Spatially explicit environmental variables at 25m resolution for spatial modelling in the Netherlands

This dataset contains 206 spatially explicit environmental variables, also termed covariates, at 25m resolution that cover the entire Netherlands (national scale). The raster data are comprised of covariates related to the soil-forming factors (climate, organism/land use/land cover, relief/topography, parent material/geology) for the purpose of using them for digital soil mapping. However, since the covariates cover a wide range of environmental variables, they can potentially be used for spatial modelling in the Netherlands also outside the field of soil science. All covariates can also be found from the original source, but the potential strength and practicality of this dataset lies in the broad range of readily available, collected, prepared and harmonized raster data.<br>The metadata of all the covariates in this dataset can be found in the "00_covariates_metadata.csv" file, including information about the names, category, value types, specific value types, type of geospatial data, file type, whether its static or dynamic, temporal coverage, date/version, resolution (all 25m), origin, source, access/license, description, processing steps and comments. The dataset includes 3 different types of files:GeoTIFF (.tif): the covariates as raster data at 25m resolution in the EPSG:28992 (Amersfoort / RD New) spatial projectionText (.txt): README files for each covariate with additional metadata information (filename ending in "_readme.txt")Tabular data (.csv): Classification and re-classification table for categorical covariates (filename ending in "_reclassify.csv")<br>Note that the reclassification tables contain potential ways to reclassify the data provided, but can be altered by the user. Reclassification may be useful for categorical covariates with a large number of classes/categories. Note that covariates with CC BY-ND 4.0 licenses, covariates that are not open data or for which the license was unknown are not shared in this dataset.<br>More information about these covariates can be found in the associated scientific paper "BIS-4D: Mapping soil properties and their uncertainties at 25m resolution in the Netherlands" (Helfenstein et al., 2024, under review). Different ways of pre-processing and preparing the covariates for subsequent modelling can be found in R scripts 20-25 in the associated code repository on GitLab. This includes assembling and preparing covariates using GDAL ("20_cov_prep_gdal.R"), computing digital elevation model (DEM) derivatives using SAGA GIS ("21_cov_dem_deriv_saga.R"), deriving spectral indices from RGBNIR bands of Sentinel 2 images ("22_cov_sensing_deriv.R"), preparing categorical covariates using GDAL ("23_cov_cat_recl_gdal.R"), deriving dynamic covariates ("24_cov_dyn_prep_gdal.R") and exploratory analysis of the covariates ("25_cov_expl_analysis_clorpt.Rmd", "25_cov_expl_analysis_cont_cat.Rmd").

本数据集包含206个空间显式环境变量（亦称为协变量），分辨率为25米，覆盖荷兰全境（国家尺度）。这些栅格数据涵盖与成土因子相关的协变量，包括气候、生物/土地利用/土地覆被、地形/地貌、母质/地质，旨在用于数字土壤制图。不过，由于本数据集的协变量覆盖了广泛的环境变量范畴，其应用场景亦可拓展至荷兰境内土壤科学以外的其他空间建模领域。所有协变量均可从原始来源获取，而本数据集的优势与实用价值在于，其收录了大量已完成收集、预处理与协调统一的现成栅格数据。<br>本数据集所有协变量的元数据可在"00_covariates_metadata.csv"文件中获取，涵盖名称、类别、数值类型、具体数值类型、地理空间数据类型、文件格式、静态/动态属性、时间覆盖范围、日期/版本、分辨率（均为25米）、来源、获取方式/许可协议、描述信息、处理步骤与备注。本数据集包含3类文件：<br>1. GeoTIFF（.tif）：以EPSG:28992（Amersfoort / RD New）空间投影格式存储的25米分辨率协变量栅格数据<br>2. 文本文件（.txt）：各协变量的README文档，包含补充元数据信息（文件名以"_readme.txt"结尾）<br>3. 表格数据（.csv）：分类协变量的分类与重分类表（文件名以"_reclassify.csv"结尾）<br>需注意，重分类表仅提供了可供参考的数据重分类方案，用户可根据需求自行调整。对于类别数量较多的分类协变量，重分类操作具备实际应用价值。此外，本数据集未包含采用CC BY-ND 4.0许可协议的协变量、非开放数据协变量以及许可信息未知的协变量。<br>更多关于这些协变量的细节可参阅相关学术论文《BIS-4D: Mapping soil properties and their uncertainties at 25m resolution in the Netherlands》（Helfenstein等人，2024，待刊）。GitLab关联代码仓库中的R脚本20至25则介绍了协变量的多种预处理与制备方法，具体包括：使用GDAL组装并预处理协变量（"20_cov_prep_gdal.R"）、通过SAGA GIS计算数字高程模型（DEM）衍生变量（"21_cov_dem_deriv_saga.R"）、从Sentinel 2影像的RGBNIR波段提取光谱指数（"22_cov_sensing_deriv.R"）、使用GDAL预处理分类协变量（"23_cov_cat_recl_gdal.R"）、生成动态协变量（"24_cov_dyn_prep_gdal.R"）以及协变量探索性分析（"25_cov_expl_analysis_clorpt.Rmd"、"25_cov_expl_analysis_cont_cat.Rmd"）。