2014 Vol. 39, No. 2
Objective The data fusion for GNSS processing often have some functional model constraints amongparameters or some stochastic model(prior information for total or part parameters)constraints.Inthis paper,the parameter estimators for dual functional and stochastic information constraints arepresented in least squares principle,and the posteriori precision estimators are also derived.As somespecial examples,the parameter estimators with only functional model constraints or stochastic modelconstraints are derived respectively.The properties of the data fusion with dual constraints are dis-cussed in theory.By analyzing the influences of the functional constraints,it is pointed that any errorin the functional model constraints will result in compulsive twist in estimated parameters which iscalled“hard twist”.The errors of the stochastic model constraints will also result in bias of parameterestimates,which is called“soft bias”.An actual GPS network with measurements of two epochs,2011and 2012,are employed in the data fusion,by which the contribution and effects of the function-al and stochastic model constraints are analyzed.
Objective Based on GNSS observations from the IGS,this paper reconstructed the 3Dspatial and tem-poral distribution of ionospheric electron density over Europe during three strong magnetic storms in2003-2006,using computerized ionospheric tomographic technology(CIT).The reconstructed imagespresent the 3Dstructure of ionospheric electron density.By analyzing the evolutionary process of ion-ospheric disturbances,the paper shows that ionospheric responses are coincident with the developmentof magnetic storms;and further that such disturbances have a remarkable latitudinal effect.Addition-ally,the altitudes where electron densities are the maximum also changed during the magnetic storms.The research and analyses in this paper illustrate that CIT can reflect the distribution and involvementof electron densities in each longitude,latitude,and altitude lane.CIT is shown to be useful for im-proved analyses of ionospheric disturbances during magnetic storms.
Objective The Jason-2satellite is an altimeter satellite,which means orbit precision must reach cmlevel.Jason-2’s precise orbit is determined from Jason-2’s satellite-borne GPS data using the zero-difference reduced-dynamic method,introduced for the processing of precise orbit determination,itanalyzes the precision of orbit determination.An experiment for precise orbit determination is donewith actual data to compare the overlap orbits from the reduced-dynamic method,the radial accuracyreaches 1.19cm,and result compares with POE provided by CLASS,and analyse the difference inRTN.The study shows that the radial accuracy reaches 5.54cm.Comparing with SLR data,the studyshows that overall accuracy reaches 6.63cm.In general,the accuracy of the computed orbit is at centi-meter level.,and it reaches the required standard.
Objective At present,China’s BeiDou Navigation Satellite System(BDS)has completed a constella-tion of regional network.The system provides a set of ionospheric parameters for the BeiDou Klobu-char model every two hours.Using a high precision GIM model for CODE as a reference,the perform-ance of ionospheric parameters and positioning assessment of BDS are evaluated.The data shows thatcorrection accuracy is generally 70% or more,the correction error in the Northern Hemisphere isabout 1.5meters,and 3.5meters in the Southern Hemisphere.In the Northern Hemisphere,the cor-rection precision in mid-latitude region is higher than high-latitude and low-latitude region.The preci-sion for BDS SPP on frequency B1is about 3meters in the horizontal direction,and about 7meters inthe vertical direction using BDS Klobuchar model.In comparison to use GPS Klobuchar model,preci-sion increased by about 10percent,especially in the vertical direction.
Objective Multipath must be eliminated as an important error source when improving relative positio-ning accuracy of GPS short baseline in practical deformation monitoring engineering such as for dams、high-rise buildings and big bridges.In this study,a new sideral algorithm based on a double residualin the GPS observation domain is proposed to mitigate mutipath errors.We calculated residuals for alldouble observations after resolving ambiguity while denoising those residuals for the first day.Theseresults were taken as a multipath model to remove the mutipath errors from the double difference ob-servation equations of the subsequent day by taking advantage of sidereal repeatability of every satel-lite.Clean double observations without multipath errors could be extracted,and a better baseline co-ordinate sequence was consequently calculated.The results show that this new method not only doeswell in the vertical precision but also reduces the root mean squre(rms)in horizontal coordinate preci-sion by 23%,as compared with traditional sidereal filter.
Objective Responding to the disadvantages existing in the total least squares algorithm(TLS),thevirtual observation method is employed to transform the TLS into a classical least squares algorithm(LS).Then,a matrix vectorization formula suitable for three-dimensional coordinate transformationis deduced.In this way,unification of LS and TLS is realized.As compared to other algorithms,thismethod has a stricter theory and simpler calculation process.A numerical test proves that a more rea-sonable transformation result can be obtained by using this method.
Objective The discussion of Rayleigh waves in near-surface investigations is rarely based on layered anisotropymedia,even as higher-mode Rayleigh waves are a hot topic in near-surface investigation.This paper discussesthe azimuthally anisotropy of multi-mode Rayleigh waves in layered azimuthally anisotropic media.The azi-muthally anisotropy degree of 45°is the highest.In most situations,the higher modes of Rayleigh waves aremore sensitive to the azimuthally anisotropy than the fundamental mode.
Objective The purpose of this study is to develop a decision support system for solving land-use alloca-tion optimization problems.After analyzing the characteristics of land-use allocation optimizationproblems,a framework for multi-objective artificial immune system model for land-use allocation opti-mization was proposed.Then,the architecture and a series of standard application programming inter-faces(APIs)for the system are designed to meet the needs of users with different roles.Finally,theland-use allocation optimization problem of Zigui County in Hubei province of China is employed as acase study to evaluate the functionalities of the system and the performance of the optimization mod-els.
Objective A Land use zoning model was constructed by spatial clustering as integrated with GIS andCLONALG.The key technology of this algorithm,including coding,antibody-antigen affinity,anti-body diversity,was improved.This model is verified by a case study of land use zoning in Wulie,Changjiang county,Hainan province.The results show that this model can be used for land use zon-ing in a multi-constrained environment.Due to the advantages of global optimization,this stable andreliablemodel can provide a scientific and rational land use planning scheme to support land use plan-ning and land use regulation and management.
Objective In this paper,a new algorithm is given for computing the smallest-area enclosing rectangle ofpoints,lines and polygons.First,the problem of calculating the smallest-area enclosing rectangle for points,lines and polygons is converted to the problem of computing the smallest-area enclosing rectangle for theirconvex hull.Secondly,the four points of the rectangle for a convex hull are computed by geometric computa-tion.The computation of many angles of rotation and coordinate transformations is avoided in order toimprove the precision.Finally,the new algorithm is verified with some examples.
Objective The medial axis(or a topological skeleton)is a thinner version of a geometric object,whichis equidistant from the object’s different edges.It can be seen from this definition that medial axisconstruction involves defining the“different edges”problem.Actually,the graph structure of polygonmedial axis shows that there is a medial axis in polygon convex vertex,and no medial axis(outside thepolygon)in a polygon concave vertex.In this paper,the left and right point method was adopted tojudge if one vertex of a polygon is a concave vertex or not,and then the different boundary segmentsof such polygons were defined and labeled.With the aid of ArcGIS software,this paper presents twomethods for constructing approximate a medial axis for planar free-form shapes:one is vector methodbased on the Voronoi diagram;another is raster method based on the regional distribution based onthe Euclidean distance.Experimental results show that both methods are both effective and feasible.
Objective Using spatial cognitive principles drawn from the Gestalt psychology,an improved cone-based model is proposed for computing and describing spatial direction relations.The basic idea of themodel is:first,calculate the MBR(minimum bounding rectangle)of the reference object;then,takethe midpoints of the four edges of the MBR as the starting points to construct four cone direction re-gions(N,S,W,E);finally,use the edges of the four cone direction regions,the edges of the MBRand their extension lines to re-divide spatial directions.Experiments show that the improved cone-based model can effectively overcome the defects in the existing cone-based models.
Objective Corresponding feature matching,essentially as a matter of global combinatorial optimiza-tion,is one of the key technologies for geospatial data integration,fusion and update.In this paper,aglobal optimum matching solution is achieved taking the advantages of ant colony optimization groupsand random search,without the centralized control and global model.The basic principle of ant colonyoptimization for road network matching is explained first,with a mathematical constraint model con-sidering both geometric error and structural characteristics.Then,the matching problem solutionmodel is designed,with a self-adaptation and local search strategy employed to improve efficiency.Fi-nally,the key steps are given.Experiments show that the ant colony optimization approach is effec-tive,feasible and practical,providing a new idea for road network matching.
Objective The structure of interval type-II fuzzy regions was analyzed based on the interval type-IIfuzzy region model.The n-intersection matrix and the calculation for each cell of a topological relationin an interval type-II fuzzy region were developed by extending the classical n-intersection model forcrisp regions.Then,the formalization analysis method of topological relation of interval type-II fuzzyregion was proposed.The similarity between topological relation matrix of interval type-II fuzzy re-gion and eight basic topological relations was calculated and sorted,then the basic relation correspond-ing with the maximum similarity degree becomes the primary topological relation,therefore possiblerelations can be analyzed through combining the topological relation distance.The theory and methodproposed by this paper was validated by a test case.
Objective Based on the actual demands of emergency evacuation,this paper establishes a multi-objec-tive optimization model which takes the flow of each path as a control variable.Maximum flow,mini-mum cost,and maximum reliability are considered as objectives to integrate the timeliness,economyand security of emergency evacuation.An improved Pareto multiple objective genetic algorithm is pro-posed,to encode the control variables directly.It introduces a fitness function based on the degree ofPareto domination and self-adaption punishment,and designs a selection operator based on tourna-ment and niche technology.The algorithm provides a practical tool to solve the problem with complexconstraints and multiple objectives.Finally,a real world road network is used for simulation and ana-lyses,which validates the effectiveness and applicability of the proposed methodology.
Objective Decomposition of a Geo-video stream presents the expression of video from spatial featureset.Although it has been studied widely,spatial relations underlying a scenario are not well under-stood.Here we use a method which takes advantage of`random graph theory to investigate the seman-tic knowledge in Geo-video,leading to correlation analysis of the target motion elements in a Geo-vide-o stream.We used the connections of target motion elements,both correlation and continuity,to leadto a structure in time series that reveals clues to the event development of the video stream.Further-more,it provides a method for the effective integration of semantic and campaign information.Ulti-mately,experimental results show that the method offers a better description of video elements thancan be achieved with existing schemes.In addition,the proposed method offers a new way of thinkingabout the semantic description of the geographic video scenarios.
Objective Existing geography topic models do not consider the degree to which different regions influ-ence microblog topics.Meanwhile,these models describe the topic evolutions in a discrete mannerwhich prevents the acquisition of topic intensities over continuous time.This paper proposes a novelspatio-temporal topic model to discover microblog topics by introducing continuous time and region in-fluences.A city was divided into multiple geographic regions.Region weights,expressing the regionfunction influence degree on microblog topics,were allocated to regions based on the number of differ-ent POI(Point of Interest)types.Then a sparse additive generative model was applied to generate mi-croblog topic distributions.Beta distributions were employed to depict topic evolution over continuoustime.Finally,we use a Gibbs sampling method to estimate model parameters.Experimental resultsshowed that not only does our model track the temporal distribution of microblog topics but also en-hances topic extraction accuracy when compared with other geography topic models.
Objective Robust affine-SIFT(ASIFT)algorithm is attractive to wide-baseline stereo image match ap-plications.However,due to exhaustive image stimulation covering a whole 3D viewpoint space,ASIFT is quite prohibitive in practice due to its huge computation demands from image feature de-scription extraction and high-dimension vector distance calculation.By adaptively selecting the mostvalid fewer affine transformations and implementing less image stimulation,ASIFT is re-developed toachieve high efficiency suitable for the needs of real applications.First,the theory behind ASIFT forstimulating single images based on absolute viewpoint direction is outlined.Also,a relative affinetransformation stimulation model for stereo images is formulated and estimated with homographymapping,and photogrammetric computation.Afterwards,we propose a single progressive computa-tion procedure for quickly obtaining fewer conjunctive points and the parameters for relative affine transfor-mation stimulation.Steps to select valid affine transformations are also summarized.Next,SIFT is imple-mented to select fewer stimulated images to obtain reliable match results.Finally,a sequence of wide-baselinestereo images is tested with proposed approaches and some conclusions are drawn.
Objective With the improvement of SAR image resolution,it is now increasingly used as an effectivedata support for building extraction.However,the traditional pixel-based method is not practicable inbuilding extraction.Not only are the result not amiable,but also the accuracy is very poor.So in thispaper we will firstly apply FNEA algorithm(fractal net evolution approach)on SAR image to obtainanalysis units.Then contextual feature of those object-level units will be utilized to propose the con-ception of highlight adjacent intensity(HAL)and shining point distribute density(SDD).After thatthese two features will be combined to be used in the process of object-level building extraction.Final-ly,a couple of experiments are conducted show that an object-oriented method outperforms pixel-based methods in building extraction from high-resolution SAR images.
Objective This paper proposes an original experiential methodology to retrieve bare surface soil mois-ture by two-polarized microwave remote sensing data.In the model,we combined the roughness pa-rameters,the root mean square Sand correlative length L,and introduced a new synthetic roughnessparameter Rsto describe the land surface.So,the unknown parameter in this model reduces to RsandFresnel reflection coefficient in normal directionГ0.Then,Г0and Rscan both be retrieved using two-polarized microwave data.In situ measurements from Heihe experiments were used to test the empiri-cal model.Results indicate that there is a strong linear relationship between the estimated soil mois-ture and the in situ measurements(R2=0.681,RMS=0.043).
Objective To solve the line matching problem caused by obstruction and extraction algorithm for close-range images,a novel algorithm of matching straight line based on local affine invariant and epipolarconstraint is presented in this paper.On the basis of straight line extraction and corresponding pointmatching on close-range image pairs,the linear feature’s candidate corresponding lines are firstlysearched based on the intersection affine invariant character of the lines including the extracted andvirtual straight ones,while endpoints of the virtual are corresponding points near the extracted lines.Then,the overlapping parts of the target lines and the matching candidates are calculated based onepipolar constraint.The right corresponding lines are finally acquired with the help of the comprehen-sive similarity measure derived from angle and neighborhood grey level of the straight line.Using theapproach proposed in this paper,experiments were carried out for the close-range images under differ-ent geometric transformation.The results show that this method has a good reliability and accuracy.
Objective In this paper we propose a method for automatic cloud detection,which employs both spec-tral and shape features.This method includes two main steps.First,based on the different spectralfeatures of clouds and snow,an otsu-based method is used for threshold segmentation of a TM Image.Then,clouds are successfully extracted by discriminant analysis using the shape feature.Experimentsindicate that as compared to the traditional threshold-based methods,the proposed method can effec-tively detect clouds with an improved automatization level.
Objective To overcome the problem of a degraded image due to the reduction of contrast under hazyweather,according to the differing polarization characteristics between the target scene and atmos-pheric aerosol,we researched image restoration for target recognition based on polarized detectionthrough haze.To obtain different polarized orientation images by experiment during hazy weather,weproposed an image restoration algorithm to enhance the image contrast,to remove degradation fromhaze on images.Experimental results show that this algorithm can effectively enhance image contrastand entropy as well as recover the target.As a by product,the method yields a range map of thescene.This research provides an effective method for the target recognition under hazy weather conditions.
Objective The temporal InSAR technique overcomes the temporal/spatial decorrelation with the slowdecorrelating filtered phase(SDFP)pixels identified by phase stability.In this paper,the Tanggu are-a has been selected as study area,where the subsidence information due to groundwater overexploita-tion from May 1992to December 1998has been inversed by processing 19ERS-1/2acquisitions usingthe temporal InSAR method.The subsidence in time of the SAR imaging has been estimated accurate-ly using cubic polynomial model.And the result derived from temporal InSAR was consistent with thelevel data which was regarded as GCPs with a little difference that less than 5mm/a.Besides,the re-sult also showed that the whole study area has suffered subsidence with a mean rate 20～50mm/a dur-ing 1992to 1998,and the subsidence is severity in the eastern.