本数据集包含2003-2017年期间中国（约960万平方公里土地）的地表温度数据，以摄氏度为单位，时间分辨率为月尺度，空间分辨率为5600米。通过结合MODIS日数据（MOD11C1和MYD11C1）、月数据（MOD11C3和MYD11C3）以及气象站数据，重建月LST影像中云覆盖下的真实LST，然后构建回归分析模型，以进一步提高不同气候条件下6个自然分区的精度。精度分析表明，重建结果与现场测量结果密切相关，平均RMSE为1.39℃，MAE为1.30℃，R2为0.97。\n
两个文件:\n
1) 文档说明文件: 00_Metadata for LSTC.docx;\n
2) 数据集文件:01_LSTC.zip，里面包含15个文件夹。文件格式包括： *.TIF (LSTC image) and *.TFW (TIFF image coordinate information).", "ds_source": "
MODIS日数据（MOD11C1和MYD11C1）、月数据（MOD11C3和MYD11C3）以及气象站数据，modis数据下载网站：https://ladsweb.modaps.eosdis.nasa.gov", "ds_process_way": "
数据集主要是通过集成MODIS每日数据（MOD11C1和MYD11C1），月数据（MOD11C3和MYD11C3）和气象站数据，以重建月尺度LST图像云覆盖下的真实LST来生成的，然后构建回归分析模型以进一步提高精度。", "ds_quality": "
精度分析表明，重建结果与现场测量结果密切相关，平均RMSE为1.39℃，MAE为1.30℃，R2为0.97。", "ds_acq_start_time": "2003-01-01 00:00:00", "ds_acq_end_time": "2017-12-31 00:00:00", "ds_acq_place": "中国", "ds_acq_lon_east": 135.3861111111111, "ds_acq_lat_south": 3.52, "ds_acq_lon_west": 73.4, "ds_acq_lat_north": 53.330000000000005, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "open-access", "ds_total_size": 161777563, "ds_files_count": 5, "ds_format": "tif", "ds_space_res": "5600米", "ds_time_res": "月", "ds_coordinate": "WGS84", "ds_projection": "Albers_Conic_Equal_Area", "ds_thumbnail": "120ea2a9-c408-4a66-97fe-314c2c0784b2.jpg", "ds_thumb_from": 2, "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": "2023-05-29 11:17:04", "last_updated": "2025-06-30 16:24:14", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.ZENODO.DB6681.2024", "i18n": { "en": { "title": "Monthly scale dataset of surface temperature in China (2003-2017)", "ds_format": "tif", "ds_source": "
MODIS daily data (MOD11C1 and MYD11C1), monthly data (MOD11C3 and MYD11C3), and meteorological station data. MODIS data download website: https://ladsweb.modaps.eosdis.nasa.gov", "ds_quality": "
Accuracy analysis shows that the reconstruction results are closely related to the on-site measurement results, with an average RMSE of 1.39 ℃, MAE of 1.30 ℃, and R2 of 0.97.", "ds_ref_way": "", "ds_abstract": "
This dataset contains surface temperature data of China (approximately 9.6 million square kilometers of land) from 2003 to 2017, measured in degrees Celsius with a monthly time resolution and a spatial resolution of 5600 meters. By combining MODIS daily data (MOD11C1 and MYD11C1), monthly data (MOD11C3 and MYD11C3), and meteorological station data, the true LST under cloud coverage in monthly LST images was reconstructed, and a regression analysis model was constructed to further improve the accuracy of six natural zones under different climate conditions. Accuracy analysis shows that the reconstruction results are closely related to the on-site measurement results, with an average RMSE of 1.39 ℃, MAE of 1.30 ℃, and R2 of 0.97.\n
Two files:\n
1) Document description file: 00_Setadata for LSTC.docx;\n
2) Dataset file: 01_LSTC. zip, containing 15 folders. The file formats include: * TIF (LSTC image) and *.TFW (TIFF image coordinate information).
", "ds_time_res": "月", "ds_acq_place": "China", "ds_space_res": "5600米", "ds_projection": "Albers_Conic_Equal_Area", "ds_process_way": "The dataset is mainly generated by integrating MODIS daily data (MOD11C1 and MYD11C1), monthly data (MOD11C3 and MYD11C3), and meteorological station data to reconstruct the real LST under cloud coverage of monthly scale LST images, and then constructing a regression analysis model to further improve accuracy.", "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": [ "热红外", "热红外辐射计", "自然灾害", "草地截留", "遥感技术", "陆地水储量异常", "地表水", "地表温度", "大气遥感", "极端降水", "森林火灾", "水文", "水温", "灾害" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国" ], "ds_time_tags": [ 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017 ], "ds_contributors": [ { "true_name": "毛克彪", "email": "maokebiao@caas.cn", "work_for": " 中国农业科学院农业资源与农业区划研究所遥感室", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "毛克彪", "email": "maokebiao@caas.cn", "work_for": " 中国农业科学院农业资源与农业区划研究所遥感室", "country": "中国" } ], "ds_managers": [ { "true_name": "毛克彪", "email": "maokebiao@caas.cn", "work_for": " 中国农业科学院农业资源与农业区划研究所遥感室", "country": "中国" } ], "category": "遥感及产品" }