Carbon map and uncertainty in forested areas of Canada, 250m spatial resolution

This project aimed to produce the first wall-to-wall estimate of C stocks in plants and soils of Canada at 250 m spatial resolution. This dataset contains the map with total C stored in plants of forested areas in Canada (AGB, BGB and dead plants) in kg/m² and C stock uncertainty. To estimate the C stored in plants of forest areas, we used 47,967 ground measurements of AGB measures and 58 covariates mainly composed of optical data, terrain parameters, structural parameters (e.g., SAR data, clump index, canopy heights – generated from satellite LiDAR- <i>included in the other dataset</i>), soil type map and radiation flux data. Different models were trained using a recursive feature elimination, random forest scheme and a 5-fold cross-validation assessment. The model with higher R² and lowest root mean square error (RMSE) was used for spatial prediction of AGB in forest areas while 1^st and 3^rd quantiles of RF quantile regression were used to build the uncertainty map. After generating the AGB map, the root biomass of forest areas was computed by its relationship to AGB according to forest type. The dead plant materials were computed by a linear regression between live and dead AGB defined with ground measurements. Ultimately, the AGB as well as dead plant materials and BGB were multiplied by 0.5 to provide the maps in kg C m^-2.

本项目旨在生成首个空间分辨率为250米的加拿大全境植物与土壤碳储量全覆盖估算结果。本数据集包含加拿大森林区域植物总碳储量（地上生物量（Aboveground Biomass, AGB）、地下生物量（Belowground Biomass, BGB）及死亡植物碳库）的空间分布图（单位：kg/m²），以及对应碳储量的不确定性数据。为估算森林区域的植物碳储量，研究团队采用了47967组地上生物量实地测量数据，以及58项协变量，协变量主要包括光学数据、地形参数、结构参数（如合成孔径雷达（Synthetic Aperture Radar, SAR）数据、聚集指数、基于卫星激光雷达（Light Detection and Ranging, LiDAR）生成的冠层高度——详见其他数据集）、土壤类型图与辐射通量数据。研究通过递归特征消除、随机森林建模方案结合5折交叉验证开展多模型训练，最终选取决定系数（R²）最高且均方根误差（Root Mean Square Error, RMSE）最低的模型，用于森林区域地上生物量的空间预测；同时利用随机森林分位数回归的第1分位数与第3分位数，构建碳储量不确定性分布图。生成地上生物量分布图后，研究依据森林类型与地上生物量的相关关系，计算得到森林区域的地下生物量；死亡植物碳库则通过实地测量得到的活体与死亡地上生物量间的线性回归关系进行估算。最终将地上生物量、死亡植物碳库及地下生物量乘以系数0.5，得到单位为kg C m⁻²的碳储量空间分布图。