本数据来源自中国土壤有机碳储量（SOCS）数据库的第 10 版，是基于全国23,103 个经过严格验证的土壤样本（7,995 个剖面），采用集成性土壤传递函数（PTF）模型构建而成的一个国家区域尺度的数据集。V10 数据集提供标准化的土壤剖面信息、环境协变量及元数据，确保数据的一致性和应用性。数据格式是CSV格式。\n新疆区域的数据是基于国家尺度的数据，叠加2024年新疆省级行政界线，按区域提取得到的矢量数据，保留源数据中的属性信息。
", "ds_source": "本数据来源自中国土壤有机碳储量（SOCS）数据库的第 10 版，是基于全国23,103 个经过严格验证的土壤样本（7,995 个剖面），采用集成性土壤传递函数（PTF）模型构建而成的一个国家区域尺度的数据集。V10 数据集提供标准化的土壤剖面信息、环境协变量及元数据，确保数据的一致性和应用性。数据格式是CSV格式。\n详情请参阅 SOCS_V10_Readme.text 文件\n官方数据引用：Chen, Z., Chen, L., Lu, R., Lou, Z., Zhou, F., Jin, Y., Xue, J., Guo, H., Wang, Z., Wang, Y., Liu, F., Song, X., Zhang, G., Su, Y., Ye, S., Shi, Z., & Chen, S. (2025). A national soil organic carbon density dataset (2010-2024) in China using ensemble modelling based pedotransfer functions [Data set]. Zenodo. https://doi.org/10.5281/zenodo.17304024\n关联文章引用：Chen, Z., Chen, L., Lu, R. et al. A national soil organic carbon density dataset (2010–2024) in China. Sci Data 12, 1480 (2025). https://doi.org/10.1038/s41597-025-05863-3
", "ds_process_way": "新疆区域的数据是基于源数据通过区域范围提取得到的矢量数据。源数据的生产方法请参考数据文章 A national soil organic carbon density dataset (2010–2024) in China https://doi.org/10.1038/s41597-025-05863-3
", "ds_quality": "提取后的矢量数据保留了源数据中的全部属性信息，未删减修改。
", "ds_acq_start_time": null, "ds_acq_end_time": null, "ds_acq_place": "", "ds_acq_lon_east": null, "ds_acq_lat_south": null, "ds_acq_lon_west": null, "ds_acq_lat_north": null, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 0, "ds_files_count": 0, "ds_format": "shp格式，csv格式", "ds_space_res": "无", "ds_time_res": "无", "ds_coordinate": "WGS84", "ds_projection": "WGS84", "ds_thumbnail": "20861951-7f72-4d08-8700-7090b7b5ac8b.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "Chen, Z., Chen, L., Lu, R., Lou, Z., Zhou, F., Jin, Y., Xue, J., Guo, H., Wang, Z., Wang, Y., Liu, F., Song, X., Zhang, G., Su, Y., Ye, S., Shi, Z., & Chen, S. (2025). A national soil organic carbon density dataset (2010-2024) in China using ensemble modelling based pedotransfer functions [Data set]. Zenodo. https://doi.org/10.5281/zenodo.17304024", "ds_from_station": null, "organization_id": "a5877b42-96ea-4f13-af7e-246f355413d6", "doi_value": "", "subject_codes": [ "210.50" ], "quality_level": 1, "publish_time": "2025-11-11 18:49:21", "first_publish_time": null, "last_updated": "2025-11-11 18:49:21", "protected": false, "protected_to": null, "lang": "zh", "cstr": null, "license": null, "extra": null, "files_shape": [], "features": null, "data_level": 0, "i18n": { "en": { "title": "Soil Organic Carbon Stocks (SOCS) Data from China to Xinjiang (2010-2024)", "ds_abstract": "This data comes from the 10th edition of the China Soil Organic Carbon Stocks (SOCS) Database. It is a national regional-scale data set constructed based on 23,103 strictly verified soil samples (7,995 profiles) across the country and using the integrated soil transfer function (PTF) model. The V10 dataset provides standardized soil profile information, environmental covariates and metadata to ensure data consistency and applicability. The data format is CSV format.\nThe data of Xinjiang region is based on national scale data, superimposed on the provincial administrative boundaries of Xinjiang in 2024, extracted vector data by region, and retained attribute information in the source data.
", "ds_source": "This data comes from the 10th edition of the China Soil Organic Carbon Stocks (SOCS) Database. It is a national regional-scale data set constructed based on 23,103 strictly verified soil samples (7,995 profiles) across the country and using the integrated soil transfer function (PTF) model. The V10 dataset provides standardized soil profile information, environmental covariates and metadata to ensure data consistency and applicability. The data format is CSV format.\nFor details, please refer to the SOCS_V10_Readme.text file\nOfficial data quote: Chen, Z., Chen, L., Lu, R., Lou, Z., Zhou, F., Jin, Y., Xue, J., Guo, H., Wang, Z., Wang, Y., Liu, F., Song, X., Zhang, G., Su, Y., Ye, S., Shi, Z., & Chen, S. (2025). A national soil organic carbon density dataset (2010-2024) in China using ensemble modelling based pedotransfer functions [Data set]. Zenodo. https://doi.org/10.5281/zenodo.17304024\nRelated article cited: Chen, Z., Chen, L., Lu, R. et al. A national soil organic carbon density dataset (2010–2024) in China. Sci Data 12, 1480 (2025). https://doi.org/10.1038/s41597-025-05863-3
", "ds_process_way": "The data of Xinjiang region is vector data extracted through regional scope based on source data. Please refer to the data article A national soil organic carbon density dataset (2010 - 2024) in China https://doi.org/10.1038/s41597-025-05863-3
", "ds_quality": "The extracted vector data retains all attribute information in the source data and is not deleted or modified.
", "ds_ref_instruction": "Chen, Z., Chen, L., Lu, R., Lou, Z., Zhou, F., Jin, Y., Xue, J., Guo, H., Wang, Z., Wang, Y., Liu, F., Song, X., Zhang, G., Su, Y., Ye, S., Shi, Z., & Chen, S. (2025). A national soil organic carbon density dataset (2010-2024) in China using ensemble modelling based pedotransfer functions [Data set]. Zenodo. https://doi.org/10.5281/zenodo.17304024", "ds_format": "shp format, csv format", "ds_projection": "WGS84", "ds_space_res": "no", "ds_time_res": "no" } }, "license_type": null, "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "土壤有机碳浓度" ], "ds_subject_tags": [ "土壤学" ], "ds_class_tags": [], "ds_locus_tags": [ "新疆" ], "ds_time_tags": [ 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024 ], "ds_contributors": [ "李锦" ], "ds_meta_authors": [ "李锦" ], "ds_managers": [ "李锦" ], "category": "土壤" }