本数据包含全国和新疆的数据，新疆范围的数据是从全国数据中掩膜提取得到的，掩膜用的矢量文件是天地图官网发布的2024年新疆维吾尔自治区行政区矢量数据。
", "ds_source": "土壤颜色是土壤最明显的可视特征。它能指示土壤的物理、化学和生物学性质及过程，是土壤质量评价和土壤管理的重要指标。它被广泛用作所有土壤分类系统的诊断特征。土壤颜色在水平和垂直方向上都有变化。为了揭示其空间变化，我们使用预测性土壤制图方法，根据最近的国家土壤普查数据和一系列环境协变量，以 1 km 2 网格单元大小和多个深度绘制土壤干色和湿色。中国土壤在九个深度的预测颜色，作为 GeoTFF 栅格的红色，绿色，蓝色分离在 1x1 公里的水平分辨率，并作为真彩色合成。
", "ds_process_way": "", "ds_quality": "", "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": 779035067, "ds_files_count": 391, "ds_format": "GeoTiff格式", "ds_space_res": null, "ds_time_res": "", "ds_coordinate": "WGS84", "ds_projection": "GCS_WGS84", "ds_thumbnail": "664ba8b1-7b08-477f-b8e5-7e7852ce843b.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "a5877b42-96ea-4f13-af7e-246f355413d6", "doi_value": "", "subject_codes": [ "210.50" ], "quality_level": 1, "publish_time": "2025-08-18 13:17:20", "first_publish_time": null, "last_updated": "2025-08-18 13:17:20", "protected": false, "protected_to": null, "lang": "zh", "cstr": null, "license": null, "extra": null, "files_shape": [ { "name": "ColourMatchingBarDry.pdf", "size": 4298, "is_dir": false }, { "name": "ColourMatchingBarMoist.pdf", "size": 4288, "is_dir": false }, { "name": "ProducingColourBars.R", "size": 598, "is_dir": false }, { "name": "readme.txt", "size": 1698, "is_dir": false }, { "name": "China", "size": null, "is_dir": true }, { "name": "Xinjiang", "size": null, "is_dir": true } ], "features": null, "data_level": 0, "i18n": { "en": { "title": "Soil color prediction data in Xinjiang, China", "ds_abstract": "This data includes national and Xinjiang data. Xinjiang data is extracted from the national data mask. The vector file used for the mask is the vector data of the administrative region of Xinjiang Uygur Autonomous Region in 2024 released by Tiantu's official website.
", "ds_source": "Soil color is the most obvious visual feature of soil. It can indicate the physical, chemical and biological properties and processes of soil, and is an important indicator for soil quality assessment and soil management. It is widely used as a diagnostic feature in all soil classification systems. Soil color changes in both horizontal and vertical directions. To reveal its spatial changes, we used predictive soil mapping methods to plot soil dry and wet colors at a grid cell size of 1 km2 and multiple depths based on recent national soil census data and a series of environmental covariates. The predicted colors of China soil at nine depths are separated as GeoTFF grids of red, green, and blue at a horizontal resolution of 1x1km and synthesized as true color.
", "ds_format": "GeoTiff format", "ds_projection": "GCS_WGS84" } }, "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": [ "土壤颜色" ], "ds_subject_tags": [ "土壤学" ], "ds_class_tags": [], "ds_locus_tags": [ "新疆", "中国" ], "ds_time_tags": [], "ds_contributors": [ "李锦" ], "ds_meta_authors": [ "李锦" ], "ds_managers": [ "李锦" ], "category": "土壤" }