Soil organic carbon (SOC) is a critical measure for ecosystem health and offers opportunities to understand carbon fluxes and associated implications. However, SOC can be significantly influenced by anthropogenic land use change, with intensive and extensive disturbances resulting in considerable SOC loss. Consequently, understanding the spatial distribution of SOC across different land uses, particularly at national level characterised by different biomes, is vital for integrated land-use planning and climate change mitigation. Remote sensing and deep learning (DL) offer a reliable largescale mapping of SOC by leveraging on their big data provision and powerful analytical prowess, respectively. This study modelled SOC stocks across South Africa’s major land uses using Deep Neural Networks (DNN) and Sentinel-3 satellite data. Based on 1936 soil samples and 31 spectral predictors, results show a relatively high accuracy with an R² and RMSE value of 0.685 and 10.15 t/h (26% of the mean), respectively. From the seven land uses evaluated, grasslands (31.36%) contributed the most to the overall SOC stocks while urban vegetation (0.04%) contributed the least. Moreover, although SOC stock was found to be relatively proportional to land coverage, commercial (46.06 t/h) and natural (44.34 t/h) forests showed a higher carbon sequestration capacity. These findings provide an important guideline to managing SOC stocks in South Africa, useful in climate change mitigation through sustainable land-use practices. Whereas landscape restoration, and other relevant interventions are encouraged to improve SOC storage, care must be taken within land-use decision making to maintain an appropriate balance between carbon sequestration, biodiversity, and general ecosystem functions.

土壤有机碳 (SOC) 是衡量生态系统健康的关键指标，为了解碳通量和相关影响提供了机会。然而，土壤有机碳会受到人为土地利用变化的显着影响，密集和广泛的干扰会导致土壤有机碳的大量损失。因此，了解不同土地利用的 SOC 空间分布，特别是在以不同生物群落为特征的国家层面，对于综合土地利用规划和减缓气候变化至关重要。遥感和深度学习 (DL) 分别利用其大数据提供和强大的分析能力，提供可靠的大规模 SOC 映射。本研究使用深度神经网络 (DNN) 和 Sentinel-3 卫星数据对南非主要土地用途的 SOC 库存进行了建模。²RMSE 值分别为 0.685 和 10.15 吨/小时（平均值的 26%）。在评估的七种土地利用中，草地（31.36%）对总有机碳储量的贡献最大，而城市植被（0.04%）贡献最小。此外，虽然发现 SOC 储量与土地覆盖率相对成比例，但商业（46.06 吨/小时）和天然（44.34 吨/小时）森林显示出更高的碳封存能力。这些发现为管理南非的 SOC 库存提供了重要的指导方针，有助于通过可持续的土地利用实践缓解气候变化。尽管鼓励景观恢复和其他相关干预措施以改善 SOC 储存，但在土地利用决策中必须小心，以保持碳封存、生物多样性和一般生态系统功能之间的适当平衡。