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作 者:程乙峰[1,2,3] 刘志辉[1,2]
机构地区:[1]新疆大学资源与环境科学学院,乌鲁木齐830046 [2]绿洲生态教育部重点实验室,乌鲁木齐830046 [3]新疆基础地理信息中心/新疆测绘档案资料馆,乌鲁木齐830002
出 处:《测绘科学》2016年第8期95-100,共6页Science of Surveying and Mapping
摘 要:针对传统知识驱动型滑坡灾害研究多依赖专业人员经验,具有主观性和不确定性的问题,该文提出了基于数据驱动滑坡致灾因子评价及危险性区划的方法。采用证据权模型,较好地平衡了滑坡危险性区划中准确性与高效性之间的矛盾,实现了较为精确的滑坡易发性及危险性区划;利用感知层、网络层、应用层的物联网技术,实现了高危险区滑坡点在线预警监测。3S技术支持下的滑坡危险性区划及监测实验结果表明:所用模型及监测技术不仅可以准确评价滑坡致灾因子权重及危险性区划,还能够精准、高效实现滑坡点实时监控预警。Aiming at problems which traditional knowledge-driven landslide disaster research is dependent on more professionals experience with subjective and uncertainties,the evaluation of landslide hazards and implement hazard zoning approach were proposed based on data-driven method.The conflict in landslide hazard zonation between accuracy and efficiency was balanced by the weights of evidence model to achieve a more accurate landslide susceptibility and hazard zoning;on this basis,online early warning and monitoring of high hazard landslide zones were realized by using the perception layer,network layer and application layer of the Internet of things(IoT).Landslide hazard zoning and monitoring based on 3Stechnology showed that the proposed models could not only evaluate the landslide hazard zonation and risk weights accurately,but also achieve real-time monitoring of landslide early warning efficiently.
分 类 号:P208[天文地球—地图制图学与地理信息工程]
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