1km seamless land surface temperature dataset of China (2002-2020)- A Big Earth Data Platform for Three Poles

Kilometer-level spatially complete (seamless) land surface temperature products have a wide range of applications needs in climate change and other fields. Satellite retrieved LST has high reliability. Integrating the LST retrieved from thermal infrared and microwave remote sensing observation is an effective way to obtain the SLT with certain accuracy and spatial integrity. Based on this guiding ideology, the author developed a framework for retrieving 1km and seamless LST over China landmass, and generated the LST data set accordingly (2002-2020)

Firstly, a look-up table based empirical retrieval algorithm is developed for retrieving microwave LST from AMSR-E/AMSR2 observations. Then, AMSR-E/AMSR2 LST is downscaled by using geographic weighted regression to obtain 1km LST. Finally, the multi-scale Kalman filter is used to fuse AMSR-E/AMSR2 LST and MODIS LST to generate a 1km seamless LST data set.

The ground valuation results show that the root mean square error (RMSE) of the 1km seamless LST is about 3K. In addition, the spatial distribution of the 1km seamless LST is consistent with MODIS LST and CLDAS LST.

File naming and required software

File naming convention: MYD.ALLSKY.LST.yyyymmdd.flag.hdf (yyyymmdd: year, month, day, flag: identification of day and night, with values of 'Day' or 'Night', representing day and night respectively). For example, MYD.ALLSKY.LST.20100101.Day.hdf represents the surface temperature in the day on January 1, 2010.
Data format:. HDF
Data Description: each HDF file contains four sub datasets: Latitude, Longitude, Lst and Lst _ QC indicates latitude, longitude, land surface temperature products and quality control file respectively
Latitude: latitude data of the product. The data type is 64 byte floating-point type, and the data unit is degrees,the filling value is 999;
Longitude: longitude data of the product, the data type is 64 byte floating-point type, and the data unit is degrees,the filling value is 999;
Lst: all-weather surface temperature results, the data type is 16 byte unsigned integer, the data unit is k, the filling value is 0, scale is 0.02, offset is 0, that is, the real LST = LST * 0.02;
Lst_ QC: quality identification of all-weather surface temperature. See the data description document for the specific value meaning. The data type is 8-byte unsigned integer and the filling value is 255.
Data reading mode: it is stored in HDF format and can be processed by ArcGIS and other software or MATLAB
Data version No.: v1

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Cite as:

Cheng, J., Dong, S., Shi, J. (2021). 1km seamless land surface temperature dataset of China (2002-2020). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Meteoro.tpdc.271657. CSTR: 18406.11.Meteoro.tpdc.271657. (Download the reference： RIS | Bibtex )

Related Literatures:

1. Xu, S., & Cheng, J. (2021). A new land surface temperature fusion strategy based on cumulative distribution function matching and multiresolution Kalman filtering. Remote Sensing of Environment, 254, 112256( View Details | Bibtex)

2. Zhang, Q., Wang, N., Cheng, J., & Xu, S. (2020). A Stepwise Downscaling Method for Generating High-Resolution Land Surface Temperature From AMSR-E Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 5669-5681( View Details | Bibtex)

3. Zhang, Q., & Cheng, J. (2020). An Empirical Algorithm for Retrieving Land Surface Temperature From AMSR-E Data Considering the Comprehensive Effects of Environmental Variables. Earth and Space Science, 7, e2019EA001006. https://doi.org/10.1029/2019EA001006( 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

Second Tibetan Plateau Scientific Expedition Program

2nd survey of Tibet plateau (No:2019QZKK0206)

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