visible and near-infrared bands and soil background. Under certain conditions, each vegetation index can be used to quantitatively indicate the growth status of vegetation. At present, Normalized Difference Vegetation Index (NDVI) is an important data source for detecting vegetation growth status, vegetation coverage, and eliminating some radiation errors.
NDVI can reflect the background influence of plant canopy, such as soil, moist ground, snow, dead leaves, roughness, etc., and is related to vegetation cover. It is one of the important parameters reflecting the growth and nutritional information of crops. Based on this parameter, the nitrogen requirements of crops in different seasons can be determined, which plays an important guiding role in the rational application of nitrogen fertilizers.
Based on the MODIS MOD13A2 dataset, segmented images covering Gansu Province will be processed using MRT tools and Python language code for batch stitching, projection conversion, cropping, etc., to generate MODIS MOD13A2 NDVI data for Gansu Province from 2018 to 2022. The spatial resolution of this dataset is 1km, and the temporal resolution is 16 days.
The data source of this dataset is MOD13A2-v005 version data, which is sourced from the NASA official website（ https://ladsweb.modaps.eosdis.nasa.gov ）.
(1) Run the MRT tool to generate prm files for MOD13A2 NDVI data concatenation and projection conversion. The spatial resolution is 1000 meters.
(2) Generate a batch file using MATLAB language program to call the MRT tool and run it;
(3) Utilize the vector boundary of Gansu Province, perform batch cropping using Python, and finally output and save in GeoTIFF format.
The quality of this data set is consistent with that of the source data set MODIS mod13a2.005. The valid range of data is - 2000 to 10000, the scaling factor is 0.0001, and the filling value is - 3000.
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.NCDC.GSEER.DB4129.2023
10.12072/ncdc.gseer.db4129.2023
