2021年山西省古建筑脆弱性评估数据

文物信息特征由文物四有档案和实地获取数据定义构建。建立“古建筑—大风”灾害模型，数据由机器学习、深度学习方法自动获取，准确率、精确率、召回率较高，符合行业要求。古遗址本体脆弱性、孕灾环境敏感性通过监测报告、相关文献以及网络爬虫获取，通过知识融合进行语义消歧，数据质量较好。大风自然灾害危险性通过访问中央气象台台风网、气象站进行历史查询获取，数据来源可靠。通过风速传感器，风向传感器，遥感等方法进行监测获取，数据实时性强。

Cultural relic information features are defined and constructed based on the "four-required" archives of cultural relics and field-collected data. A "ancient architecture - strong wind" disaster model was established. The data was automatically acquired via machine learning and deep learning methods, with high accuracy, precision and recall, meeting industry standards. The vulnerability of ancient ruin entities and the sensitivity of disaster-inducing environments are obtained through monitoring reports, relevant literature and web crawlers, and semantic disambiguation is performed via knowledge fusion, resulting in good data quality. The hazard of strong wind natural disasters is obtained through historical queries by accessing the Typhoon Network of the Central Meteorological Observatory and meteorological stations, with reliable data sources. Monitoring and data acquisition are carried out via wind speed sensors, wind direction sensors, remote sensing and other methods, ensuring strong real-time performance of the data.

搜集汇总

背景与挑战

背景概述

该数据集是2021年山西省古建筑脆弱性评估数据，专注于评估古建筑在大风自然灾害下的脆弱性。它通过机器学习、深度学习方法和多源数据（如监测报告、气象站数据和遥感信息）自动生成，构建了'古建筑-大风'灾害模型，具有高精度、良好数据质量和实时性特点，数据分辨率为0.005°，覆盖山西省全境。