OpenLandMap-soildb: soil type probability - suborder: Vitrands

Sub-dataset: soil type probability - suborder: Vitrands Description Global annual maps of soil properties for 2000—2022 produced within the scope of the Land & Carbon Lab, integrating Digital surface/terrain model, vegetation/tillage indices, climatic/bioclimatic variables, and based on tree-based spatiotemporal Machine Learning. While the primary focus is on improving monitoring in global soil properties, the dataset provides wall-to-wall coverage across all terrestrial ecosystems and is organized into 300+ global mosaics in COG (Cloud Optimized GeoTIFF) format. Data are presented at 5-year intervals, across 3 standard depth intervals (0–30 cm, 30–60 cm, 60–100 cm), and cover 79 USDA soil taxonomy suborders. Original layers use the WGS84 Coordinate System (EPSG:4326) at a pixel resolution of 0.00025 degrees, and 0.00075 degrees with uncertainty (STAC and GEE). Layers archived on Zenodo are at 0.00075 degrees with uncertainty but include only the initial and final periods (2000–2005 & 2020–2022), including: Soil Organic Carbon Content (g/kg) As a key indicator of soil fertility, structure, and microbial activity, it represents the concentration of organic carbon in the fine earth fraction of the soil. Standard method of measurement is dry combustion using elemental analyzers (e.g., ISO 10694). Soil Organic Carbon Density (kg/m³) Represents the mass of organic carbon per unit volume of soil. It is derived as: SOC content × bulk density × (1 − coarse fragment volume fraction). This value is critical for estimating total carbon stocks and monitoring soil carbon changes over time. Soil pH Indicates the acidity or alkalinity of soil, affecting nutrient availability and microbial processes. Reported as pH measured in water solution (pH in H₂O). Bulk Density (g/cm³) Refers to the mass of dry fine earth (<2 mm) per unit volume, excluding coarse fragments. It reflects soil compaction and porosity, influencing water retention and root penetration. Commonly determined using the core method or calculated from pedotransfer functions. Soil Texture Fraction Defines the relative proportions of mineral particles by size. Texture influences water movement, nutrient holding capacity, and plant growth. Clay content (%): Proportion of particles <0.002 mm in diameter. Sand content (%): Proportion of particles between 0.05–2.0 mm (some definitions use 0.063 mm as lower threshold). Silt content (%): Particles sized between 0.002–0.05 mm or up to 0.063 mm depending on classification system. Textural fractions follow USDA or FAO particle size classifications. Soil Type Probability Probabilistic classification of soils based on USDA Soil Taxonomy at the subgroup level. Each pixel is assigned a probability distribution across potential soil types, based on legacy point data and environmental covariates. 30m layers can be accessed through STAC and Google Earth Engine GEE) through: OpenLandMap STAC https://stac.openlandmap.org Google Earth Engine https://code.earthengine.google.com/?asset=projects/global-pasture-watch/assets/gsm-30m All modeling framework is publicly available at OpenLandMap GitHub - soildb Data Detail Time period: 2000-2022, in 5-year intervals (last period covers 2020–2022) for soil properties ; 2000-2022 static for soil type Type of data: Spatiotemporal soil data base, with depth ranges and weighted percentage data for soil assessments and static soil type classification. How the data was collected or derived: The data was derived using machine learning models. Statistical methods used: Tree-based spatiotemporal machine learning Depth reference: b30cm..60cm = below ground at 30-60cm interval Limitations or exclusions in the data: no Antarctica; masking out permanent ice and deserts Coordinate reference system: EPSG:4326 Bounding box (Xmin, Ymin, Xmax, Ymax): (-180, -56, 180, 76) Spatial resolution: 0.00075 degree (~120m) Image size: 360,000P, 132,000L File format: Cloud Optimized Geotiff (COG) format Dataset Contents This dataset includes: soil type probability - suborder: Vitrands Related Identifiers SOC density: below ground 0cm-30cm 2000-2005 , below ground 0cm-30cm 2020-2022 , below ground 30cm-60cm 2000-2005 , below ground 30cm-60cm 2020-2022 , below ground 60cm-100cm 2000-2005 , below ground 60cm-100cm 2020-2022 , SOC content: below ground 0cm-30cm 2000-2005 - part 1 , below ground 0cm-30cm 2000-2005 - part 2 , below ground 0cm-30cm 2020-2022 - part 1 , below ground 0cm-30cm 2020-2022 - part 2 , below ground 30cm-60cm 2000-2005 , below ground 30cm-60cm 2020-2022 , below ground 60cm-100cm 2000-2005 , below ground 60cm-100cm 2020-2022 , Bulk density: below ground 0cm-30cm 2000-2005 , below ground 0cm-30cm 2020-2022 , below ground 30cm-60cm 2000-2005 , below ground 30cm-60cm 2020-2022 , below ground 60cm-100cm 2000-2005 , below ground 60cm-100cm 2020-2022 , Soil ph of water: below ground 0cm-30cm 2000-2005 , below ground 0cm-30cm 2020-2022 , below ground 30cm-60cm 2000-2005 , below ground 30cm-60cm 2020-2022 , below ground 60cm-100cm 2000-2005 , below ground 60cm-100cm 2020-2022 , Soil textures fraction: clay below ground 0cm-30cm 2000-2005 , clay below ground 0cm-30cm 2020-2022 , clay below ground 30cm-60cm 2000-2005 , clay below ground 30cm-60cm 2020-2022 , clay below ground 60cm-100cm 2000-2005 , clay below ground 60cm-100cm 2020-2022 , sand below ground 0cm-30cm 2000-2005 , sand below ground 0cm-30cm 2020-2022 , sand below ground 30cm-60cm 2000-2005 , sand below ground 30cm-60cm 2020-2022 , sand below ground 60cm-100cm 2000-2005 , sand below ground 60cm-100cm 2020-2022 , silt below ground 0cm-30cm 2000-2005 , silt below ground 0cm-30cm 2020-2022 , silt below ground 30cm-60cm 2000-2005 , silt below ground 30cm-60cm 2020-2022 , silt below ground 60cm-100cm 2000-2005 , silt below ground 60cm-100cm 2020-2022 , Soil type (Suborder): Uderts , Calcids , Xerands , Orthents , Cryands , Ustalfs , Cryalfs , Aquepts , Udalfs , Cryolls , Durids , Usterts , Boralfs , Orthids , Udands , Torrerts , Histels , Rendolls , Aqualfs , Udepts , Xeralfs , Gelepts , Xerults , Fibrists , Ustepts , Xererts , Ustults , Aquands , Perox , Xerolls , Tropepts , Turbels , Udults , Aquents , Aquerts , Ustox , Aquods , Aquolls , Xerepts , Udox , Cryods , Ustolls , Aquults , Psamments , Arents , Fluvents , Humults , Vitrands , Udolls , Borolls , Orthels , Hemists , Wassents , Albolls , Salids , Cryepts , Saprists , Folists , Gypsids , Ochrepts , Cambids , Argids , Orthods , Data Details Time period: 2000-2022 Type of data: soil type probability - suborder: Vitrands How the data was collected or derived: Machine learning models. Statistical Methods used: Random Forest. Limitations or exclusions in the data: The dataset does not include Antarctica. Coordinate reference system: EPSG:4326 Bounding box (Xmin, Ymin, Xmax, Ymax): (-180, -56, 180, 76) Spatial resolution: 120m Image size: 360,000P x 132,000L File format: Cloud Optimized Geotiff (COG) format. Layer information: File Name Unit Scale Data Type No Data Description oc_iso.10694.1995.mg.cm3 kg/m³ 10 UInt16 32767 Organic carbon density derived by multiply fine earth bulk density and organic carbon content oc_iso.10694.1995.wpml g/kg 10 UInt16 32767 Organic carbon content based on dry combustion weight percent ph.h2o_iso.10390.2021.index - 10 Byte 255 The pH, 1:1 soil-water suspension is the pH of a sample measured in distilled water at a 1:1 soil:solution ratio bd.core_iso.11272.2017.g.cm3 g/cm³ 100 UInt16 32767 Bulk density, <2mm fraction, dry is the weight per unit volume of the <2 mm fraction, with volume measured in laboratory sand.tot_iso.11277.2020.wpct % 1 Byte 255 Total laboratory-estimated sand 0.063 to 2.0 mm particle diameter silt.tot_iso.11277.2020.wpct % 1 Byte 255 Total laboratory-estimated silt 0.002 to 0.063 mm particle size clay.tot_iso.11277.2020.wpct % 1 Byte 255 Total clay is the soil separate with <0.002 mm particle diameter soil.types_ensemble % 1 Byte 255 Probability of soil type occurrence Support If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue here Naming convention To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. For example, for oc_iso.10694.1995.wpml_m_30m_b30cm..60cm_20000101_20051231_g_epsg.4326_v20250204.tif, the fields are: generic variable name: oc = organic carbon variable procedure combination: iso.10694.1995.wpml = organic carbon content based on dry combustion weight per mille Position in the probability distribution/variable type: m = mean Spatial support: 30m Depth reference: b30cm..60cm = below ground at 30-60cm interval Time reference begin time: 20000101 = 2000-01-01 Time reference end time: 20051231 = 2005-12-31 Bounding box: g = global EPSG code: EPSG:4326 Version code: v20250204 = version from 2025-02-04 Acknowledgement This project is funded by European Commission through Open-Earth-Monitor project and by World Resources Institute through Land & Carbon Lab子数据集：土壤类型概率 - 亚纲：Vitrands ### 数据集描述 本数据集由陆地与碳实验室（Land & Carbon Lab）生成，涵盖2000—2022年全球年度土壤属性地图，整合了数字地表/地形模型、植被/耕作指数、气候/生物气候变量，基于树基时空机器学习构建。尽管本数据集核心目标为提升全球土壤属性监测能力，但其实现了所有陆地生态系统的无缝全域覆盖，并以云优化GeoTIFF（Cloud Optimized GeoTIFF, COG）格式组织为300余幅全球镶嵌图。 数据以5年为间隔发布，涵盖3个标准深度区间（0–30 cm、30–60 cm、60–100 cm），覆盖美国农业部（United States Department of Agriculture, USDA）土壤分类系统的79个土壤亚纲。原始图层采用WGS84坐标系（EPSG:4326），像素分辨率为0.00025度；其中带有不确定性信息的图层分辨率为0.00075度，可通过时空资产目录（SpatioTemporal Asset Catalog, STAC）和谷歌地球引擎（Google Earth Engine, GEE）获取。存储于Zenodo的图层分辨率为0.00075度且包含不确定性信息，但仅涵盖初始与最终时段（2000–2005及2020–2022），具体包含以下图层： 1. **土壤有机碳含量（Soil Organic Carbon Content, g/kg）** 作为土壤肥力、结构与微生物活性的关键指标，该图层表征土壤细粒部分（<2 mm）中的有机碳浓度。标准测量方法为使用元素分析仪进行干式燃烧法（如ISO 10694标准）。 2. **土壤有机碳密度（Soil Organic Carbon Density, kg/m³）** 表征单位体积土壤中的有机碳质量，计算公式为：SOC含量 × 容重 × (1 − 粗碎屑体积占比)。该参数对于估算总碳储量及长期监测土壤碳变化至关重要。 3. **土壤pH值** 表征土壤的酸碱性，影响养分有效性与微生物过程。报告值为水土悬液pH值（pH in H₂O）。 4. **容重（Bulk Density, g/cm³）** 指单位体积干细粒土壤（<2 mm）的质量，不含粗碎屑组分。该参数反映土壤压实度与孔隙度，影响水分持留与根系穿透能力，通常通过环刀法测定或通过土壤传递函数（pedotransfer functions）计算得到。 5. **土壤颗粒机械组成（Soil Texture Fraction）** 表征不同粒径矿物颗粒的相对占比，其影响水分运移、养分保持能力与植物生长。 - 黏粒含量（Clay content, %）：粒径<0.002 mm的颗粒占比。 - 砂粒含量（Sand content, %）：粒径0.05–2.0 mm的颗粒占比（部分分类标准以0.063 mm作为下限阈值）。 - 粉粒含量（Silt content, %）：粒径0.002–0.05 mm的颗粒占比，部分分类系统将上限调整至0.063 mm。 颗粒机械组成遵循美国农业部（USDA）或联合国粮农组织（Food and Agriculture Organization, FAO）的粒径分类标准。 6. **土壤类型概率（Soil Type Probability）** 基于美国农业部土壤分类系统（USDA Soil Taxonomy）的亚类级别，对土壤进行概率分类。基于历史点位数据与环境协变量，每个像素被赋予潜在土壤类型的概率分布。 30米分辨率图层可通过以下途径通过STAC和GEE获取： - OpenLandMap STAC：https://stac.openlandmap.org - 谷歌地球引擎：https://code.earthengine.google.com/?asset=projects/global-pasture-watch/assets/gsm-30m 所有建模框架已公开至OpenLandMap GitHub仓库soildb。 #### 数据详情 - 时间范围：土壤属性数据为2000-2022年，以5年为间隔（最后一个时段涵盖2020–2022）；土壤类型数据为2000-2022年静态数据。 - 数据类型：时空土壤数据库，包含深度区间与加权百分比数据，用于土壤评估与静态土壤类型分类。 - 数据获取/衍生方式：通过机器学习模型衍生得到。 - 所用统计方法：基于树的时空机器学习。 - 深度参考：b30cm..60cm = 地下30-60cm区间 - 数据局限性与排除范围：不含南极洲；已对永久冰盖与沙漠区域进行掩膜处理。 - 坐标系：EPSG:4326 - 边界框（Xmin, Ymin, Xmax, Ymax）：(-180, -56, 180, 76) - 空间分辨率：0.00075度（约120米） - 图像尺寸：360,000列 × 132,000行 - 文件格式：云优化GeoTIFF（COG）格式 #### 数据集内容 本数据集包含： - 土壤类型概率 - 亚纲：Vitrands #### 相关标识符 - **SOC密度**： 地下0cm-30cm 2000-2005 地下0cm-30cm 2020-2022 地下30cm-60cm 2000-2005 地下30cm-60cm 2020-2022 地下60cm-100cm 2000-2005 地下60cm-100cm 2020-2022 - **SOC含量**： 地下0cm-30cm 2000-2005 - 部分1 地下0cm-30cm 2000-2005 - 部分2 地下0cm-30cm 2020-2022 - 部分1 地下0cm-30cm 2020-2022 - 部分2 地下30cm-60cm 2000-2005 地下30cm-60cm 2020-2022 地下60cm-100cm 2000-2005 地下60cm-100cm 2020-2022 - **容重**： 地下0cm-30cm 2000-2005 地下0cm-30cm 2020-2022 地下30cm-60cm 2000-2005 地下30cm-60cm 2020-2022 地下60cm-100cm 2000-2005 地下60cm-100cm 2020-2022 - **水土比土壤pH**： 地下0cm-30cm 2000-2005 地下0cm-30cm 2020-2022 地下30cm-60cm 2000-2005 地下30cm-60cm 2020-2022 地下60cm-100cm 2000-2005 地下60cm-100cm 2020-2022 - **土壤颗粒机械组成**： 黏粒 地下0cm-30cm 2000-2005 黏粒 地下0cm-30cm 2020-2022 黏粒 地下30cm-60cm 2000-2005 黏粒 地下30cm-60cm 2020-2022 黏粒 地下60cm-100cm 2000-2005 黏粒 地下60cm-100cm 2020-2022 砂粒 地下0cm-30cm 2000-2005 砂粒 地下0cm-30cm 2020-2022 砂粒 地下30cm-60cm 2000-2005 砂粒 地下30cm-60cm 2020-2022 砂粒 地下60cm-100cm 2000-2005 砂粒 地下60cm-100cm 2020-2022 粉粒 地下0cm-30cm 2000-2005 粉粒 地下0cm-30cm 2020-2022 粉粒 地下30cm-60cm 2000-2005 粉粒 地下30cm-60cm 2020-2022 粉粒 地下60cm-100cm 2000-2005 粉粒 地下60cm-100cm 2020-2022 - **土壤类型（亚纲）**： Uderts、Calcids、Xerands、Orthents、Cryands、Ustalfs、Cryalfs、Aquepts、Udalfs、Cryolls、Durids、Usterts、Boralfs、Orthids、Udands、Torrerts、Histels、Rendolls、Aqualfs、Udepts、Xeralfs、Gelepts、Xerults、Fibrists、Ustepts、Xererts、Ustults、Aquands、Perox、Xerolls、Tropepts、Turbels、Udults、Aquents、Aquerts、Ustox、Aquods、Aquolls、Xerepts、Udox、Cryods、Ustolls、Aquults、Psamments、Arents、Fluvents、Humults、Vitrands、Udolls、Borolls、Orthels、Hemists、Wassents、Albolls、Salids、Cryepts、Saprists、Folists、Gypsids、Ochrepts、Cambids、Argids、Orthods #### 补充数据详情 - 时间范围：2000-2022年 - 数据类型：土壤类型概率 - 亚纲：Vitrands - 数据获取/衍生方式：机器学习模型 - 所用统计方法：随机森林（Random Forest） - 数据局限性与排除范围：本数据集不含南极洲 - 坐标系：EPSG:4326 - 边界框（Xmin, Ymin, Xmax, Ymax）：(-180, -56, 180, 76) - 空间分辨率：120米 - 图像尺寸：360,000列 × 132,000行 - 文件格式：云优化GeoTIFF（COG）格式 - 图层信息： | 文件名 | 单位 | 缩放比例 | 数据类型 | 无数据值 | 描述 | | --- | --- | --- | --- | --- | --- | | oc_iso.10694.1995.mg.cm3 | kg/m³ | 10 | UInt16 | 32767 | 有机碳密度：通过细粒土壤容重与有机碳含量相乘得到 | | oc_iso.10694.1995.wpml | g/kg | 10 | UInt16 | 32767 | 有机碳含量：基于干式燃烧法重量百分比测定 | | ph.h2o_iso.10390.2021.index | - | 10 | Byte | 255 | 土壤pH值：1:1水土悬液pH，即按照1:1土水比将样品悬浮于蒸馏水后测定的pH值 | | bd.core_iso.11272.2017.g.cm3 | g/cm³ | 100 | UInt16 | 32767 | 容重：<2mm组分干重，指<2mm组分的单位体积重量，体积通过实验室测定 | | sand.tot_iso.11277.2020.wpct | % | 1 | Byte | 255 | 总砂粒含量：实验室测定的粒径0.063~2.0mm颗粒占比 | | silt.tot_iso.11277.2020.wpct | % | 1 | Byte | 255 | 总粉粒含量：实验室测定的粒径0.002~0.063mm颗粒占比 | | clay.tot_iso.11277.2020.wpct | % | 1 | Byte | 255 | 总黏粒含量：粒径<0.002mm的土壤颗粒组分占比 | | soil.types_ensemble | % | 1 | Byte | 255 | 土壤类型出现概率 | #### 支持与反馈 若您发现程序漏洞、数据异常或不一致之处，或有相关疑问，请在此处提交GitHub议题。 #### 命名约定 为确保项目内外部的一致性与易用性，本数据集遵循Ai4SoilHealth与Open-Earth-Monitor标准文件命名规范。该规范包含10个字段，用于描述数据的关键属性，使用户可无需打开文件即可实现文件检索、数据分析准备等操作。 以文件名`oc_iso.10694.1995.wpml_m_30m_b30cm..60cm_20000101_20051231_g_epsg.4326_v20250204.tif`为例，各字段含义如下： - 通用变量名：oc = 有机碳 - 变量与处理组合：iso.10694.1995.wpml = 基于干式燃烧法重量千分比测定的有机碳含量 - 概率分布位置/变量类型：m = 均值 - 空间分辨率：30m - 深度参考：b30cm..60cm = 地下30-60cm区间 - 时间起始：20000101 = 2000-01-01 - 时间结束：20051231 = 2005-12-31 - 空间范围：g = 全球 - EPSG代码：EPSG:4326 - 版本号：v20250204 = 2025年2月4日发布的版本 #### 致谢 本项目由欧盟委员会通过Open-Earth-Monitor项目，以及世界资源研究所（World Resources Institute）通过陆地与碳实验室（Land & Carbon Lab）资助。