News media provides time and data guarantee for rapid post-disaster assessment. However, disaster information from news media often suffers from semantic ambiguity and conflicting content, and disaster information changes over time. These characteristics of disaster information seriously affect its application in disaster assessment. How to obtain timely reasonable quantitative disaster assessment results based on this kind of disaster information is the key to making full use of media information, but existing studies rarely have addressed the issue. This paper proposes a novel method to assess the percentage of buildings collapse by leveraging timely disaster information with geographical positions. The method includes four parts. First, based on preprocessing of disaster information, the cloud model is used to quantitatively express fuzzy disaster information and construct basic probability assignments (BPAs) for different ranges of buildings collapse. Second, the conflict and ambiguity of each item of disaster information is analyzed, and its credibility is measured. Based on this, the BPAs are modified to reduce conflicting disaster information. Third, multiple items of disaster information are fused by using Dempster–Shafer theory to obtain buildings damage assessment results. Finally, the assessment results of the previous stage are dynamically updated with new information. The method is applied to Ya'an earthquake on April 20, 2013 and Yi'bin earthquake on June 17, 2019. The assessment results are analyzed and compared with those obtained by other methods, and it is found that the method can obtain reliable results in a short time. This study can provide a reference for timely emergency decision-making.

新闻媒体为快速的灾后评估提供时间和数据保障。但是，来自新闻媒体的灾难信息经常遭受语义歧义和内容冲突的困扰，并且灾难信息会随着时间而变化。灾害信息的这些特征严重影响了其在灾害评估中的应用。如何根据这类灾害信息及时获得合理的定量灾害评估结果，是充分利用媒体信息的关键，但现有研究很少解决这一问题。本文提出了一种通过利用及时的灾害信息和地理位置来评估建筑物倒塌百分比的新颖方法。该方法包括四个部分。首先，基于灾难信息的预处理，云模型用于定量表达模糊灾害信息，并为不同范围的建筑物倒塌构造基本概率分配（BPA）。其次，分析了每项灾害信息的冲突和模糊性，并评估了其可信度。基于此，对BPA进行了修改以减少冲突的灾难信息。第三，运用Dempster-Shafer理论融合多种灾害信息，以获取建筑物破坏评估结果。最后，前一阶段的评估结果将动态更新为新信息。该方法适用于2013年4月20日的雅安地震和2019年6月17日的宜宾地震。分析评估结果并与其他方法得出的结果进行比较，发现该方法可以在短时间内获得可靠的结果。该研究可为及时的应急决策提供参考。