This dataset contains surface temperature data of China (approximately 9.6 million square kilometers of land) from 2003 to 2017, measured in degrees Celsius with a monthly time resolution and a spatial resolution of 5600 meters. By combining MODIS daily data (MOD11C1 and MYD11C1), monthly data (MOD11C3 and MYD11C3), and meteorological station data, the true LST under cloud coverage in monthly LST images was reconstructed, and a regression analysis model was constructed to further improve the accuracy of six natural zones under different climate conditions. Accuracy analysis shows that the reconstruction results are closely related to the on-site measurement results, with an average RMSE of 1.39 ℃, MAE of 1.30 ℃, and R2 of 0.97.
Two files:
1) Document description file: 00_Setadata for LSTC.docx;
2) Dataset file: 01_LSTC. zip, containing 15 folders. The file formats include: * TIF (LSTC image) and *.TFW (TIFF image coordinate information).
MODIS daily data (MOD11C1 and MYD11C1), monthly data (MOD11C3 and MYD11C3), and meteorological station data. MODIS data download website: https://ladsweb.modaps.eosdis.nasa.gov
The dataset is mainly generated by integrating MODIS daily data (MOD11C1 and MYD11C1), monthly data (MOD11C3 and MYD11C3), and meteorological station data to reconstruct the real LST under cloud coverage of monthly scale LST images, and then constructing a regression analysis model to further improve accuracy.
Accuracy analysis shows that the reconstruction results are closely related to the on-site measurement results, with an average RMSE of 1.39 ℃, MAE of 1.30 ℃, and R2 of 0.97.
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.NCDC.ZENODO.DB6681.2024
10.5281/zenodo.3528024
