STUDY OF THE TECHNIQUE FOR LANDSLIDE RAPID RECOGNITION BY INSAR
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摘要: 研究探索了一条以InSAR变形为主,辅助光学遥感、地貌和地质条件特征,进行活动性滑坡快速排查的技术方法,并以四川省雷波县域为例进行了实验。应用4种SAR数据(PALSAR-1升轨、Sentinel-1 A/B升、降轨和PALSAR-2降轨数据)进行合成孔径雷达干涉(Interferometric Synthetic Aperture Radar,InSAR)处理,共解译活动性地质灾害163处,并分析了其时空分布规律,获得了几点认识:(1)InSAR技术能够追溯滑坡长期微小变形,从而实现活动性滑坡的有效识别;(2)多时段、多角度和多分辨率SAR数据的综合使用,可以有效克服滑坡观测的阴影叠掩、失相干等问题,提高滑坡(尤其是高位滑坡)识别的效果、效率和时效性;(3)与地面调查结果比较,InSAR识别的滑坡更全面、规模更准确,对高位滑坡和集中分布滑坡识别更有效,可以作为现今地质灾害排查的重要手段之一;(4)雷波县地质灾害主要分布在金沙江及美姑河沿岸,北向坡和30°~40°坡度是地质灾害高发区,除寒武系、奥陶—志留系地层发生地质灾害比例较高,其它各地层总体分布较均一。Abstract: An active landslide rapid recognition method, based on InSAR deformation and assisted by optical remote sensing, geomorphologic features and geological conditions, is presented in this article and Leibo County of Sichuan Province is chosen to be the study area. Four type of SAR data, PALSAR-1/2 as-/descend and Senitnel-1A/B de-/ascend are processed, with interpretation of 163 landslides overall and analysis of spatial and temporal distribution, from which some important conclusions are drawn. (1) InSAR can trace long and small deformation so as to realize effective recognition of active landslides; (2) The use of multiple types SAR data can overcome the shortages of InSAR, such as layover, shadow, incoherence, to improve the efficiency, effect and timeliness; (3) Compared with field investigation results, landslides recognized by InSAR are more comprehensive and accurate, especially for high-position and centralized landslides, and therefore InSAR can be taken as one of the important methods for landslide survey; (4) The landslides in Leibo county mainly occurred along the Jinsha river and the Meigu river, on the north slope and slope areas with a gradient from 30° to 40°. The overall distribution of geological hazards in each stratum is even, except for the Cambrian and Ordovician-Silurian with a relatively high ratio.
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Key words:
- landslide /
- geological hazard recognition /
- InSAR /
- SAR data /
- Leibo County in Sichuan province
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图 8 滑坡在不同地层岩性中分布的比例
O-Shx—奥陶—志留系红石崖组—回星哨组碳酸盐岩及碎屑岩;∈—寒武系筇竹寺组—娄山关组泥页岩、粉砂岩、砂岩、灰岩、白云岩(底部含磷);O-Sd—奥陶—志留系红花园组/大路寨组并层页岩、笔石页岩、灰岩夹钙质页岩、钙质砂岩、白云岩;T3C—上三叠统宝顶组/白果湾组陆相长石石英砂岩、粉砂岩、泥岩夹煤;P2-3s—中—上二叠统树河组/梁山组—宣威组/黑泥哨组下部为砂页岩、灰岩、白云岩,上部为拉斑玄武岩偶含砂页岩;T1-2PLF—下—中三叠统飞仙关组—雷口坡组台地相以灰岩、白云岩为主,底部为页岩,顶部岩溶角砾岩;P2-3x—中上二叠统梁山组/峨眉山组—宣威组并层砂岩夹页(泥)岩、煤层,灰岩及玄武岩;Z—震旦系观音崖组—灯影组白云岩,底为砂岩、页岩;T1PLF—下三叠统东川组/飞仙关组—嘉陵江组台地相,以灰岩、白云岩为主,底部页岩;J2—中侏罗统千佛岩组—沙溪庙组,灰—紫红色泥岩、粉砂岩、砂岩夹灰岩;T1MS—下三叠统飞仙关组浅海相紫红色泥(页)岩夹灰岩;J1—下侏罗统自流井组/新田沟组紫红色泥岩、砂岩、粉砂岩夹灰岩、泥灰岩
Figure 8. Percentage of landslides in different strata and lithologies
表 1 所选数据类型及卫星传感器基本参数
Table 1. The selected data type and main parameters of the satellite sensor
星载SAR系统 波长/cm 极化方式 观测方向 数据日期 平均基线/m 侧视角/(°) 分辨率/m 灾害个数 PALSAR-1 L(23.6) HH 升轨 2007-07-07、2007-08-22、2007-08-22、2008-01-07、2008-04-08、2008-05-24、2009-01-09、2009-02-24、2009-08-27、2010-01-12、2010-02-27、2011-01-15和2011-03-02 299 38.74 12 75 PALSAR-2 L(23.8) HH 降轨 2016-10-22和2017-01-28 56 39.66 3.0 81 Sentinel-1 A/B C(5.6) VV 升轨 2016-01-07和2017-03-08 45 33.91 15 11 Sentinel-1 A/B C(5.6) VV 降轨 2016-12-03和2017-12-27 30 33.95 15 34 -
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