Data from: Soil Landscapes of the United States 100-meter (SOLUS100) soil property maps project repository

This repository provides extended documentation, code, and updated links to access the Soil Landscapes of the United States (SOLUS) 100-meter soil property maps. It provides supporting materials for a peer reviewed paper (Nauman et al., In Review) documenting the theory and novel application of hybridized legacy training datasets used to inform the machine learning models used to create the new soil property maps presented here. The SOLUS dataset includes 20 different soil properties (listed below) with most properties predicted for seven standard depths (0, 5, 15, 30, 60, 100, and 150 cm). Further details on these properties and all included files are available in the README.docx document. Also included is a git repository formatted as a hybrid R package that includes all code used to create the soil property maps.All SOLUS100 mapping layers are available as cloud optimized geotiffs at: https://storage.googleapis.com/solus100pub/index.htmlMetadata: https://storage.googleapis.com/solus100pub/SOLUS100_metadata_pub.htmlList of files at this URL are listed at: https://storage.googleapis.com/solus100pub/Final_Layer_Table_20231215.csvNote that many of the raster files are scaled by multipliers of 10, 100, or 1000 to store the values as integers to decrease file size. The ‘scalar’ field of the file list table (Final_Layer_Table_20231215.csv) files provide those values. The actual rasters must be divided by the scalars to get the actual units of the properties. To download files, simply concatenate the google API URL with a forward slash and the file name listed in the table into a browser (e.g. EC at 0 cm would be https://storage.googleapis.com/solus100pub/ec_15_cm_p.tif). To automate downloads, a loop in python, R or your language of choice that builds file download urls from the file list in the csv can be implemented. Alternatively, some GIS programs (e.g. QGIS) will let you visualize and interact with the files without downloading the files by entering the URL.All raster environmental covariates used in mapping are available here: https://storage.googleapis.com/cov100m/index.htmlProperties included in SOLUS100:Bulk density (oven dry) Calcium carbonate Cation Exchange Capacity (pH 7) Clay Coarse sand Electrical Conductivity (sat. paste) Effective cation exchange capacity Fine sand Gypsum (in <20 mm fraction) Medium sand pH (1:1 method) Rock content Sand Sodium adsorption ratio Silt Soil organic carbon Very coarse sand Very fine sand Depth to bedrock Depth to restrictionNauman, T.W., Kienast-Brown, S., White, D.A. Brungard, C.W., Philippe, J., Roecker, S.M., Thompson, J.A. Soil Landscapes of the United States (SOLUS): developing predictive soil property maps of the conterminous US using hybrid training sets. In Prep for SSSAJ.

本仓库提供了美国土壤景观（Soil Landscapes of the United States, SOLUS）100米分辨率土壤属性地图的扩展文档、代码以及更新后的访问链接。本资源为一篇已提交同行评议的论文（Nauman等人，待刊）提供了支撑材料，该论文阐述了用于构建本文所述新型土壤属性地图的机器学习模型所采用的混合遗留训练数据集的理论基础与创新应用。
SOLUS数据集包含20种不同的土壤属性（详见下文），其中多数属性针对7个标准深度（0、5、15、30、60、100和150 cm）进行了预测。关于这些属性及所有包含文件的详细信息，请参阅README.docx文档。本仓库还包含一个采用混合R包格式的Git仓库，其中包含了用于生成土壤属性地图的全部代码。
所有SOLUS100制图图层均以云优化GeoTIFF（Cloud Optimized GeoTIFF）格式提供，访问地址为：https://storage.googleapis.com/solus100pub/index.html
元数据页面：https://storage.googleapis.com/solus100pub/SOLUS100_metadata_pub.html
该URL下的完整文件列表详见：https://storage.googleapis.com/solus100pub/Final_Layer_Table_20231215.csv
请注意，多数栅格文件通过乘以10、100或1000的系数将数值存储为整数以减小文件体积。文件列表表格（Final_Layer_Table_20231215.csv）中的"scalar"字段即提供了该系数值。需将实际栅格数据除以该系数，方可得到属性的真实单位数值。
若要手动下载文件，只需将Google API基础URL与正斜杠及表格中列出的文件名拼接后输入浏览器即可（例如，0 cm深度的电导率文件对应链接为https://storage.googleapis.com/solus100pub/ec_15_cm_p.tif）。若需自动化下载，可通过Python、R或其他你偏好的编程语言编写循环脚本，基于CSV文件中的文件列表构建下载链接。此外，部分GIS软件（如QGIS）支持通过输入URL直接可视化并交互查看文件，无需提前下载。
制图过程中使用的所有栅格环境协变量均可在此处获取：https://storage.googleapis.com/cov100m/index.html
SOLUS100包含的土壤属性如下：
1. 容重（烘干基）
2. 碳酸钙
3. 阳离子交换量（pH 7条件下）
4. 黏粒
5. 粗砂
6. 电导率（饱和泥浆法）
7. 有效阳离子交换量
8. 细砂
9. 石膏（<20 mm粒级）
10. 中砂
11. pH（1:1水土比法）
12. 岩石含量
13. 砂粒
14. 钠吸附比
15. 粉粒
16. 土壤有机碳
17. 极粗砂
18. 极细砂
19. 基岩埋深
20. 限制层埋深
参考文献：Nauman, T.W., Kienast-Brown, S., White, D.A., Brungard, C.W., Philippe, J., Roecker, S.M., Thompson, J.A. 美国土壤景观（SOLUS）：基于混合训练集构建美国本土预测性土壤属性地图。提交至SSSAJ待刊。