Table of Content

20 November 2015, Volume 44 Issue 11

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Spatial Distribution and Ten Years Change of Global Built-up Areas Derived from GlobeLand30

CHEN Jun, CHEN Lijun, LI Ran, LIAO Anping, PENG Shu, LU Nan, ZHANG Yushuo

2015, 44(11):  1181-1188.  doi:10.11947/j.AGCS.2015.20140677

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As an important anthropogenic indicator and human ecological foot print,built-up areas and its change is an essential information for environmental change analysis, geo-conditional monitoring and sustainable development. In the past, built-up areas and its change studies were mainly focused on a city, regional or nation scale, and it has not been possible to conduct a global built-up areas and its change analysis yet. This paper presented the methodology and results of the first global analysis of built-up areas and its ten year's change(2000-2010) using GlobeLand30, China's 30 meter resolution global land cover data sets-. Built-up areas, change rate and increase proportion were the major statistical variables used for the statistical analysis. The result shows that the total area of the global built-up areas is 1.1875 million km², covering 0.88% of the total area of the global land surface; the area of global built-up areas increased 57400km² with the variation rate of 5.08% from 2000 to 2010;and China and United Sates are the top two countries having the largest increased built-up areas, i.e., accounting over 50% of that of the global total; 50.26% of the total increased built-up areas comes from the arable land. These results provide reliable spatio-temporal information to the study of human domination of Earth's ecosystems and global monitoring.

A Direct Approach to Determine the External Disturbing Gravity Field by Applying Green Integral with the Ground Boundary Value

TIAN Jialei, WU Xiaoping, LI Shanshan

2015, 44(11):  1189-1195.  doi:10.11947/j.AGCS.2015.20140516

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By using the ground as the boundary, Molodensky problem usually gets the solution in form of series. Higher order terms reflect the correction between a smooth surface and the ground boundary. Application difficulties arise from not only computational complexity and stability maintenance, but also data-intensiveness. Therefore, in this paper, starting from the application of external gravity disturbance, Green formula is used on digital terrain surface. In the case of ignoring the influence of horizontal component of the integral, the expression formula of external disturbance potential determined by boundary value consisted of ground gravity anomalies and height anomaly difference are obtained, whose kernel function is reciprocal of distance and Poisson core respectively. With this method, there is no need of continuation of ground data. And kernel function is concise, and suitable for the stochastic computation of external disturbing gravity field.

Calibration and Analysis of SGG Observations of GOCE Based on Prior Gravity Models

XU Xinyu, ZHAO Yongqi, WEI Hui, WU Tangting

2015, 44(11):  1196-1201.  doi:10.11947/j.AGCS.2015.20140414

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GOCE satellite carries a high-sensitivity gradiometer, whose observations are used for recovering high-precision and high-resolution earth gravity field. Based on EIGEN-5C, EGM2008, GGM03S and GOTIM3 global gravity field models, the calibration parameters of the diagonal components(V_xx, V_yy, V_zz) of GOCE gravitational gradient tensor(GGT) were obtained. We analyzed the stability of scale factors. The influences on the calibration parameters and the calibrated observations from different gravity field models, the same model with different maximum degree and order and whether estimating the drift parameters were discussed in detail.The results shows that the stability of scale factors are about 10^-4 and calibrated observations are mainly determined by the low-degree signal of gravity field models. The differences of calibrated observations between EGM2008 and EIGEN-5C up to degree and order 250 are less than 10^-4E, which is far less than the noise level of GOCE GGT. We also find that the effects of whether estimating the drift parameter on the calibrated observations could approach 0.4E when the calibration is carried out every day. At the same time, the PSD(power spectral density) of the observation difference before and after the calibration shows that the low-frequency part of observations V_xx, V_yy, V_zz are mainly calibrated from the low-medium degree part(<150) of the empirical gravity field models. Taking the measurement bandwidth of GOCE gradiometer into account, the calibrated observations could be used for recovering the middle-high frequency signal of gravity field.

The InSAR Coseismic Deformation Observation and Fault Parameter Inversion of the 2008 Dachaidan M_w6.3 Earthquake

LIU Yang, XU Caijun, WEN Yangmao, HE Ping

2015, 44(11):  1202-1209.  doi:10.11947/j.AGCS.2015.20140628

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On November 10, 2008, an M_w6.3 earthquake struck the Dachaidan region of Qinghai Province. The ascending and descending synthetic aperture radar(SAR) data from EnviSat satellite and the differential interferometric SAR(DInSAR) technology are used to extract the coseismic deformation field. The uniform dislocation model is used to determine the fault parameters, the grid iteration method is then used to find the optimal dip angle, and the non-uniform dislocation model is used to obtain the detailed slip distribution simultaneously. The results show that the earthquake uplifts the hanging wall up to~8.5cm and~10cm along the line of sight of the descending and ascending tracks, respectively. The optimal dip angle is 47.9°. The coseismic slip doesn't rupture to the earth surface, and mainly occurs at a depth range from 8.2km to 23.7km, with the maximum and average slip of 0.5m and 0.19m, respectively. The average rake angle is 104.9°. The inverted earthquake moment is 3.74×10¹⁸ N·m, and the moment magnitude M_w is 6.35.

GPS Partial Ambiguity Resolution Method for Zero-difference Precise Point Positioning

PAN Zongpeng, CHAI Hongzhou, LIU Jun, DONG Bingquan, LIU Ming, WANG Huarun

2015, 44(11):  1210-1218.  doi:10.11947/j.AGCS.2015.20150056

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With the development of ambiguity resolution for precise point positioning(PPP) in recent years, it can improve positioning accuracy of PPP with short time observations since ambiguities can be fixed to right integers. However, unacceptable errors would be introduced into coordinate parameters if ambiguities are fixed to wrong integers. It's necessary to investigate the reliability and success rate of ambiguity-fixed PPP. This paper investigates PPP ambiguity fixing method based on zero-differenced fractional-cycle biases(FCBs). A partial ambiguity resolution(PAR) strategy based on cascaded quality control is proposed. Data sets from Europe CORS are used to validate and demonstrate PAR strategy. Results have showed that PPP ambiguity fixing can improve positioning accuracy of hourly PPP solution. When the strategy of PAR is applied, the influence of un-convergence ambiguities can be controlled efficiently and the success rate of PPP ambiguity fixing is improved.

High Accurate Estimation of Point Spread Function Based on Improved Reconstruction of Slant Edge

FAN Chong, LI Guanda, WU Chaoyun, LI Cheng, ZHONG Lei

2015, 44(11):  1219-1226.  doi:10.11947/j.AGCS.2015.20140400

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A high accurate estimation algorithm for point spread function which is free from edge slant angle is proposed. In this algorithm, high accuracy estimation of point spread function is gained by improved edge line fitting, sample denosing and anti-aliasing resampling. Compared with the existing slanted edge methods, the new method yields a significant improvement in accuracy and stability.

Informative Vector Machine Classification for Hyperspectral Imagery

TAN Xiong, YU Xuchu, QIN Zhiyuan, ZHANG Pengqiang, WEI Xiangpo

2015, 44(11):  1227-1234.  doi:10.11947/j.AGCS.2015.20140600

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Informative vector machine is a method of sparse Gaussian process based on Bayesian theory, which has high speed in model training, small consuming in memory, strong effective in sparseness and good forecasting performance. In this paper, the Gaussian process regression model is introduced firstly, and then a hyperspectral imagery classification method based on informative vector machine is brought forward. Secondly, to solve the problem of non-Gaussian noise model in the Gaussian process classification, the classification problem is transformed into a regression problem by using the assume density filtering algorithm, after which model is trained by maximizing the marginal likelihood function. Finally, the number of informative vector is chosen in active subset to achieve the purpose of sparse. According to the experimental results of ROSIS images, the advantages of hyperspectral imagery classification method based on informative vector machine are validated.

Noise Estimation from Remote Sensing Images by Fractal Theory and Adaptive Image Block Division

FU Peng, SUN Quansen, JI Zexuan

2015, 44(11):  1235-1245.  doi:10.11947/j.AGCS.2015.20140327

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A novel approach for additive noise estimation from highly textured optical remote sensing images has been proposed, which is based on fractal theory and adaptive image block division. Different from the conventional regular block division based noise estimation methods, the divided adaptive image blocks with the proposed method are adhering to the local image information, which are most likely to be homogeneous blocks. Combining with the week textured image region detection using fractal theory and noise standard deviation calculation using statistical analysis, the proposed method can automatically estimate additive noise intensity from optical remote sensing images. Quantified analysis of experiments with ZY-3 satellite images demonstrates that the proposed method is applicable to optical remote sensing images with various complexities and different noise levels. Meanwhile, the notion of week textured image region detection and adaptive image block division can also be applied to multiplicative noise estimation from radar images after modification.

High Quality Targets Selection in SBAS-InSAR Technique by Considering Temporal and Spatial Characteristic

XIONG Wenxiu, FENG Guangcai, LI Zhiwei, DU Yanan, LI Ning

2015, 44(11):  1246-1254.  doi:10.11947/j.AGCS.2015.20140547

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Traditional coherence-based point-selection method in the SBAS technique is often suffered from the side lobe effect problem, which can result in the omission of partial high-quality points and reservation of partial low-quality points. A new algorithm to select high-quality points is proposed in the SBAS technique by quantifying the separated noise phase component. Compared with the traditional filtering methods, it is found that the Non-Local algorithm considering the homogeneous points can accurately separate spatially-correlated phase from the unwrapping differential interferometric phase, and then the precision of the noise phase component estimation is improved. Coherence-based approach and our new algorithm are compared by selecting high-quality points and mapping the surface deformation of the test area in Shanghai. There it is utilized the 24 JERS-1 SAR images acquired from 1992 to 1998. The results suggest that the proposed algorithm not only can select the high-quality points in fields covered by farmlands and hamlets which are omitted by coherence-based method, but also can effectively exclude the points extracted by coherence-based method due to the side lobe effect.

SAR River Image Segmentation Based on Reciprocal Gray Entropy and Improved Chan-Vese Model

WU Shihua, WU Yiquan, ZHOU Jianjiang, MENG Tianliang

2015, 44(11):  1255-1262.  doi:10.11947/j.AGCS.2015.20140519

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To further improve the accuracy and speed of river segmentation on synthetic aperture radar(SAR) images, a segmentation method is proposed, which is based on improved Chan-Vese(CV) model combining with reciprocal gray entropy multi-threshold selection optimized by artificial bee colony algorithm. Considering the uniformity of the gray level within river object cluster and background cluster, a coarse river image segmentation is made by using the multi-threshold selection algorithm based on reciprocal gray entropy and artificial bee colony optimization; Contrapose the low convergence speed and the sensitivity to initial conditions of basic CV model, the Dirac function is replaced with the image edge intensity and the coarse segmentation results serve as the initial condition of improved CV model which is utilized to make a fine segmentation for the river image. A large number of experimental results show that, the proposed segmentation method needs not set initial conditions and has high running speed as well as segmentation accuracy.

A Global Optimal Coherence Method for Multi-baseline InSAR Elevation Inversion

HUA Fenfen, ZHAO Zheng, WANG Mengmeng, ZHANG Jixian, HUANG Guoman

2015, 44(11):  1263-1270.  doi:10.11947/j.AGCS.2015.20140694

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A global optimal coherence method for elevation inversion from multi-baseline polarimetric InSAR data is proposed. The multi-baseline polarimetric InSAR data used in experiments were obtained by Chinese X-SAR system and Germany's E-SAR system. Through combining several full polarimetric InSAR images, the proposed method constructs the multi-baseline polarimetric InSAR coherency matrix, and solves the optimal interferograms under global optimal coherence criterion. The optimal interferograms generated by global optimal coherence method were used to calculate the elevation of target with multi-baseline InSAR elevation inversion method. The proposed method reduces the influence of different scattering centers effectively using multi-baseline InSAR, which improves the accuracy and reliability of the interferometric phase and eventually improves the accuracy of DEM. The results verify the validity of the proposed method.

A Method of Spatio-temporal Trajectory Fusion and Road Network Generation Based on Cognitive Law

TANG Luliang, LIU Zhang, YANG Xue, KAN Zihan, LI Qingquan, DONG Kun

2015, 44(11):  1271-1276.  doi:10.11947/j.AGCS.2015.20140591

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The spatio-temporal trajectory of taxi GPS data in streets and small lanes of Wuhan city is taken as the experiment data source, based on the "perceptual-cognition-experience" three levels of cognitive law, a new approach for track fusion and road network generation is put forward from the GPS spatio-temporal trajectories. The experiment with the taxi GPS trajectory in Wuhan is done, and the results are shown us that the proposed method in this paper for the taxi trajectory fusion and road network generation is practicable.

A Topological Process Model of Trajectories-regions Based on Critical Points

WU Tao, XIANG Longgang, GONG Jianya

2015, 44(11):  1277-1284.  doi:10.11947/j.AGCS.2015.20140261

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The increasing pervasiveness of movement data, as a consequence of ubiquitous positioning techniques, has made researches on trajectories in the spotlight, which can facilitate and convey valuable knowledge to various kinds of studies as well as applications, such as spatio-temporal query and data mining. Despite recent research interest on trajectories switched from raw data to semantic trajectories, neither of them take into account topological invariants harbored in movements. This paper develops a topological process model of trajectories-regions based on critical points in a two-dimensional space, which distinguishes 14 basic intersection types, in point set topological theory, between trajectories and region objects by the pattern of a nested matrix, combined as sequences of intersections for describing topological correlations of trajectories-regions. The model is not only a description of topological invariants among trajectories and regions, but also the complicated topological process covering multi-trajectory and multi-region, by incorporating semantics of trajectories' behaviors. Also, constraints on trajectories' movements, brought by topological relations among regions, are discussed in the model by means of intersection linkage patterns between two adjacent intersection events.

A User Profile-driven Intelligent Service of Remote Sensing Information

YANG Xiaoxia, XU Ting, LI Shaoda, YANG Ronghao, DING Yulin, CAO Zhenyu

2015, 44(11):  1285-1294.  doi:10.11947/j.AGCS.2015.20140413

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To overcome limits of traditional passive remote sensing data distribution methods, personalization is an inevitable trend of spatial information service. User profile is the basic foundation for personalized, active and accurate spatial information dissemination service, which can be used in the definition of users' preferences or interests of remote sensing data. In view of the coverage characteristics of remote sensing data in spatial and spectrum, this paper adopted the interval mathematics method into the representation of user profiles. Based on user profiles, the concepts of the correlation degree and interest degree are introduced. In addition, by the construction of decision matrixes, the solutions of the generations of intelligent services can be converted into the solutions of multiple attribute decision problems. Finally, an instance is given to show the usability of the presented method.

GNSS/INS Integrated System Model Refining and Position & Attitude Determination Using Carrier Phase

GAN Yu

2015, 44(11):  1295-1295.  doi:10.11947/j.AGCS.2015.20150368

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Agent Technology Applied in Map Generalization: Case Study for Land-use Patch

JIA Xiaobin

2015, 44(11):  1296-1296.  doi:10.11947/j.AGCS.2015.20150245

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BDS/GPS Multi-frequency Real-time Kinematic Positioning Theory and Algorithms

LI Jinlong

2015, 44(11):  1297-1297.  doi:10.11947/j.AGCS.2015.20150254

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Research on Service Encapsulation Method of Geographical Model

HU Di

2015, 44(11):  1298-1298.  doi:10.11947/j.AGCS.2015.20150291

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