The preparation of this data set is based on the proposed downscaling method of all-weather surface temperature data for the glacier area in Southeast Tibet. By analyzing the relationship between all-weather surface temperature and its spatio-temporal influence factor elevation, surface coverage type, vegetation index, snow cover index, surface reflectance and other data, a downscaling model of all-weather surface temperature is constructed, which increase the spatial resolution of all-weather surface temperature products from 1 km to 250 m. The validation results show that the RMSE of downscaling surface temperature at the site is about 2.25 K and 2.16 K in the daytime and at night, respectively, which is about 0.5 K higher than that of the original 1 km surface temperature product. The results of image quality index show that the downscaling surface temperature not only obtains a lot of detailed thermal information, but also maintains a high consistency with the original 1 km surface temperature in spatial pattern and amplitude. This data set has certain significance for high resolution all-weather surface temperature generation and disaster monitoring in glacier area of Southeast Tibet.

File naming and required software

Daily 250 m all-weather land surface temperature dataset in Southeast Tibet(2011) is stored in GeoTIFF format, and each GeoTIFF file is about 11 MB. The data is stored in day and night folders respectively. The specific file naming method is "DOY. TIF", where DOY stands for the annual product day minus 1, such as 0.tif stands for the first day of 2011.
The data format is integer
Usage: GIS software or MATLAB and other software can be directly used for reading and subsequent processing
Data resolution: twice a day, 250 m
Data time: every day in 2011
Projection method: Albert equal area
units = "K"

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Cite as:

Zhou, J., Huang, Z., Zhong, H., Tang, W. (2022). Daily 250 m all-weather land surface temperature dataset in Southeast Tibet（2011）. A Big Earth Data Platform for Three Poles, DOI: 10.11888/RemoteSen.tpdc.271979. CSTR: 18406.11.RemoteSen.tpdc.271979. (Download the reference： RIS | Bibtex )

Related Literatures:

1. Ma, J., Zhou, J., & Göttsche, F.-M, et al. (2020). A global long-term (1981-2000) land surface temperature product for NOAA AVHRR. Earth System Science Data, 12, 3247-3268.( View Details | Bibtex)

2. Zhang, X., Zhou, J., & Liang, S., et al. (2020). Estimation of 1-km all-weather remotely sensed land surface temperature based on reconstructed spatial-seamless satellite passive microwave brightness temperature and thermal infrared data. ISPRS Journal of Photogrammetry and Remote Sensing, 167, 321-344.( View Details | Bibtex)

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

Support Program

Integration and Demonstration of Monitoring and Early Warning Technology and Equipment for Debris Flow in Complex Mountainous Areas (No:2018YFC1505205)

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