本数据集包含2002年至2018年中国土地的土壤水分数据，时间分辨率为月尺度，空间分辨率为0.05°。更具体地说，它是由三种无源微波遥感产品产生的：日本宇宙航空研究开发机构 (JAXA) 的微波扫描辐射计-地球观测系统 (AMSR-E) 和高级微波扫描辐射计(AMSR2)3级土壤水分数据，以及由 Institut National de la Recherche Agronomique (INRA) 和 Centre d’Etudes Spatiales de la BIOsphère (CESBIO) 土壤水分数据开发的SMOS产品。为了克服低分辨率被动微波土壤水分产品的不足，我们使用中分辨率成像光谱仪 (MODIS) 数据计算的 TVDI 构建空间加权分解 (SWD)，包括地表温度 (LST) MYD11C3 数据和归一化差异植被指数 (NDVI) MYD13C2 数据。总体而言，降尺度的土壤水分 (SM) 产品与原位测量结果一致 (R>0.78)，并表现出低均方根误差 (ubRMSE < 0.05 m3/m3)，这表明整个时间序列具有良好的准确性
", "ds_source": "日本宇宙航空研究开发机构（JAXA）的 AMSR-E 的 Level 3 土壤水分数据和 AMSR2 的 Level 3 土壤水分数据，以及由法国农业科学研究院（INRA）和法国空间生物圈研究中心（CESBIO）研发的 SMOS 产品的土壤水分数据。", "ds_process_way": "
TVDI由中分辨率成像光谱仪（MODIS）的地表温度（LST）MYD11C3数据和归一化植被指数（NDVI）MYD13C2数据计算而来。
", "ds_quality": "降尺度的土壤水分 (SM) 产品与原位测量结果一致 (R>0.78)，并表现出低均方根误差 (ubRMSE < 0.05 m3/m3)，这表明整个时间序列具有良好的准确性。", "ds_acq_start_time": "2002-01-01 00:00:00", "ds_acq_end_time": "2018-12-31 00:00:00", "ds_acq_place": "中国", "ds_acq_lon_east": 135.15, "ds_acq_lat_south": 18.1, "ds_acq_lon_west": 73.45, "ds_acq_lat_north": 53.5, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "open-access", "ds_total_size": 914225837, "ds_files_count": 7, "ds_format": "tif", "ds_space_res": "0.05°", "ds_time_res": "月", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "e50f3410-0e16-4459-9619-9b4894dd712f.png", "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.DB6684.2024", "i18n": { "en": { "title": "Chinese Soil Moisture Dataset (2002-2018)", "ds_format": "tif", "ds_source": "
The Level 3 soil moisture data of AMSR-E and AMSR2 from the Japan Aerospace Exploration Agency (JAXA), as well as the soil moisture data of SMOS products developed by the French Academy of Agricultural Sciences (INRA) and the French Center for Space Biosphere Research (CESBIO).", "ds_quality": "
The downscaled soil moisture (SM) product is consistent with the in-situ measurement results (R>0.78) and exhibits low root mean square error (ubRMSE<0.05 m3/m3), indicating good accuracy of the entire time series.", "ds_ref_way": "", "ds_abstract": "
This dataset contains soil moisture data of Chinese land from 2002 to 2018, with a temporal resolution of monthly scale and a spatial resolution of 0.05 °. More specifically, it is generated by three passive microwave remote sensing products: the Microwave Scanning Radiometer Earth Observation System (AMSR-E) and Advanced Microwave Scanning Radiometer (AMSR2) Level 3 soil moisture data from the Japan Aerospace Exploration Agency (JAXA), as well as the SMOS product developed from soil moisture data from the Institute National de la Recherche Agronomique (INRA) and Centre d'Etudes Spatiales de la BIOsph è re (CESBIO). To overcome the shortcomings of low resolution passive microwave soil moisture products, we constructed a spatially weighted decomposition (SWD) using TVDI calculated from Moderate Resolution Imaging Spectroradiometer (MODIS) data, including surface temperature (LST) MYD11C3 data and Normalized Difference Vegetation Index (NDVI) MYD13C2 data. Overall, the downscaled soil moisture (SM) product is consistent with the in-situ measurement results (R>0.78) and exhibits low root mean square error (ubRMSE<0.05 m3/m3), indicating good accuracy of the entire time series
", "ds_time_res": "月", "ds_acq_place": "China", "ds_space_res": "0.05°", "ds_projection": "", "ds_process_way": "TVDI is calculated from surface temperature (LST) MYD11C3 data and normalized vegetation index (NDVI) MYD13C2 data from the Moderate Resolution Imaging Spectroradiometer (MODIS).
", "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": [ "土壤水分", "微波遥感", "空间加权分解", "降尺度" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国" ], "ds_time_tags": [ 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018 ], "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" }