基于多时相SAR数据的大区域城镇信息变化检测

多时相SAR变化检测技术,通过分析同一区域不同时相的SAR数据可以检测地表地物目标的变化信息,在土地资源调查及监测管理方面具有广泛应用。本文将长时间SAR图像相干性特征与目标幅度信息进行融合,并采用多时相SAR数据堆栈处理方法进行大区域城建目标分类及变化信息检测。最后采用13景ALOS PALSAR数据对中国天津地区2007~2010年期间的城建区域变化进行了检测实验,得到了良好的实验结果,并验证方法有效性。     

大幅场景高分辨率SAR图像机场自动检测

针对现有大场景高分辨率SAR图像机场检测方法中所采用的图像分割方法效果不佳、适应性不强,直线特征提取方法耗时长且易产生断裂的问题,提出一种在大幅场景SAR图像中自动检测机场的方法。首先,提出基于PPB滤波的模糊C均值算法进行图像分割,利用区域特征筛选出感兴趣区域(ROI);然后,采用启发式搜索快速有效地提取线基元,并提出新的共线性测度方法减少线基元连接中的误连接和欠连接;最后,利用平行线特征和灰度特征实现机场的检测。实验结果验证了该方法的有效性。     

Monitoring of the water-area variations of Lake Dongting in China with ENVISAT ASAR images

As an active microwave remote sensing sensor, synthetic aperture radar (SAR) can image the Earth surface with high spatial resolution in both day and night under all weather conditions. In this paper, a digital image processing technique was implemented to extract water area information from SAR images and the result is used to monitor the water area variation of Lake Dongting, the second largest freshwater lake in China. 8-year time series of European Space Agency's ENVISAT ASAR (Advanced Synthetic Aperture Radar) images acquired between 2002 and 2009 were obtained and a land-water classification scheme was implemented. Using independent in situ water level data measured at a lake-side hydrologic station during study period, we derived the relationship between water level and water area of Lake Dongting. The results show that, (1) during dry seasons, the water area is 518 km² larger than that in the 1990s reported by Yangtze BHYRWRC (Bureau of Hydrology and Yangtze River Water Resources Commission), 2000; (2) the water area of Lake Dongting increased significantly in the 2000s after the Chinese Government's “return land to lake” policy took effect in 1998; (3) the water level of Lake Dongting could be low during a rainy season due to drought; but could be high in a dry season due to discharges from the upstream Three Gorges Dam. In addition, the relationship between water storage change and water area/level change is obtained.     

Improving the Wishart Synthetic Aperture Radar image classifications through Deterministic Simulated Annealing

This paper proposes the use of Deterministic Simulated Annealing (DSA) for Synthetic Aperture Radar (SAR) image classification for cluster refinement. We use the initial classification provided by the maximum-likelihood classifier based on the complex Wishart distribution that is then supplied to the DSA optimization approach. The goal is to improve the classification results obtained by the Wishart approach. The improvement is verified by computing a cluster separability coefficient. During the DSA optimization process, for each iteration and for each pixel, two consistency coefficients are computed taking into account two kinds of relations between the pixel under consideration and its neighbors. Based on these coefficients and on the information coming from the pixel itself, it is re-classified. Several experiments are carried out to verify that the proposed approach outperforms the Wishart strategy. We try to improve the classification results by considering the spatial influences received by a pixel through its neighbors. Finally, a link about the contribution of DSA to thematic mapping is also established.     

Ground settlement monitoring based on temporarily coherent points between two SAR acquisitions

An InSAR analysis approach for identifying and extracting the temporarily coherent points (TCP) that exist between two SAR acquisitions and for determining motions of the TCP is presented for applications such as ground settlement monitoring. TCP are identified based on the spatial characteristics of the range and azimuth offsets of coherent radar scatterers. A method for coregistering TCP based on the offsets of TCP is given to reduce the coregistration errors at TCP. An improved phase unwrapping method based on the minimum cost flow (MCF) algorithm and local Delaunay triangulation is also proposed for sparse TCP data. The proposed algorithms are validated using a test site in Hong Kong. The test results show that the algorithms work satisfactorily for various ground features.     

Monitoring of urban subsidence with SAR interferometric point target analysis: A case study in Suzhou,China

Ground subsidence, mainly caused by over exploitation of groundwater and other underground resources, such as oil, gas and coal, occurs in many cities in China. The annual direct loss associated with subsidence across the country is estimated to exceed 100 million US dollar. Interferometric SAR (InSAR) is a powerful tool to map ground deformation at an unprecedented level of spatial detail. It has been widely used to investigate the deformation resulting from earthquakes, volcanoes and subsidence. Repeat-pass InSAR, however, may fail due to impacts of spatial decorrelation, temporal decorrelation and heterogeneous refractivity of atmosphere. In urban areas, a large amount of natural stable radar reflectors exists, such as buildings and engineering structures, at which radar signals can remain coherent during a long time interval. Interferometric point target analysis (IPTA) technique, also known as persistent scatterers (PS) InSAR is based on these reflectors. It overcomes the shortfalls in conventional InSAR. This paper presents a procedure for urban subsidence monitoring with IPTA. Calculation of linear deformation rate and height residual, and the non-linear deformation estimate, respectively, are discussed in detail. Especially, the former is highlighted by a novel and easily implemented 2-dimensional spatial search algorithm. Practically useful solutions that can significantly improve the robustness of IPTA, are recommended. Finally, the proposed procedure is applied to mapping the ground subsidence in Suzhou city, Jiangsu province, China. Thirty-four ERS-1/2 SAR scenes are analyzed, and the deformation information over 38,881 point targets between 1992 and 2000 are generated. The IPTA-derived deformation estimates correspond well with leveling measurements, demonstrating the potential of the proposed subsidence monitoring procedure based on IPTA technique. Two shortcomings of the IPTA-based procedure, e.g., the requirement of large number of SAR images and assumed linear plus non-linear deformation model, are discussed as the topics of further research.     

合成孔径雷达影像地形校正半经验模型

结合SAR成像特点和数学理论知识,给出左视、右视两种侧视成像情况下影响地形起伏区域SAR后向散射的本地入射角理论计算模型,基于微波散射物理模型AIEM,模拟不同雷达入射角下地形坡度、坡向对SAR数据后向散射的影响,结果表明雷达入射角相对较小的SAR数据受地形起伏影响较小,是地形起伏地区SAR应用的最佳数据源。并提出一种SAR影像后向散射系数的地形校正半经验模型。地形校正过的SAR影像分类总体精度较未校正SAR影像提高12%。     

一种改进的阈值法提取SAR图像海面油污

对阈值的选取作了相关研究,提出了一种改进的阈值法提取SAR图像海面油膜。试验表明,改进方法在提取海面油膜的应用中具有一定的可行性。     

局部统计活动轮廓模型的SAR图像海岸线检测

首次将局部统计活动轮廓模型引入SAR图像海岸线检测问题中,提出了一种基于局部统计活动轮廓模型的SAR 图像海岸线检测方法。首先利用C-V模型进行粗分割,消除局部统计活动轮廓模型对初始轮廓线设置要求严格的限制,然后提出了一种基于G⁰分布的局部统计活动轮廓模型,进行精细分割。该模型采用G⁰分布对轮廓线上每一点的邻域进行统计建模,增强了模型数据拟合能力,提高了海岸线检测精度,加入水平集函数惩罚项,消除了重新初始化过程。实测SAR图像实验表明,本文方法可用于精确海岸线检测。     

使用多指数模型的 SAR 海冰图像偏差场校正

提出了一种使用多指数模型的SAR 海冰图像入射角偏差场校正的新算法, 该算法先对SAR 图像进行方 位向取平均, 然后用多指数模型对一维校正场建模, 应用熵值最小化方法求取最优的一维校正场, 再用推出的二维 校正场对原始图像进行校正。实验结果表明, 该算法对于SAR 海冰图像的入射角偏差场校正是有效的。与Karvonen 的算法相比, 该算法有更好的校正效果, 且不需要提供像素的入射角信息。