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合成孔径雷达差分干涉测量技术(D-InSAR)可监测地球表面的微量形变,包括地震、火山活动、冰川漂移、地面沉降、活动断裂及山体滑坡等引起的地表位移,是近年来发展起来并得到日益重视的新方法,与其他监测方法(如GPS监测等)相比,用D-InSAR进行地面微位移监测具有全天时、全天候、精度高、覆盖范围大且空间连续的巨大优势。采用D-InSAR技术对阿尔金东段构造变形特征进行了研究,结果表明,阿尔金断裂带是青藏高原东北缘地壳变形的重要分界线。界线以北地区变形均匀,而且变形量较小;以南地区变形强烈且不均匀,变形强度的总体趋势为西高东低,中间受北祁连断裂带西段的影响,在断裂带中出现约为1.0cm的变形低值。另外,南区存在N65°W和近NW两个方向的线性强变形带,前者与阿尔金走滑断裂带次一级的压扭面方向一致,后者与北祁连断裂带西段的展布方向一致。 相似文献
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基于卫星遥感的潮滩植被、高程、潮沟空间关系探讨-以崇明东滩为例 总被引:2,自引:1,他引:2
The analysis of vegetation-environment relationships has always been a study hotspot in ecology. A number of biotic, hydrologic and edaphic factors have great influence on the distribution of macrophytes within salt marsh.Since the exotic species Spartina alterniflora(S. alterniflora) was introduced in 1995, a rapid expansion has occurred at Chongming Dongtan Nature Reserve(CDNR) in the Changjiang(Yangtze) River Estuary, China.Several important vegetation-environment factors including soil elevation, tidal channels density(TCD),vegetation classification and fractional vegetation cover(FVC) were extracted by remote sensing method combined with field measurement. To ignore the details in interaction between biological and physical process,the relationship between them was discussed at a large scale of the whole saltmarsh. The results showed that Scirpus mariqueter(S. mariqueter) can endure the greatest elevation variance with 0.33 m throughout the marsh in CDNR. But it is dominant in the area less than 2.5 m with the occurrence frequency reaching 98%. S. alterniflora has usually been found on the most elevated soils higher than 3.5 m but has a narrow spatial distribution. The rapid decrease of S. mariqueter can be explained by stronger competitive capacity of S. alterniflora on the high tidal flat. FVC increases with elevation which shows significant correlation with elevation(r=0.30, p0.001). But the frequency distribution of FVC indicates that vegetation is not well developed on both elevated banks near tidal channels from the whole scale mainly due to tidal channel lateral swing and human activities. The significant negative correlation(r=–0.20, p0.001) was found between FVC and TCD, which shows vegetation is restricted to grow in higher TCD area corresponding to lower elevation mainly occupied by S. mariqueter communities. The maximum occurrence frequency of this species reaches to 97% at the salt marsh with TCD more than 8 m/m2. 相似文献
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随着雷达成像技术和高分辨率光栅显示技术的发展和应用,基于船载雷达图像的船只检测成为可能.海上船只检测的主要困难之一是雷达图像中包含固有的海面背景杂波.传统的雷达船只检测方法,如恒虚警率法(CFAR),以杂波分布模型为基础,计算待检测窗口中的信号统计分布来确定自适应阈值,取得了一些成果.但是,当海面背景杂波和船只目标的回波强度在同一数量级,甚至船只目标淹没在海面背景杂波中时,就难以确定一个有效的阈值将船只目标从雷达图像中提取出来.在分析海面背景杂波和船只目标的相关差异性基础上,提出了一种基于船载雷达序列图像的海上船只快速检测方法.该方法首先对相邻两幅图像进行互相关性分析,在两幅图像中的同一位置提取一定尺寸的移动窗口,计算其互相关函数值,窗口移动一个步长,重复操作直至遍布整幅图像,形成一幅由灰度图像互相关函数值组成的相关图像.然后使用概率神经网络模型(PNN模型)来估计相关图像背景杂波的灰度概率密度分布函数(PDF),应用CFAR技术,使用二分法求解一个区分船只和背景噪声的自适应整体阈值,并根据阈值将相关图像二值化,其中大于阈值的像元作为候选的船只目标信息,小于阈值的像元则为海面背景杂波.最后使用连通性8-邻域准则统计各个候选船只目标区域的像元数,并与预先定义的最小船只目标像元数进行比较,偏小的候选船只目标区域作为虚警去除,保留下来的候选船只目标区域即为船只检测结果.研究显示,如果图像序列中没有船只目标信息,则三维相关图像比较平整.相反,如果图像序列中含有船只目标信息,则三维相关图像上有峰值被检测出,通过测量峰值的高度,就能判断存在可能的船只目标.运用X波段船载雷达序列图像对本文提出的海上船只检测方法进行了测试.测试结果表明,该检测方法具有很好的船只检测效果,得到的船只检测结果与目视判别的结果一致.而且该检测算法原理简单,计算速度快,易于实时处理,具有广阔的应用前景. 相似文献
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