本数据集的制备方法是一种基于新型地表温度时间分解模型的卫星热红外遥感-再分析数据集成方法。方法的主要输入数据为Aqua MODIS LST产品和GLDAS等数据,辅助数据包括卫星遥感提供的植被指数、地表反照率等。方法充分利用了卫星热红外遥感和再分析数据提供的地表温度高频分量、低频分量以及地表温度的空间相关性,最终重建得到较高质量的全天候地表温度数据集。
评价结果表明,本数据集具有良好的图像质量和精度,不仅在空间上无缝,还与当前学术界广泛采用的逐日1 km Aqua MODIS LST产品在幅值和空间分布上具有较高的一致性。当以MODIS LST为参考时,该数据集在白天和夜间的平均偏差(MBE)为0.08K至0.16K,偏差标准差(STD)为1.12K至1.46K。基于分布于黑河流域、东北、华北和华南地区的15个站点实测数据的检验结果表明,其MBE为-0.06K至-1.17K,RMSE为1.52K至3.71K,且在晴空与非晴空条件下无显著区别。
本数据集的时间分辨率为逐日2次,空间分辨率为1km,时间跨度为2000年-2021年(注:通过外推方式将缺少Aqua MODIS LST产品时段内的全天候地表温度补齐);空间范围包括我国陆域的主要区域(包含港澳台地区,暂不包含我国南海诸岛)及周边区域(72°E-135°E,19°N-55°N)。本数据集的缩写名为TRIMS LST(Thermal and Reanalysis Integrating Moderate-resolution Spatial-seamless LST),以便用户使用。需要说明的是,TRIMS LST的空间子集TRIMS LST-TP(中国西部逐日1 km全天候地表温度数据集(TRIMS LST-TP;2000-2021)V2)同步在国家青藏高原科学数据中心发布,以减少相关用户数据下载和处理的工作量。
1. Zhang, X., Zhou, J., Liang, S., Wang, D. (2021). A practical reanalysis data and thermal infrared remote sensing data merging (RTM) method for reconstruction of a 1-km all-weather land surface temperature. Remote Sensing of Environment, 260, 112437. https://doi.org/10.1016/j.rse.2021.112437.(查看)
2. Zhang, X., Zhou, J., Göttsche, F., Zhan, W., Liu, S., & Cao, R. (2019). A Method Based on Temporal Component Decomposition for Estimating 1-km All-Weather Land Surface Temperature by Merging Satellite Thermal Infrared and Passive Microwave Observations. IEEE Transactions on Geoscience and Remote Sensing, 57, 4670–4691. https://doi.org/10.1109/TGRS.2019.2892417(查看)
3. Zhou, J., Zhang, X., Zhan, W., Göttsche, F.-M., Liu, S., Olesen, F.-S., Hu, W., & Dai, F. (2017). A thermal sampling depth correction method for land surface temperature estimation from satellite passive microwave observation over barren land. IEEE Transactions on Geoscience and Remote Sensing, 55, 4743–4756. https://doi.org/10.1109/TGRS.2017.2698828(查看)
数据的引用
张晓东, 周纪, 唐文彬, 丁利荣, 马晋, 张旭. (2021). 中国陆域及周边逐日1km全天候地表温度数据集(TRIMS LST;2000-2021). 国家青藏高原科学数据中心, 2021. doi:
10.11888/Meteoro.tpdc.271252.
[Zhang, X., Zhou, J., Tang, W., Ding, L., Ma, J., Zhang, X. (2021). Daily 1-km all-weather land surface temperature dataset for the Chinese landmass and its surrounding areas (TRIMS LST; 2000-2021). National Tibetan Plateau Data Center, 2021]
1. Zhang, X., Zhou, J., Liang, S., Wang, D. (2021). A practical reanalysis data and thermal infrared remote sensing data merging (RTM) method for reconstruction of a 1-km all-weather land surface temperature. Remote Sensing of Environment, 260, 112437. https://doi.org/10.1016/j.rse.2021.112437.
2. Zhang, X., Zhou, J., Göttsche, F., Zhan, W., Liu, S., & Cao, R. (2019). A Method Based on Temporal Component Decomposition for Estimating 1-km All-Weather Land Surface Temperature by Merging Satellite Thermal Infrared and Passive Microwave Observations. IEEE Transactions on Geoscience and Remote Sensing, 57, 4670–4691. https://doi.org/10.1109/TGRS.2019.2892417
3. Zhou, J., Zhang, X., Zhan, W., Göttsche, F.-M., Liu, S., Olesen, F.-S., Hu, W., & Dai, F. (2017). A thermal sampling depth correction method for land surface temperature estimation from satellite passive microwave observation over barren land. IEEE Transactions on Geoscience and Remote Sensing, 55, 4743–4756. https://doi.org/10.1109/TGRS.2017.2698828
本数据要求的数据的引用方式:
张晓东, 周纪, 唐文彬, 丁利荣, 马晋, 张旭. (2021). 中国陆域及周边逐日1km全天候地表温度数据集(TRIMS LST;2000-2021). 国家青藏高原科学数据中心, 2021.
doi:
10.11888/Meteoro.tpdc.271252.
[Zhang, X., Zhou, J., Tang, W., Ding, L., Ma, J., Zhang, X. (2021). Daily 1-km all-weather land surface temperature dataset for the Chinese landmass and its surrounding areas (TRIMS LST; 2000-2021). National Tibetan Plateau Data Center, 2021.
doi:
10.11888/Meteoro.tpdc.271252. ]