Accurate and quick building damage assessment is an indispensable step after a destructive earthquake. Acquiring building damage information of the seismic area in a remotely sensed way enables a timely emergency response. Existing remote sensing building damage detection methods based on convolutional neural network (CNN) mainly need two-step processing or only use single post-event image, leading to low efficiency and inaccurate building boundary. Considering the practical needs of emergency rescue and post-disaster reconstruction, this study proposed a hierarchical building damage assessment workflow using CNN-based direct remote sensing change detection on superpixel level. First, vulnerable building areas close to the epicenter are extracted using extra feature enhancement bands (EFEBs) to narrow the extent of image processing. Then, fine scale building damage is detected in the extracted building areas based on a direct change detection method with pre-event superpixel constraint (PreSC) strategy to improve the precision and efficiency. Finally, a rapid remote sensing earthquake damage index (rRSEDI) is used to quantitatively assess the damage. Experimental results of the case study show that damaged buildings can be effectively and accurately localized and classified using the proposed workflow. Comparative experiments with single-temporal image and post-event segmentation further embody the superiority of the direct change detection. The damage assessment result matches the official report after Ludian earthquake, proving the reliability of the proposed workflow. For future natural hazard events, the workflow can contribute to formulating appropriate disaster management, prevention and mitigation policies.

准确、快速的建筑损坏评估是破坏性地震发生后不可或缺的一步。以遥感方式获取地震区的建筑物损坏信息，可以及时进行应急响应。现有基于卷积神经网络（CNN）的遥感建筑物损伤检测方法主要需要两步处理或仅使用单个事后图像，导致效率低且建筑物边界不准确。考虑到应急救援和灾后重建的实际需求，本研究提出了一种基于CNN的超像素级直接遥感变化检测的分层建筑物损伤评估工作流程。首先，使用额外的特征增强带（EFEB）提取靠近震中的易受攻击的建筑区域，以缩小图像处理的范围。然后，基于事件前超像素约束（PreSC）策略的直接变化检测方法在提取的建筑物区域中检测精细尺度的建筑物损坏，以提高精度和效率。最后，使用快速遥感地震破坏指数（rRSEDI）对破坏进行定量评估。案例研究的实验结果表明，使用所提出的工作流程可以有效、准确地对受损建筑物进行定位和分类。单时相图像和事后分割的对比实验进一步体现了直接变化检测的优越性。损伤评估结果与鲁甸地震后的官方报告相符，证明了所提工作流程的可靠性。对于未来的自然灾害事件，工作流程有助于制定适当的灾害管理，