陆地表面温度（LST）是研究陆地表面过程最重要和最广泛使用的参数之一。中分辨率成像分光仪（MODIS）的地表温度产品（如 MOD11A1 和 MYD11A1）可以提供覆盖全球的中等时空分辨率的地表温度信息。然而，由于云污染等因素造成的缺失值，这些数据的应用受到了阻碍，这表明有必要制作一个类似于MODIS的无缝全球LST数据集，但目前还没有这种数据集。在本研究中，我们利用时空补缺框架，在标准MODIS LST产品的基础上，生成了2003年至2020年全球1 km每日（日中和夜中）无缝类MODIS LST数据集。", "ds_source": "
研究区域几乎涵盖整个全球陆地表面，包括 178块 MODIS 瓦片。本研究使用的主要数据是2003 年至2020年的1公里每日MODIS LST产品第 6 版。该产品基于美国国家航空航天局（NASA）的地球观测系统（EOS）卫星Terra Aqua（MOD11A1 和 MYD11A1）。这两颗卫星每天进行四次观测（即当地时间 10:30 和 22:30，Terra：T1 和 T3；13:30 和 01:30，Aqua：T2 和 T4）： T2 和 T4）。使用的另外两个辅助数据集是年度 MODIS 土地覆被产品（MCD12Q1）和根据夜间光观测数据及其周边农村地区得出的城市范围。我们的分析排除了 MCD12Q1 产品中的水像素。", "ds_process_way": "
该方法包括两个步骤 (1) 数据预处理和 (2) 时空拟合。在数据预处理过程中，我们过滤了数据质量较低的像素点，并利用同一天另外三个时间点观测到的LST填补了空白。在时空拟合过程中，我们首先使用平滑样条函数，根据每个像素点的年月日（自变量）拟合观测数据的时间趋势（总体平均值）。然后，我们对每天的观测值和总体平均值之间的残差进行时空插值。最后，我们将总体平均值与内插残差值相加，估算出LST的缺失值。", "ds_quality": "
结果表明，原始MODIS LST中的缺失值得到了有效和高效的填补，并且降低了计算成本，而且不存在其他无缝LST数据集可能存在的大面积缺失值（尤其是在瓦片边界附近）造成的明显块状效应。全球范围内不同缺失率的交叉验证结果表明，间隙填充的LST数据具有较高的精度，日中（13:30）和夜中（01:30）的平均均方根误差（RMSE）分别为1.88和1.33。空间分辨率为1公里的无缝全球日（昼中和夜中）LST数据集在全球城市系统研究、气候研究和建模以及陆地生态系统研究中具有重要用途。", "ds_acq_start_time": "2003-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "全球", "ds_acq_lon_east": -180.0, "ds_acq_lat_south": -90.0, "ds_acq_lon_west": 180.0, "ds_acq_lat_north": 90.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "open-access", "ds_total_size": 2467630236891, "ds_files_count": 36, "ds_format": "", "ds_space_res": null, "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "15a5fea8-74d2-4e26-858d-1526744261aa.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "0a4269e1-65f4-45f1-aeba-88ea3068eebf", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2024-07-17 15:13:55", "last_updated": "2025-06-30 16:19:13", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.IASTATE.C.DB6465.2024", "i18n": { "en": { "title": "A global seamless 1 km resolution daily land surface temperature dataset (2003–2020)", "ds_format": "", "ds_source": "
The research area covers almost the entire global land surface, including 178 MODIS tiles. The main data used in this study is the 6th edition of the MODIS LST product, which covers a daily distance of 1 kilometer from 2003 to 2020. This product is based on NASA's Earth Observation System (EOS) satellites Terra Aqua (MOD11A1 and MYD11A1). These two satellites conduct four observations per day (i.e. 10:30 and 22:30 local time, Terra: T1 and T3; 13:30 and 01:30, Aqua: T2 and T4): T2 and T4. The other two auxiliary datasets used are the annual MODIS land cover product (MCD12Q1) and the urban range derived from nighttime light observation data and its surrounding rural areas. Our analysis excluded water pixels in the MCD12Q1 product.", "ds_quality": "
The results indicate that the missing values in the original MODIS LST have been effectively and efficiently filled, and the computational cost has been reduced. Moreover, there is no significant block effect caused by large missing values (especially near tile boundaries) that may exist in other seamless LST datasets. The cross validation results of different missing rates globally indicate that LST data with gap filling has high accuracy, with average root mean square errors (RMSE) of 1.88 and 1.33 for intraday (13:30) and nighttime (01:30), respectively. The seamless global daily (daytime and nighttime) LST dataset with a spatial resolution of 1 kilometer has important applications in global urban system research, climate research and modeling, and terrestrial ecosystem research.", "ds_ref_way": "", "ds_abstract": "
Land surface temperature (LST) is one of the most important and widely used parameters for studying land surface processes. The surface temperature products of the Moderate Resolution Imaging Spectroradiometer (MODIS), such as MOD11A1 and MYD11A1, can provide surface temperature information with medium spatiotemporal resolution covering the globe. However, the application of these data has been hindered by missing values caused by factors such as cloud pollution, indicating the need to create a seamless global LST dataset similar to MODIS, which currently does not exist. In this study, we utilized a spatiotemporal imputation framework to generate a seamless global 1 km daily (mid day and mid night) MODIS LST dataset based on standard MODIS LST products from 2003 to 2020.
", "ds_time_res": "", "ds_acq_place": "Global", "ds_space_res": "", "ds_projection": "", "ds_process_way": "This method consists of two steps: (1) data preprocessing and (2) spatiotemporal fitting. During the data preprocessing process, we filtered out pixels with lower data quality and filled in the gaps using LSTs observed at three other time points on the same day. In the process of spatiotemporal fitting, we first use a smooth spline function to fit the time trend (overall average) of the observed data based on the year, month, day (independent variable) of each pixel point. Then, we perform spatiotemporal interpolation on the residuals between the daily observations and the overall average. Finally, we add the overall average value to the interpolated residual value to estimate the missing value of LST.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_outside", "cstr_reg_from": "reg_outside", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "MODIS", "无缝", "地表温度（LST）" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "全球" ], "ds_time_tags": [ 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020 ], "ds_contributors": [ { "true_name": "周宇宇", "email": "yuyuzhou@iastate.edu", "work_for": "Department of Geological and Atmospheric Sciences, Iowa State University", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "周宇宇", "email": "yuyuzhou@iastate.edu", "work_for": "Department of Geological and Atmospheric Sciences, Iowa State University", "country": "中国" } ], "ds_managers": [ { "true_name": "周宇宇", "email": "yuyuzhou@iastate.edu", "work_for": "Department of Geological and Atmospheric Sciences, Iowa State University", "country": "中国" } ], "category": "气象" }