地基SAR数据优化及灾变体面积预警预报分析

针对地基SAR异常数据难以识别、潜在滑坡体发展特征及规律不明显、临滑面积估算难度大的问题，本文以甘肃某矿山滑坡数据为基础，介绍了地基SAR形变数据的处理方法，通过Matlab软件有效地识别、筛选、剔除了异常形变数据，并以色彩差异进行区分，进一步突显了不同阶段潜在灾变体面积的演化规律。基于地基雷达监测原理，提出一种多边形面域估算方法，实现潜在危险区域面积的估算。研究不等周期处理的速度倒数曲线组，发现速度倒数平方法能够进一步放大特征趋势，预测结果准确、预报效果好，为实现矿山滑坡超前预警预报提供了新的思路。

Optimization of ground-based SAR data and analysis of disaster body area early warning and prediction

Aiming at the problems that it is difficult to identify the ground-based SAR abnormal data, the development characteristics and laws of potential landslide mass are not obvious, and it is difficult to estimate the critical sliding area, this paper introduces the processing method of ground-based SAR deformation data based on the landslide data of a mine in Gansu province. The abnormal deformation data are effectively identified, screened and eliminated by Matlab software, and distinguished by color differences, which further highlights the evolution law of potential disaster body area in different stages. Based on the principle of ground-based radar monitoring, a polygon area estimation method is proposed. This method can estimate the area of potentially hazardous areas. Study on velocity reciprocal curve group with unequal period treatment, it is found that the inverse square method of velocity can further amplify the characteristic trend. The early warning result is accurate and the prediction effect is good through this early warning and prediction method, which provides a new idea for realizing the early warning and prediction of mine landslide.