A Target Detection Method for Hyperspectral Imagery Based on Two-Time Detection

To solve the low detection efficiency problem of Constrained Energy Minimization (CEM) method used for hyperspectral remote sensing imagery, this paper firstly presents two improved detection methods: principal component CEM (PCCEM) and matrix taper CEM (MTCEM). Then, based on these two methods, a more optimized Two-Time detection (TTD) method is proposed. Primarily, the targets of interest in the hyperspectral image are detected by using the PCCEM and MTCEM method. Then the autocorrelation matrix of non-target pixels is estimated according to the target detection results. Finally, based on this autocorrelation matrix, a new weight vector is constructed for the second detection. Under the effect of this new weight vector, the output energy of the target can be kept at unity and the output energy of the background is suppressed at the same time. Then, the improvement of target detection result can be realized. Experimental results on a real world hyperspectral data show the efficiency of the proposed TTD method to improve the detection performance.     

A Novel Approach of Despeckling SAR Images Using Nonlocal Means Filtering

Synthetic aperture radar (SAR) is a day and night, all weather satellite imaging technology. Inherent property of SAR image is speckle noise which produces granular patterns in the image. Speckle noise occurs due to the interference of backscattered echo from earth’s rough surface. There are various speckle reduction techniques in spatial domain and transform domain. Non local means filtering (NLMF) is the technique used for denoising which uses Gaussian weights. In NLMF algorithm, the filtering is performed by taking the weighted mean of all the pixels in a selected search area. The weight given to the pixel is based on the similarity measure calculated as the weighted Euclidean distance over the two windows. Non local means filtering smoothes out homogeneous areas but edges are not preserved. So a discontinuity adaptive weight is used in order to preserve heterogeneous areas like edges. This technique is called as discontinuity adaptive non local means filtering and is well-adapted and robust in the case of Additive White Gaussian Noise (AWGN) model. But speckle is a multiplicative random noise and hence Euclidean distance is not a good choice. This paper presents evaluation results of using different distance measures for improving the accuracy of the Non local means filtering technique. The results are verified using real and synthetic images and from the results it can be concluded that the usage of Manhattan distance improves the accuracy of NLMF technique. Non local approach is used as a preprocessing or post processing technique for many denoising algorithms. So improving NLMF technique would help improving many of the existing denoising techniques.     

A Simplified Semi-Automatic Technique for Highway Extraction from High-Resolution Airborne LiDAR Data and Orthophotos

Information on highways is an essential input for various geospatial applications, including car navigation, forensic analysis on highway geometries, and intelligent transportation systems. Semi-automatic and automatic extractions of highways are critical for the regular updating of municipal databases and for highway maintenance. This study presents a semi-automatic data processing approach for extracting highways from high-resolution airborne LiDAR height information and aerial orthophotos. The method was developed based on two data sets. Experimental results for the first testing site showed that the accuracy of the proposed method for highway extraction was 74.50 % for completeness and 73.13 % for correctness. Meanwhile, the completeness and correctness for the second testing site were 71.20 and 70.72 %, respectively. The proposed method was compared with an object-based approach on a different data set. The accuracy for highway extraction of the object-based approach was 64.29 % for completeness and 63.11 % for correctness, whereas that of the proposed method was 67.14 % for completeness and 65.08 % for correctness. This research aims to promote semi-automatic highway extraction from LiDAR data and orthophotos by proposing a new approach and a multistep post-processing technique. The proposed method provides an accurate final output that is valuable for a wide range of geospatial applications.     

Proximal Remote Sensing of Herbicide and Drought Stress in Field Grown Colocasia and Sweet Potato Plants by Sunlight-Induced Chlorophyll Fluorescence Imaging

Chlorophyll fluorescence is an indicator of plant photosynthetic activity and has been used to monitor the health status of vegetation. Several studies have exploited the application of red/far-red chlorophyll fluorescence ratio in detecting the impact of various types of stresses in plants. Recently, sunlight-induced chlorophyll fluorescence imaging has been used to detect and discriminate different stages of mosaic virus infection in potted cassava plants with a multi-spectral imaging system (MSIS). In this study, the MSIS is used to investigate the impact of drought and herbicide stress in field grown crop plants. Towards this control and treatment groups of colocasia and sweet potato plants were grown in laterite soil beds and the reflectance images of these crop plants were recorded up to 14-days of treatment at the Fraunhofer lines of O₂ B at 687 nm and O₂ A at 759.5 nm and the off-lines at 684 and 757.5 nm. The recorded images were analyzed using the Fraunhofer Line Discrimination technique to extract the sunlight-induced chlorophyll fluorescence component from the reflectance images of the plant leaves. As compared to the control group, the chlorophyll fluorescence image ratio (F ₆₈₇/F ₇₆₀) in the treatment groups of both the plant varieties shows an increasing trend with increase in the extent of stress. Further, the F ₆₈₇/F ₇₆₀ ratio was found to correlate with the net photosynthetic rate (Pn) and stomatal conductance (g_s) of leaves. The correlation coefficient (R ²) for the relationship of F ₆₈₇/F ₇₆₀ ratio with Pn were found to be 0.78, 0.79 and 0.78, respectively for the control, herbicide treated and drought treated colocasia plants, while these were 0.77, 0.86 and 0.88, respectively for sweet potato plants. The results presented show the potential of proximal remote sensing and the application F ₆₈₇/F ₇₆₀ fluorescence image ratio for effective monitoring of stress-induced changes in field grown plants.     

Objects Detection in Hyperspectral Images Using Spectral Derivative

In recent years hyperspectral imaging has proved its significance in the detection and mapping of various objects of interest in a scene. Various methods for object detection in hyperspectral images have been developed with their advantages and limitations. In the present study, a methodology comprising spectral derivative (first order) and spectral information divergence has been investigated for detection of objects in hyperspectral images. The efficacy of the detection scheme has been examined over two different hyperspectral data sets of Hyperion images. Tea plants (Camellia sinensis) and Sal trees (Shorea robusta) (pure pixels) have been detected as the objects of interest in the hyperspectral images independently with reduced false pixels. The proposed methodology may in future be applied for classification of mixed pixels.     

Cyclone Frame Prediction by Gaussian Mixture Modeling of the Three Penultimate Time-Lapse Frames

A fast cyclone frame prediction is proposed in this paper that fits a Gaussian Mixture model on the spatio-temporal data extracted from the three penultimate time-lapse frames, prior to fuzzy regression. Unlike the previous work in Verma and Pal (In: Applied Imagery Pattern Recognition Workshop (AIPR), pp. 1–8, 2010) that models the entire history on a per pixel basis, a single Gaussian mixture is used for fitting the spatio-temporal data within the time-span of the last three frames, making the process faster and more accurate. The increase in accuracy is attributed to the fact that cyclones evolve over time and thus the recent frames give a more meaningful insight into the predictions for the next frame. The number of components in the Gaussian mixture is determined from the occurrence of equally likely modes that correspond to high entropy peaks. Our results on satellite videos of recent cyclones that hit the Indian seas show a high accuracy of frame prediction.     

对新疆土地生态环境保护的思考

新疆幅员辽阔,总面积为1.6×106km2,占我国国土总面积的1/6。但新疆远离海洋,气候干燥,沙漠面积7.3×105km2,占全国沙漠总面积的2/3。生态环境脆弱,直接威胁人们的生存环境。本文叙述了新疆土地荒漠化的现状及成因和危害;开荒造田的历程;开荒造田中的经验和教训,指出了新疆土地生态环境保护中存在的主要矛盾和问题,并提出了思考和建议。     

GPS PPK远距离在航潮位测量及其在航道的实现

在分析传统潮位测量方法、潮位模型及GPS RTK潮位测量缺陷的基础上,给出GPS PPK远距离在航潮位测量的方法。系统地研究GPS PPK在航潮位测量、数据处理的基本理论和流程,并对潮位测量和数据处理中的GPS PPK高程质量控制、船舶姿态改正、动态吃水改正、潮位数据提取、垂直基准转换5个关键问题进行深入研究,最终确定测量船测量期间的在航潮位。试验结果表明,GPS PPK在航潮位测量方法具有实施简便、精度较高及稳定、可靠、作用距离长等优势,可广泛应用于航道在航潮位测量中。     

SVLBI用于大地测量的卫星轨道及其跟踪网设计

SVLBI （space very long baseline interferometry） has some important potential applications in geodesy and geodynamics, for which one of the most difficult tasks is to precisely determine the orbit of an SVLBI satellite. This work studies several technologies that will possibly be able to determine the orbit of a space VLBI satellite. Then, according to the types and charac- teristics of the satellite and the requirements for geodetic study and the geometry of the GNSS （GPS, GALILEO） satellite to track the space VLBI satellite, the six Keplerian elements of the SVLBI satellite （TEST-SVLBI） are determined. A program is designed to analyze the coverage area of space of different altitudes by the stations of the network, with which the tracking network of TEST-SVLBI is designed. The efficiency of tracking TEST-SVLBI by the network is studied, and the results are presented.     

南极国际GPS跟踪站的海潮位移改正

This paper describes the ocean loading tides corrections of GPS stations in Antarctica, such as the Great Wall station and Zhongshan station. Based on the theory of ocean loading tides, the displacement corrections of ocean loading tides on GPS stations in Antarctica are calculated by using the CRS4.0 ocean loading tides model. These corrections are also applied to GPS data processing. The GPS data are analyzed by the GAMIT software with and without these corrections. We compared and analyzed the GPS baseline components to get the differences. The results show that the ocean tidal displacement corrections have obvious effects upon GPS baseline components. Therefore, we should not ignore the ocean loading tides corrections of GPS stations in Antarctica to obtain precise and reliable results.