基于地球多传感器网络信息的潜在滑坡判识模型

潜在滑坡的判识是滑坡预测预报中的关键问题,潜在滑坡早期判识能够有效减少灾害的发生。基于滑坡灾害诱发的各种影响因素,利用地球多源时空信息和多传感器网络,遥感监测潜在滑坡体,利用监测设备获取滑坡岩性、坡体结构、地貌形态、活动迹象等关键控制信息,从中选取滑坡灾害诱发的主要控制要素作为判识指标,建立基于多源信息的潜在滑坡多因素判识模型;特别是根据滑坡的成灾规律,分析潜在滑坡孕育过程中地貌形态改变、成灾条件变化与滑坡发生的临滑诱发条件,建立基于不同信息源的滑坡控制因素判识模型。最后,通过汶川地震灾区垮梁子滑坡体实例分析,验证潜在滑坡综合判识模型并进行优化,从而为滑坡灾害的早期判识预测提供依据。

Potential Landslide Discrimination Model Based on Information of Earth Multi-sensor Net

Discrimination of potential landslide is the key question for landslides forecast, and the early discrimination of potential landslide can effectively reduce the disaster. Based on various factors induced by landslide disaster, potential landslides were monitored by the means of earth multi-source space-time information, earth multi-sensor net and remote sensing; the key information including landslide lithology, slope structure, landform shape and activity evidence were collected, and the main control factors induced by landslide disaster were selected from the key information; potential landslide multi-factor discrimination model was built based on multi-source information. Especially, according to the law of landslide disaster, the changes of landform shape, hazard condition and critical landslide induced condition during the potential landslides breed were analyzed, landslide control factor discrimination model was built based on different information sources. Finally, taking Kualiangzi landslide in Wenchuan earthquake disaster area as an example, the integrated discrimination model of potential landslide was verified and optimized in order to provide the basis of the early discrimination prediction of landslide disaster.