Classification of dual- and single polarized SAR images by incorporating visual features

Fully and partially polarimetric SAR data in combination with textural features have been used extensively for terrain classification. However, there is another type of visual feature that has so far been neglected from polarimetric SAR classification: Color. It is a common practice to visualize polarimetric SAR data by color coding methods and thus it is possible to extract powerful color features from such pseudo color images so as to gather additional crucial information for an improved terrain classification. In this paper, we investigate the application of several individual visual features over different pseudo color generated images along with the traditional SAR and texture features for a novel supervised classification application of dual- and single-polarized SAR data. We then draw the focus on evaluating the effects of the applied pseudo coloring methods on the classification performance. An extensive set of experiments show that individual visual features or their combination with traditional SAR features introduce a new level of discrimination and provide noteworthy improvement of classification accuracies within the application of land use and land cover classification for dual- and single-pol image data.     

大面阵数字航空相机DMZ影像预处理研究

对国产新型内拼式大面阵数字航测相机DMZ原型系统获取的数字影像进行几何预处理的方法进行了研究;在分析DMZ全色成像光路特点的基础上,提出了多相机联合的影像几何校正与缝合方法,生成等效虚拟立体影像。利用等效虚拟立体影像进行了3种布控方案的数字空三平差和精度分析,验证了该方法的正确性和可靠性,实现了对DMZ影像预处理的探索性研究。     

A comparative assessment between object and pixel-based classification approaches for land use/land cover mapping using SPOT 5 imagery

Abstract

Land use/land cover (LULC) classification with high accuracy is necessary, especially in eco-environment research, urban planning, vegetation condition study and soil management. Over the last decade a number of classification algorithms have been developed for the analysis of remotely sensed data. The most notable algorithms are the object-oriented K-Nearest Neighbour (K-NN), Support Vector Machines (SVMs) and the Decision Trees (DTs) amongst many others. In this study, LULC types of Selangor area were analyzed on the basis of the classification results acquired using the pixel-based and object-based image analysis approaches. SPOT 5 satellite images with four spectral bands from 2003 and 2010 were used to carry out the image classification and ground truth data were collected from Google Earth and field trips. In pixel-based image analysis, a supervised classification was performed using the DT classifier. On the other hand, object-oriented (K-NN) image analysis was evaluated using standard nearest neighbour as classifier. Subsequently SVM object-based classification was performed. Five LULC categories were extracted and the results were compared between them. The overall classification accuracies for 2003 and 2010 showed that the object-oriented (K-NN) (90.5% and 91%) performed better results than the pixel-based DT (68.6% and 68.4%) and object-based SVM (80.6% and 78.15%). In general, the object-oriented (K-NN) performed better than both DTs and SVMs. The obtained LULC classification maps can be used to improve various applications such as change detection, urban design, environmental management and zooning.     

Segmenting mangrove ecosystems drone images using SLIC superpixels

Abstract

Mangrove ecosystems play a very important ecological role on land–ocean interfaces in tropical regions. These ecosystems comprise of various tree species and aquatic animals, protecting the environment and providing a habitat that supports many living organisms including humans. The identification of image regions in mangrove ecosystems plays a significant role in ecosystem monitoring and conservation. Recent studies have suggested oversegmentation of colour images using superpixels as a solution to the segmentation of image regions. This study used the SLIC superpixel algorithm and k-means clustering to segment images taken from a camera mounted on a drone from a mangrove ecosystem in Fiji. The SLIC superpixel algorithm performed well to demarcate image regions with similar colour and texture information into patches and to use k-means for the segmentation of the whole image. These results lend support to the use of superpixel algorithms for the segmentation of mangrove ecosystems. Understanding how superpixels can be used for the segmentation of drone images will assist conservation efforts in mangrove ecosystems.     

1米太阳望远镜光谱仪像旋转及消旋控制

光谱仪是1 m太阳望远镜的主要终端设备之一,该望远镜采用地平式的机架结构和修正的格里高利光学系统。在望远镜跟踪太阳时,由于地平式望远镜的自身运动特点和光学系统中平面反射镜的存在,其光谱仪狭缝所在平面上的太阳像随时间绕主光轴旋转,因此光谱仪必须进行消旋才能正常工作。首先深入研究了光谱仪狭缝平面上像的旋转变化,分析其旋转范围、速度和加速度随时角变化的特性,然后根据光谱仪消旋精度并结合像的旋转特性提出伺服系统位置检测和驱动电机的主要性能指标,最后给出光谱仪消旋伺服控制方案。     

Finite strain analysis of nonuniform deformation inside shear bands in sands

A methodology has been developed to extend the incremental (Eulerian) Digital Image Correlation (DIC) technique to enable a Lagrangian‐based large‐strain analysis framework to examine the nature of strain and kinematic nonuniformity within shear bands in sands. Plane strain compression tests are performed on dense sands in an apparatus that promotes unconstrained persistent shear band formation. DIC is used to capture incremental, grain‐scale displacements in and around shear bands. The performance of the developed accumulation algorithm is validated by comparing accumulated displacements with two sources of reference measurements. A comparison between large and infinitesimal rotation is performed, demonstrating the nature of straining within shear bands in sands and the necessity of using a finite strain formulation to characterize ensuing behavior. Volumetric strain variation along the shear band is analyzed throughout macroscopic postpeak deformation. During softening, volumetric activity within the shear band is purely dilative. During the global critical state, the shear band material is seen on the average to deform at zero volumetric strain; however, locally, the sand is seen to exhibit significant nonzero volumetric strain, putting into question the current definition of critical state. At the softening‐critical state transition, a spatially periodic pattern of alternating contraction and dilation along the shear band is evidenced, and a preliminary evaluation indicates that the periodicity appears to be a physical phenomenon dictated only in part by median grain size. Copyright © 2011 John Wiley & Sons, Ltd.     

ENVI遥感图像监督分类方法比较

鉴于遥感监督分类方法的普遍应用,本文介绍了五种常用的监督分类方法:平行六面体法、最小距离法、马氏距离法、最大似然法和人工神经网络分类法。就同一地区TM影像应用这五种方法进行了土地利用分类,对比分析了这五种方法的分类精度,发现人工神经网络对土地覆盖与利用的分类精度高于最大似然法,最大似然法分类精度优于平行六面体法、最小距离法和马氏距离法。所得结论对有关遥感图像分类工作具有指导和借鉴意义。     

A Comparison of Several Image Locating Algorithms in Astronomical Instruments

In astronomical observations at optical wavelengths, a fast image tracking system can be adopted to reduce the effects of the atmospheric seeing and telescopic tracking error, and therefore improve the observing efficiency. Aiming at the need of astronomical observations, totally 5 kinds of algorithms in two categories were selected to make a comparative study on their accuracies and stabilities under different noise conditions by both numerical experiment and laboratory test. The results indicate that the normalized cross-correlation method and barycenter method have not only a higher accuracy but also a better reliability against interferences, they will be applied to the high-resolution spectrograph of the Xinglong 2.16 m telescope and the scienti?c instruments of the SONG (Stellar Observations Network Group) project, respectively.     

SAR与光学影像融合在宁陕地区明长城探测中的应用研究

宁夏和陕西地区的明长城在遭到自然与人为双重破坏后日渐退化,有的区段已消失于地表。本文采用了SAR与光学影像像素 级融合方法——HIS变换融合和PC主成份变换融合,通过比较2种方法的融合效果,最终选定PC主分量变换融合的结果作为自动提取 该区明长城信息的基础。通过“骨架”算法实现了对该区明长城空间位置的自动提取,最终获得了较为清晰的明长城信息。该区明 长城准确而完整的空间位置,可为进一步研究该区明长城沿线环境变化及古环境演变提供精准的研究范围和研究基础。