Multi‐resolution dune morphology using Shuttle Radar Topography Mission (SRTM) and dune mobility from fuzzy inference systems using SRTM and altimetric data

The complex morphology of large sand dunes of the world's great deserts have significant importance on conservation and climate change and hence are of interest to a wide variety of scientific and environmental applications including studies on aeolian processes, paleoclimate, civilian infrastructure management, and design of blown‐sand control systems. Scientific studies on dune formation and dynamics have been limited to desert margins due to inaccessibility of the desert interior by conventional surveying and mapping techniques. Thus, dune morphology in the deep desert interiors is not well studied and much about the driving forces controlling dune activity and dynamics are still poorly understood.

We demonstrate the utility of space‐based observations to characterize dune morphology. Specifically, we used the Shuttle Radar Topography Mission (SRTM) C‐band data to investigate and compare morphologic attributes of dune fields of the Taklimakan and the Namib Deserts. Cross‐sectional amplitude roughness estimates have similar magnitude but stoss slopes are shallower in the Taklimakan Desert than in the Namib Desert. The high Height‐Width (H:W) ratio of 0.09 for the linear dunes in the Taklimakan Desert is indicative of its equilibrium with aeolian shear stress whereas the Namib Desert dunes are unstable. Multi‐resolution planimetric properties from SRTM Digital Elevation Model (DEM) using B‐spline wavelet decomposition reveal linear dunes in the Taklimakan Desert are superimposed on a dome‐like substrate whereas the linear dune in the Namib Desert are constructed on a knoll‐like submorphology. These long‐wavelength features, taken as paleotopography, may be a major controlling factor on wind patterns and dune sinuosity.

We demonstrate the utility of ANFIS to assess seasonal dune changes in the Namib Desert using ICESat observations and SRTM. ANFIS is a data‐driven prediction scheme. Predicted topography along ICESat tracks have low rms of 3.5m, a 30% increase over SRTM accuracy. Seasonal track comparison from August 2003 to January 2005 shows that most changes to dune topography occur at crestal deformation of isolated dunes. The results show seasonal waning and waxing of dune crests.     

Monitoring migration rates of an active subarctic dune field using optical imagery

We developed a novel method to quantify subtle rates of landscape evolution using two satellite imaging systems with different viewing angles and spectral sensitivities. We selected the slowly migrating, high-latitude, subarctic Great Kobuk Sand Dunes (GKSD), Kobuk Valley National Park, Alaska (USA), for our study. The COSI-Corr technique was used for precise orthorectification, co-registration, and subpixel correlation of satellite data. ASTER Visible Near Infrared (VNIR) and SPOT Panchromatic images with a 5-year temporal separation were correlated to measure the horizontal velocity of the GKSD. To reduce correlation noise, ASTER VNIR bands were linearly mixed to match the SPOT Panchromatic band, and raw correlation measurements were projected onto a local robust migration direction to estimate unbiased velocity magnitudes. The results show that the most likely migration rate for the GKSD ranges from 0.5 to 1.5 m/year, with peak velocities up to 3.8 m/year, and uncertainty of approximately 0.16 m/year. The unprecedented ability to measure slow migration rates, including those that may occur over a relatively short time interval, illustrates the value of this method to reliably detect and monitor subtle ground movements including dune migration, glacier flow, mass movements, and other small-scale processes.     

New range domain carrier‐smoothed code filtering with dual‐frequency BDS data

In global navigation satellite system (GNSS) applications, the carrier‐smoothed code is a widely used technique to combine code pseudo‐range and carrier phase measurements. Unlike conventional methods, a method using dual‐frequency GNSS data to improve smoothing accuracy by eliminating ionosphere delay is described in this paper. In the recursive least‐squares theory for colored measurement errors framework, a global one‐step carrier‐smoothed code filter in range domain is proposed to overcome the limitations of traditional approaches. The correlations of the time‐differenced carrier phase measurements are considered. This approach avoids overly optimistically evaluating the estimate and improves the transient accuracy of the estimate. Compared with stepwise strategy, the one‐step method is superior and globally optimal. Experiments are conducted using real BDS data, and the performance of the proposed method is demonstrated.     

Surface currents from hourly variations of suspended particulate matter from Geostationary Ocean Color Imager data

Surface currents in Korean coastal regions were obtained using the maximum cross-correlation method applied to hourly suspended particulate matter images from the Geostationary Ocean Color Imager. Preliminary current vectors were filtered out by applying a series of quality-control procedures. The current vectors resulting from the tests were compared with the currents from a numerical model with tide and wind field. It was found that the estimated currents were more similarly to the currents caused by both tide and wind. A high degree of discrepancy was detected in regions of strong tidal currents, where the fundamental assumption of horizontal movement was limited due to the dominant vertical tidal mixing in the shallow region. The hourly rotations of the current vectors within a day were clarified by a comparison of the time-varying orientation angles of tidal ellipses. This study emphasized how to understand the short-term surface flows from hourly high-resolution geostationary satellite images.     

Computational simulations of blown sand fluxes over the surfaces of complex microtopography

Studies of sand saltation are currently concentrating on wind tunnel experiments, theoretical analyses and numerical simulations under ideal as well as controllable conditions. These theoretical analyses and numerical simulations cannot accurately predict sand movements in field environments. In this paper, we simulate wind field patterns for two different surfaces of complex microtopography using the computational fluid dynamic model, FLUENT. To demonstrate that the model can successfully reproduce wind patterns in complex microtopography, we first simulate a well-studied mesquite bush and coppice dune field from the Chihuahuan Desert. This is then followed by an analysis of the wind field pattern around a large barchan dune that is complex in shape. For this case, the wind pattern was linked with a sediment transport equation to estimate sediment flux and transport. Finally, as shown by the simulation results, the sand flux, from the right horn to the left horn of the dune, first increased then decreased after reaching its maximum at the intersection of the brink and the longitudinal centreline of the dune.     

基于稀疏表示方法的短期风电功率预测

针对短期风电功率预测,提出一种基于稀疏表示特征提取的建模方法.为了构建预测模型,将历史风电功率数据构成具有时延的输入-输出数据对,将时延输入数据向量作为初始字典,由K-均值奇异值分解(K-SVD)算法将其进行稀疏分解与变换至稀疏域以得到学习后的字典,由正交匹配追踪(OMP)算法获取相应的稀疏编码向量,再将该向量作为极限...     

Estimating vertical error of SRTM and map-based DEMs using ICESat altimetry data in the eastern Tibetan Plateau

The Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud and land Elevation Satellite (ICESat) provides elevation data with very high accuracy which can be used as ground data to evaluate the vertical accuracy of an existing Digital Elevation Model (DEM). In this article, we examine the differences between ICESat elevation data (from the 1064 nm channel) and Shuttle Radar Topography Mission (SRTM) DEM of 3 arcsec resolution (90 m) and map-based DEMs in the Qinghai-Tibet (or Tibetan) Plateau, China. Both DEMs are linearly correlated with ICESat elevation for different land covers and the SRTM DEM shows a stronger correlation with ICESat elevations than the map-based DEM on all land-cover types. The statistics indicate that land cover, surface slope and roughness influence the vertical accuracy of the two DEMs. The standard deviation of the elevation differences between the two DEMs and the ICESat elevation gradually increases as the vegetation stands, terrain slope or surface roughness increase. The SRTM DEM consistently shows a smaller vertical error than the map-based DEM. The overall means and standard deviations of the elevation differences between ICESat and SRTM DEM and between ICESat and the map-based DEM over the study area are 1.03 ± 15.20 and 4.58 ± 26.01 m, respectively. Our results suggest that the SRTM DEM has a higher accuracy than the map-based DEM of the region. It is found that ICESat elevation increases when snow is falling and decreases during snow or glacier melting, while the SRTM DEM gives a relative stable elevation of the snow/land interface or a glacier elevation where the C-band can penetrate through or reach it. Therefore, this makes the SRTM DEM a promising dataset (baseline) for monitoring glacier volume change since 2000.     

Satellite‐based assessment of the dynamics of new lakes in southern Egypt

Lakes in arid landscapes are indicators of environmental change and important sources of water for human use. In regions without in situ hydrologic measurements, remote sensing may provide the only means to monitor long‐term changes in water storage. We used a synergistic combination of multiple satellite remote‐sensing methods to provide the first comprehensive assessment of the dynamics of a newly formed chain of large lakes in the hyper‐arid Toshka Depression of southern Egypt. A total of 145 MODIS and AVHRR satellite images were used to monitor changes in lake surface area, which increased to a maximum of 1740 km² before declining to 900 km². Two methods were tested for satellite‐based measurement of lake levels and volumes, one based on analysis of a digital elevation model and one using data from the ICESat GLAS laser altimeter. This study shows the power of satellite remote sensing for long‐term monitoring of regional‐scale hydrologic transformations.     

Objectively determined 10-day African rainfall estimates created for famine early warning systems

A method of estimation of accumulated precipitation which incorporates numerical model analyses, satellite and surface data has been developed for the African continent. An estimate for accumulated convective cloud precipitation is computed from cold cloud top temperature duration with a bias removal made from the use of rain-gauge data. Orographic precipitation from relatively warm cloud sources is estimated using a combination of surface and satellite data, orography, and numerical model analyses of relative humidity and wind. The results of a comparison of these precipitation estimates with independent rainfall data show this method produces skilful analyses of estimated accumulated precipitation for the Sahel region of Africa.     

Multi-objective optimization for parameter selection and characterization of optical flow methods

Optical flow methods are among the most accurate techniques for estimating displacement and velocity fields in a number of applications that range from neuroscience to robotics. The performance of any optical flow method will naturally depend on the configuration of its parameters, and for different applications there are different trade-offs between the corresponding evaluation criteria (e.g. the accuracy and the processing speed of the estimated optical flow). Beyond the standard practice of manual selection of parameters for a specific application, in this article we propose a framework for automatic parameter setting that allows searching for an approximated Pareto-optimal set of configurations in the whole parameter space. This final Pareto-front characterizes each specific method, enabling proper method comparison and proper parameter selection. Using the proposed methodology and two open benchmark databases, we study two recent variational optical flow methods. The obtained results clearly indicate that the method to be selected is application dependent, that in general method comparison and parameter selection should not be done using a single evaluation measure, and that the proposed approach allows to successfully perform the desired method comparison and parameter selection.     

HJ星数据在关中冬小麦种植面积遥感监测中的应用 

应用冬小麦抽穗期的环境小卫星影像对关中地区依据行政区划划分,采用多种遥感监测方法进行冬小麦种植面积提取,提取精度达95.64%。结果表明:抽穗期是关中地区提取冬小麦种植面积的最佳时相,同时也表明环境小卫星可以用来监测大范围的冬小麦种植面积,并得到很高的精度。在未来的研究中,对于地形差异较大的地区,可依据地形和冬小麦的种植结构对研究区进行划分,针对每个子研究区采用不同的遥感监测方法以提高提取精度。     

A simple equation for determining sea surface emissivity in the 3–15 µm region

The high level of accuracy demanded for the sea surface temperature retrieval from infrared data requires an accurate determination of directional sea surface emissivity (SSE). Previous models have permitted calculating SSEs using a physical characterization of sea surface roughness and emission. However, these result in complex equations, and make an operational application difficult. This paper presents a simple SSE algorithm based on a parametrization of one of these models, which was selected as a reference since it reproduces SSE experimental data to a reasonable level of accuracy. The parametrization provides the SSE variation with observation angle and wind speed from a given nadir SSE value, using only one channel-dependent coefficient. This coefficient and the nadir SSE value are given for the IR bands of several current satellite sensors: ENVISAT‐AATSR, EOSTerra/Aqua‐MODIS, NOAA17‐AVHRR and MSG‐SEVIRI. The average standard error of the SSE estimate using the proposed equation is±0.0009.     

Combining differential SAR interferometry and the probability integral method for three-dimensional deformation monitoring of mining areas

With the exploitation of coal resources, ground surface subsidence continues to occur in mining areas, destroying the ecological environment and significantly affecting the daily productivity and life of humans. The differential synthetic aperture radar interferometry (D-InSAR) technique is widely used to monitor ground surface deformation because of its unique advantages such as high accuracy and wide coverage. However, conventional D-InSAR technology provides only one-dimensional (1D) displacement monitoring along the radar line of sight (LOS). This article proposes a method based on an analysis of the mining subsidence law for true three-dimensional (3D) displacement monitoring by combining D-InSAR and a subsidence prediction model based on the probability integral method. In this approach, 1D displacement, obtained using D-InSAR, is then combined with the prediction model to obtain the 3D displacement of ground surface target points. Here, 3D displacement curves were obtained for the Fengfeng mining area (China) using RadarSat-2 images obtained on 9 January and 2 February 2011. True ground surface displacement was measured simultaneously by levelling when the 152under31 s working face was being exploited in Jiulong mine. Vertical displacement and inclined deformation calculated using the proposed method were compared with levelling survey data and the results showed average differences of 3.2 mm and 0.1 mm m^?1, respectively; the calculated maximum displacement in the east–west and south–north directions were 106 and 73 mm, respectively. The spatial distribution of the displacements was in accordance with the mining subsidence law. Thus, the new method can retrieve highly accurate 3D displacements caused by mining subsidence.     

Evaluation of AMSR-E soil moisture results using the in-situ data over the Little River Experimental Watershed, Georgia

An operational global soil moisture data product is currently generated from the observations of the Advanced Microwave Scanning Radiometer (AMSR-E) aboard NASA's Aqua satellite using the retrieval procedure described in Njoku and Chan [Njoku, E.G. and Chan, S.K., 2006. Vegetation and surface roughness effects on AMSR-E land observations, remote sensing environment, 100(2), 190-199]. We have generated another soil moisture dataset from the same AMSR-E observed brightness temperature data using the Land Surface Microwave Emission Model (LSMEM) adopting a different estimation method. This paper focuses on a comparison study of soil moisture estimates from the above two methods. The soil moisture data from current AMSR-E product and LSMEM are compared with the in-situ measured soil moisture datasets over the Little River Experimental Watershed (LREW), Georgia, USA for the year 2003. The comparison study was carried out separately for the AMSR-E daytime and night time overpasses. The LSMEM method performed better than the current operational AMSR-E retrieval algorithm in this study. The differences between the AMSR-E and LSMEM results are mostly due to differences in various simplifications and assumptions made for variables in the radiative transfer equations and the soil and vegetation based physical models and the accuracy of the input surface temperature datasets for the LSMEM forward model approach. This study confirms that remote sensing data have the potential to provide useful hydrologic information, but the accuracy of the geophysical parameters could vary depending on the estimation methods. It cannot be concluded from this study whether the soil moisture estimation by the LSMEM approach will perform better in other geographic, climatic or topographic conditions. Nevertheless, this study sheds light on the effects of different approaches for the estimation of geophysical parameters, which may be useful for current and future satellite missions.     

基于迭代UKF的主动段弹道跟踪算法研究

卫星在角度测量信息下对弹道导弹主动段的跟踪面临可观测性弱、初始误差大等问题，寻找一种快速稳健的跟踪算法尤为重要。引入一种稳健而有效的迭代UKF滤波算法（IUKF），它通过对UKF算法进行修正，改善了对状态滤波值和协方差的估计。通过Monte Carlo仿真与其他算法进行比较，表明新算法收敛速度更快、收敛精度更高，是解决主动段跟踪问题的一种更为有效的算法。     

基于特征降维的卫星通信辐射源个体识别方法

针对卫星通信系统安全检测问题,提出了一种基于重构降维分析的卫星辐射源个体识别方法.该方法通过提取所有卫星终端设备训练数据的高维特征向量,然后以监督方式寻找使得降维特征向量离同类最近、离异类边缘点最远的子空间,并利用降维特征向量训练分类器,最后利用分类器判决未知信号的类别.提出的卫星辐射源个体识别方法所提取的辐射源特征基于高维特征向量的线性组合,保留了不同发射机的差异信息,具备很强的分类辨别能力.实际采集的数据测试结果表明,该方法可有效识别不同辐射源个体.     

Velocity Estimation for Robot Manipulators Using Neural Network

In robot manipulators, optical incremental encoders are widely used as the transducers to monitor joint position and velocity information. With incremental encoder, positional information is determined as discrete data relative to a reference (home) position. However, velocity information can only be deduced by processing the position data. In this paper, a method of using a neural network to estimate the velocity information of robotic joint from discrete position versus time data is proposed and evaluated. The architecture of the neural net and the training methodology are presented and discussed.This approach is then applied to estimate the joint velocity of a SCARA robot while performing an electronic component assembly task. Based on computer simulations, comparison of the accuracy of the neural network estimator with two other well established velocity estimation algorithms are made. The neural net approach can maintain good performance even in the presence of measurement noises.     

Traffic monitoring with spaceborne SAR—Theory, simulations, and experiments

This paper reviews the theoretical background for upcoming dual-channel radar satellite missions to monitor traffic from space and exemplifies the potentials and limitations by real data. In general, objects that move during the illumination time of the radar will be imaged differently than stationary objects. If the assumptions incorporated in the focusing process of the synthetic aperture radar (SAR) principle are not met, a moving object will appear both displaced and blurred. To study the impact of these (and related) distortions in focused SAR images, the analytic relations between an arbitrarily moving point scatterer and its conjugate in the SAR image have been reviewed and adapted to dual-channel satellite specifications. Furthermore, a specific detection scheme is proposed that integrates complementary detection and velocity estimation algorithms with knowledge derived from external sources as, e.g., road databases. Results using real SAR data are presented to validate the theory.     

Giant landslide displacement analysis using a point cloud set conflict technique: a case in Xishancun landslide,Sichuan, China

Landslides, threatening millions of human lives, are geological phenomena on earth, occurred frequently. An increasing number of techniques are being used to monitor landslide deformation. Among these, Light Detection and Ranging (LiDAR) stands out for its high efficiency and accuracy in displacement detection, particularly for giant landslides. In this work, we collected two temporal datasets of terrain laser scanning and proposed a flowchart for giant landslide displacement analysis using the point cloud set conflict（PCSC） technique. First, the terrestrial points were obtained by performing registration and off-terrain point filtering. Second, the landslide displacement field was acquired using the proposed method based on its surface roughness. The displacement results from our established methodological system are comparable with the ones of Interferometric Synthetic Aperture Radar (InSAR)-derived deformations. The differences estimated from two systems are at the centimetre level. Cross-analysis on the trigger factor with landslide occurred mechanism could be achieved based on the results as well. Therefore, this work provides a novel system to analyse the displacement of a giant landslide in the future study.     

Evaluating capture-recapture models with two inspectors

Capture-recapture (CR) models have been proposed as an objective method for controlling software inspections. CR models were originally developed to estimate the size of animal populations. In software, they have been used to estimate the number of defects in an inspected artifact. This estimate can be another source of information for deciding whether the artifact requires a reinspection to ensure that a minimal inspection effectiveness level has been attained. Little evaluative research has been performed thus far on the utility of CR models for inspections with two inspectors. We report on an extensive Monte Carlo simulation that evaluated capture-recapture models suitable for two inspectors assuming a code inspections context. We evaluate the relative error of the CR estimates as well as the accuracy of the reinspection decision made using the CR model. Our results indicate that the most appropriate capture-recapture model for two inspectors is an estimator that allows for inspectors with different capabilities. This model always produces an estimate (i.e., does not fail), has a predictable behavior (i.e., works well when its assumptions are met), will have a relatively high decision accuracy, and will perform better than the default decision of no reinspections. Furthermore, we identify the conditions under which this estimator will perform best