明确森林损毁成因对于制定森林保护政策至关重要，当前准确且全面地识别森林损毁驱动因素仍面临巨大挑战。本文选择森林损毁现象严重、驱动因素多样化的非洲，采用全球30 m地表覆盖动态监测产品、人类足迹数据、火灾数据、森林管理数据、气象数据等多源空间数据集，构建了基于决策树规则的森林损毁驱动因素分类框架，将非洲森林损毁归因于五种人为因素和三种自然因素。基于目视解译样本的精度评估结果显示，驱动因素分类结果的总体精度约95.38%。驱动因素分析结果表明：（1）2000至2020年间非洲近86.73%的森林损毁由人为因素导致，且这一比例持续上升，而自然因素仅占13.27%；（2）农业用地侵占和林业砍伐是最重要的两类驱动因素，分别导致了44.02%和11.40%的森林损毁；（3）几乎所有人为因素导致的森林损毁速度都翻倍增长，并呈现加速趋势。因此，迫切需要采取更具针对性和更有力的森林保护行动，以实现2030年之前遏止森林面积持续下降的可持续发展目标。

Objective: Identifying the drivers of forest loss is essential for developing forest management policies, yet accurately and comprehensively classifying these drivers on a large scale remains a significant challenge. In this study, we focused on Africa, a region experiencing severe forest loss due to various human activities and natural disturbances. Our objectives are twofold: (1) to generate a spatially explicit and dynamic dataset for proximate drivers of forest loss, and (2) to quantitatively analyze their spatiotemporal patterns. Method: Our approach consists of three main steps. First, we developed a decision tree-based classification framework to attribute annual forest loss in Africa to five human and three natural drivers. This framework integrates multi-source remote sensing data—including a global 30-m land cover dynamic monitoring dataset, human footprint pressure, fire occurrences, forest management practices, and the Standardized Precipitation Evapotranspiration Index (SPEI)—following a hierarchical approach based on identification difficulty. Second, we validated the driver classification results using approximately 15,000 third-party visual interpretation samples at a 1 km × 1 km resolution. Additionally, we compared our results with prior studies and systematically analyzed the sources of observed discrepancies. Finally, we quantified forest loss driven by different drivers across three spatial scales: the entire African continent, distinct geographical zones, and latitudinal gradients. We further examined temporal dynamics and long-term trends at both continental and zonal levels. Result: We developed a 30-m annual forest loss driver dataset for Africa (2000–2020) with an overall accuracy of 95.38% in pan-tropical regions. Over this period, Africa experienced an estimated 93.51 Mha of forest loss, with human activities responsible for 86.73% of the loss and natural drivers accounting for 13.27%. Agricultural encroachment was the leading driver, causing 44.02% of the total loss, followed by forestry activity (11.40%). At a finer scale (0.01°×0.01°), agricultural encroachment was the dominant driver in most areas. Its impact increased significantly, from 1.53±0.24 Mha/yr (2001–2011) to 2.71±0.23 Mha/yr (2012–2020), peaking at 3.01 Mha/yr in 2014. Forestry activity declined slightly before 2012 but nearly doubled by 2020 (1.00 Mha/yr vs. 0.52 Mha/yr in 2001). All human drivers, except for impervious surface expansion, displayed significant accelerating trends. Agricultural encroachment showed the most pronounced increase (0.08 Mha/yr2, P<0.05), followed by forestry activity (0.03 Mha/yr2, P<0.05). In contrast, natural drivers remained stable or declined, with persistent drought showing a decrease of -0.01 Mha/yr2 (P<0.05). The dominance of human activities in African forest loss intensified over time, rising from 80.62% in 2001 to 90.38% in 2020. Agricultural encroachment remained the primary driver throughout 2000–2020, peaking at 49.50% of total loss in 2014. The contribution of forestry activity rose sharply from 9.93% in 2001 to 18.61% in 2020, surpassing human-induced fire as the third-largest driver after 2013. Conclusion: This study integrates multi-source remote sensing datasets to develop a decision tree-based classification framework for identifying the proximate drivers of forest loss during 2000–2020 in Africa. The driver classification results achieved an overall accuracy of 95.38% in the pan-tropical regions. Our analysis revealed that human activities were responsible for nearly 86.73% of Africa’s forest loss during this period, with their impacts continuing to grow, while natural drivers accounted for only 13.27%. Among the human drivers, agricultural encroachment (44.02%) and forestry activity (11.40%) were the two most significant contributors to forest loss. Notably, the rate of forest loss driven by nearly all human drivers has doubled over time, showing an accelerating trend. These findings highlight the urgent need for stronger forest conservation efforts, as Africa remains far from achieving SDG 15.2 (sustainable forest management), particularly in regions facing rapid agricultural expansion.