ELITE land surface temperature: seamless 1km LST over China (2016)

The Essential thermaL Infrared remoTe sEnsing (ELITE) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn).

This dataset is the ELITE seamless 1km LST  over China landmass (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 using the geographically weighted regression to obtain 1km LST. Finally, the multi-scale kalman filter is used to fuse MODIS LST and AMSR-E/AMSR2 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.

This is the seamless LST dataset in 2016. Please click here to download the ELITE LST product in 2015 and click here to download the ELITE LST product in 2017.

Dataset Characteristics:

Spatial Coverage: China

Temporal Coverage: 2016

Spatial Resolution: 1 KM

Temporal Resolution: 2 times per day

Data Format: hdf

Scale: 0.02

Citation (Please cite these papers when using the data):

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

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 

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 

If you have any questions, please contact Prof. Jie Cheng ([e-mail]).

核心热红外遥感（Essential Thermal Infrared Remote Sensing, ELITE）产品套件目前包含四类产品，分别为地表温度（Land Surface Temperature, LST：晴空与全天空场景）、发射率（含窄带发射率NBE、宽带发射率BBE与光谱发射率）、地表辐射与能量收支组分（含地表长波上行辐射SLUR、地表长波下行辐射SLDR、地表长波净辐射SLNR），以及地球辐射收支组分（含出射长波辐射OLR、反射太阳辐射RSR）。ELITE产品的时空分辨率主要取决于所采用的卫星数据源。如需了解ELITE产品的更多信息，请访问官网：https://elite.bnu.edu.cn。

本数据集为覆盖中国陆域的ELITE无缝1km分辨率地表温度产品（时间跨度2002-2020年）。首先，基于查找表开发经验反演算法，用于从AMSR-E/AMSR2观测数据中反演微波地表温度；随后，采用地理加权回归对AMSR-E/AMSR2反演得到的地表温度进行降尺度处理，获取1km分辨率地表温度；最后，通过多尺度卡尔曼滤波器融合MODIS地表温度与AMSR-E/AMSR2地表温度，生成无缝1km分辨率地表温度数据集。地面验证结果表明，该1km无缝地表温度产品的均方根误差（Root Mean Square Error, RMSE）约为3K。此外，该1km无缝地表温度的空间分布与MODIS地表温度及CLDAS地表温度具有良好一致性。

本页面为2016年无缝地表温度数据集。请点击此处下载2015年ELITE地表温度产品，点击此处下载2017年ELITE地表温度产品。

数据集特征：
空间覆盖范围：中国陆域
时间覆盖范围：2016年
空间分辨率：1km
时间分辨率：每日2次
数据格式：HDF
缩放系数：0.02

引用说明（使用本数据集时请引用以下文献）：
1. Xu, S., & Cheng, J. (2021). 基于累积分布函数匹配与多分辨率卡尔曼滤波的新型地表温度融合策略. 环境遥感, 254, 112256
2. Zhang, Q., Wang, N., Cheng, J., & Xu, S. (2020). 从AMSR-E数据生成高分辨率地表温度的逐步降尺度方法. IEEE应用地球观测与遥感选刊, 13, 5669-5681
3. Zhang, Q., & Cheng, J. (2020). 考虑环境变量综合影响的AMSR-E数据地表温度反演经验算法. 地球与空间科学, 7, e2019EA001006. https://doi.org/10.1029/2019EA001006

如有任何疑问，请联系程洁教授（邮箱：[e-mail]）。