2012 Vol. 37, No. 6
To further confirm the role that forest ecological system plays on global warming and global carbon cycle,quantitative study on forest biomass of large scale areas is needed.Traditional approaches based on field measurement are highly accurate,while they are only fit for small place and difficult to implement in large place.With the breakthrough progress in quantitatively obtaining forest parameters such as height of forest,canopy density,etc.,remote sensing has become the primary source for biomass estimation.We review research progress of remote sensing-based biomass estimation from single-and multi-sensor data,and discuss existing issues influencing biomass estimation.
An object-oriented typical ground objects extraction method based on multi-level rules is presented to solve the problem of ground objects extraction,which are complex and various in high resolution remote sensing image.Image segmentation method based on region is improved with an initial growing by global optimal principle,avoiding seed selecting.Image objects from image segmentation are used as primitive for extraction of ground objects extraction.The typical extraction features are analyzed for different ground objects.Multi-level rules are made based on different features and used to extract ground objects.And overall exaction accuracy of 87.1% is achieved in the experiment.
We explore widely used K-means algorithm and propose two methods to improve its performance for hyperspectral clustering and analysis.A novel initialization method based on orthogonal subspace projection(OSP) is presented,which can get the suitable initial seeds for K-means clustering.In addition,we address a new cardinality estimation index which maximizes the distance ratio between intra-cluster distance and inter-cluster distance.It is used as a tool to estimate the numbers of clusters in K-means for hyperspectral data.The experimental results show that the proposed method can performs better than other traditional methods.
Gray level difference index is proposed to quantize the gray level differences between two pixels in a multispectral image theoretically.In the view of Top-of-the-Atmosphere Effect(TOA),the weak information in multispectral image can be suppressed in the strong reflective/rediation field.A novel algorithm is developed to detect edge feature homogeneously and weaken or suppress the effects of TOA.In spectral vector space,the gradient magnitude and direction of a multispectral image is charectrized by the eigenvalues and eigenvectors by the first fundamental form.And dyadic B-spline wavelet transform is applied to obtain edge information in scales from fine to coarse.The results show that the response of gradient is more homogeneous and significant than Canny and Sobel detector results,and integration multiscale edge feature can locate the edge points accurately and ignored the nosie affection.
The purpose of image registration is to remove inconsistencies in geometry between the matched registration image and the reference image,including translation,rotation and scaling transform,which is the necessary premise for image contrast,data fusion,transform analysis and target recognition.A new kind of remote sensing image registration,which is called Fourier-Mellin transform method is put forward.Firstly,Fourier transform is performed to get frequency spectrum power for the reference image and the matched image respectively.Next,high-pass filtering is conducted with regard to their energy spectrum.Then,energy after filtering is converted into log-polar coordinate formation.In the case,mutual power spectrum can be computed adopting phase correlation technique to obtain their rotation angle and scale factor correspondingly.Lastly,transform image may be gotten by these parameters.And again,for reference image,high-pass filtering is performed to reduce background noise and frequency aliasing interference in the transformation process.Then,phase correlation calculation may achieve translation value,another transform image can be gotten through translation transform.Finally,registration image may gain by the two images' superposition.The experimental results show that the algorithm is efficiency and reliability.
Surface bi-directional reflectance distribution function(BRDF) model can be applied to retrieve land surface climatological or biological parameters.However,in geosciences,it is often an ill-posed inverse problem to extract true information of complex surface through BRDF model inversion with limited satellite observations.Based on analysis of the cause of instability in model inversion and the mechanism of data error propagation,regularization filtering technique was adopted to overcome the difficulty due to the discrete ill-posedness in inverting the BRDF model.In order to test the retrieval ability and validity of the presented algorithm,multi-angular POLDER-3/PARASOL BRDF data and MODIS satellite data with deficient looks over the Tibetan Plateau were used.Retrieval results reveal that accuracy of the proposed regularized filtering algorithm is equivalent to that of MODIS AMBRALS code and thus it can be applied to retrieve land surface parameters using sufficient or even sparse observations.
The single-and dual-frequency ionosphere corrections in satellite altimetry are analyzed in detail.Taking Topex dual-frequency ionosphere corrections as an example,RMS of cross-over difference can be reduced upto 5.7-7.3 mm by along-track filtering of low-pass Gauss.Then,the filtered Topex ionosphere corrections are cross-calibrated with DOIRS,IRI2007 and GIM models that are established by measurements of global continuous GPS tracking stations.The results show that the accuracy of DORIS and GIM is higher than that of IRI2007.The statistics of difference between the filtered Topex dual-frequency ionosphere correction and that from these models show a systematic bias of 10-15 mm.
Considering the practical background of few data and unpredictable probability distribution in the domain of equipments test and training,a novel trajectory prediction method based on MGM(1,N) model was proposed to predict the location of moving object such as unmanned aerial vehicle.Firstly,the principle of MGM(1,N) model and the parameters estimation algorithm were introduced.Then a MGM(1,3) model for 3 location coordinates of a moving object was carried out and the implementation steps was illustrated accordingly.Finally the simulation through the aviation data of an unmanned air vehicle was utilized to prove the validity of such method.The simulation results show that the proposed approach is feasible and effective,which can predict the location information of any time in the next period with high prediction precision.
For GPS single frequency users,the ionospheric delay error is the most serious and intractable problem.High efficiency and high precision correction of ionospheric delay error is the most critical factor to determine the positioning accuracy of single frequency users.Several new correction programs are discussed.The efficiency and feasibility of new algorithm are tested by examples.And some reasonable proposals for different precision users to select ionospheric delay correction programs are given.
The traditional methods of calculating the bending angle are mainly radiosonde and model.Although the accuracy of bending angle calculation based on radiosonde is high,the radiosonde is unfit for real time application for its limitations such as inefficiency,high cost and great interval between adjacent observations.The model method is simple,but its accuracy is poor.The estimation of real time bending angles based on singular ground-based GPS is presented.The method can overcome radiosonde limitations and is fit for real time application.In order to validate the feasibility,an experiment of GPS and radiosonde is carried out on an island in Shantou,south China,and the observations of qingdao GPS station are disposed.Through results comparing between GPS and radiosonde,we find that the GPS results agree well with those of radiosonde,and are better than those of Hopfield model.
We give an analysis of 27 fiducial stations'coordinates of time series data in China since March 3,2011,which are sub-band processed through the wavelet transformation to extract a long trend items(T≥512 d) primarily.From the curve of the long trend items we can see that the stations have regional characteristics,the stations from the same region have a big correlation coefficient,and has a good coincidence with the block.When the curve has fluctuation characteristics,there always be earthquake above Ms 7.5 happened in Chinese mainland and its surroundings afterward.This phenomenon is of great significance and reference value for the medium-term(1-3 a) Earthquake prediction.
The time variable gravity in Wenchuan and its surrounding areas was calculated by using the GRACE data published by UTCSR.Then the multi-scale wavelet analysis was used to decompose the satellite gravity field,therefore,details and approximations reflecting different depth of geological bodies were obtained.By studying changes in the gravity field of every detail and approximation component,combining with the features of regional tectonic movement,a preliminary explanation and discussion on the features of time variable gravity as well as the dynamic mechanism of Wenchuan earthquake was presented.The results show that the change in gravity which caused by the tectonic deformation and deep mass transfer in Wenchuan area is revealed effectively by the fourth-order detail and approximation.Moreover,the features of changes in gravity before earthquake meet the conditions of earthquake preparation and occurrence.
Ambiguity resolution(AR) instantaneously is a significant way to improve the continuity and reliability for GPS kinematic deformation surveying system,and the AR is easier for longer wavelength.We propose a new method for AR in double-differenced level using a single epoch of data.Two combined signals with longer wavelength,φ-3,4 and φ4,-5,are used in this method.Based on the constraints of priori coordinates and the relation between the dual frequency,AR instantaneously is achieved.A robust adaptive Kalman filter is used for ensure the reliability of AR and the accuracy of position.The tolerance of position error for priori coordinate is exceeded to 50 cm and suit for kinematic deformation surveying.
A new algorithm of instantaneous double difference ambiguity resolution for long-range reference stations of Network RTK is proposed.The wide-lane ambiguity are determined by the linear relationship between double frequency carrier phase ambiguities.Then candidates of double frequency carrier phase ambiguities can be selected,the integer ambiguities are searched out through the computation of non-dispersive error e.g.tropospheric delay and orbit offset between reference stations.Test data were used to evaluate the algorithm.The results indicate that this algorithm can provide reliable double difference integer ambiguities very quickly for long-range reference stations.
A real time cycle slip detection method is proposed based on Jarque-Bera test for testing the normality of slip parameter in epoch window,which constructed by bi-differences of pseudo range and carrier phase observations.Real time cycle slip detection tests are analyzed with GPS static observation data and on-board GPS dynamic data.The results indicate that the algorithm can detect outliers in real time,and provide the base of data quality controlling for real time precision orbit determination and positioning.
On the basis of preliminary cycle slip detection by the W-M wide lane linear combination,a new method is introduced to make a second detection.The differences of the ionosphere-free L3 combination observables in the successive epochs can be used to work out the change of receiver clock errors when a-priori satellite orbit is known.For observables with cycle slips,their resulting values would be distinct from others in the same epochs.Exprimental results show that new cycle slips can be dug out while detected cycle slips in previous step are verified by the twice detection method.
Unscented transformation is analyzed through the viewpoint of statistical linear regression,and iterated unscented Kalman filter(IUKF) is derived.The so-called hybrid iterated unscented Kalman filter is presented by incorperating secant method into IUKF in order to cope with the high-computation-cost problem.New filtering method is introduced into the example of univariate nonstationary growth model.Simulation results show that new method outperforms extended Kalman filter,iterated extended Kalman filter and unscented Kalman filter.The computation cost can be reduced relative to IUKF.
Klobuchar model is used for ionospheric delay correction by GPS,and NeQuick model is used by the Galileo system with the same purpose in the single frequency mode.We consider ionosphere products that are post-processed by Center for Orbit Determination in Europe as reference,taking advantage of vertical TEC data provided by Klobuchar and NeQuick model for the 15 GPS basic stations in Crustal Movement Observation Network of China from the year 2000 to 2008.And the eight coefficients for Klobuchar model will be provided by CODE and GPS navigation message respectively,we analyze the application of the two models in the Chinese region.① It is more obvious that the bias of Klobuchar model will increase with respect to the lowering of latitude.Both NeQuick and Klobuchar model of GPS broadcasting are observed to have stronger links to the periodic variations of solar activities.② There are relatively large standard deviation which has excluded bias,in the two models in peak year of solar activity and low latitude region.yet on the whole,NeQuick model produces the least standard deviation.③ The fact that the two models,when applied to the area of China,show regular variation depending on solar activities and latitude,provide with the possibility and basis of the further optimization and improvment of them.
Anomaly of mathematical model in Kalman filter can be caused by various outliers in precise point positioning.To find out the minimal detectable biases(MDB) resulting from this anomaly and the effects of undetectable outliers on estimator,the reliability of Kalman filter is necessary.This reliability of both measurements and predicted state are derived according to the reliability theory of the least squares and compared with the reliability of traditional redundancy.The results show that the internal reliability of two methods is related not only with the precision of the observation,but also with satellite geometry as well as elevation.Meanwhile,the internal reliability of predicted state is more sensitive with geometry than the internal reliability of measurements.Although the external reliability of two methods is at mm level,the convergence of pseudorange is faster than carrier phase.
A new TDMA technique is introduced into inter-satellite network of satellite navigation system,which allows a satellite to seize the timeslot of another satellite.The delay of waiting for transmitting signal is reduced significantly comparing with the traditional TDMA.The optimum object of timeslot assignment is formulated for the new TDMA technique.According to the inter-satellite visibility of the navigation constellation,an algorithm is proposed to achieve the object of the timeslot assignment based on the vertices coloring theory.The simulation results show that the communication system is improved significantly by the new TDMA technique without influencing the satellite obit determination and URE performance comparing with the TDMA adopted by GPS.
Based on the theoretical study status of three-dimensional topology and real three-dimensional topology of specific applications needs,we analyze the topological relationships in some particular application areas,and conclude two approaches of building three-dimensional topological relationship with different data organization.Two methods mainly build exterior topology between bodies,while maintain interior topology within a body.The first one implements topological construction after body constructed individually.The second takes into account that most 3D model data organization are based on discrete faces set,and come up to a auto-search bodies algorithm which simultaneously gets the exterior topological relationship between bodies.Lastly,taking 3D data based on special parcel data and architectural plan in Shenzhen as an example,we verify feasibility and effectiveness of two methods.
Pattern recognition of road networks plays an important role in map generalization,data matching and spatial analysis.A grid is characterized by a set of mostly parallel lines,which are crossed by a second set of parallel lines with roughly right angle.We propose a method for extracting the grid pattern based on graph theory.First,relation graphs of roads are created,in which the vertices represent road segments and the edges represent the roads' relation.Then grid pattern is extracted via some graph-theoretic operators such as finding connected component,creating maximal complete sub-graph,join and intersection.Experimental results show that the proposed method is valid in extracting the grid pattern.Advantages and limitations are discussed.
A complex network analysis method is proposed to estimate the hierarchies of urban road networks.The method is based on dual graph generated by the strokes of urban networks.Structural hierarchies of strokes are analyzed and different importance values of roads are calculated via each structural parameter evaluation.Finally,a multiple-criteria indices modeling algorithm is implemented to maintain the information of each structural index.Experimental results show the validities of this method.Structural hierarchy of strokes can reflect the structure characteristics of urban road networks.Compared with the single criterion and traditional road classification,the hierarchical levels division via multi-criteria integration is better fit the principle of perceptual grouping.
A Web 2.0 map is the kind of spatial information platform where customer may participate mapping,and where cartographic information transmission is two-way between customer and map.Thus,Web 2.0 map influences the transmission model of map information of A.Kolacny,where information transmission is one-way.We suggest a kind of two-way transmission model for Web 2.0 mapping based on Kolacny Model by means of a designed method of layering for Internet.This two-way model will enrich and perfect map communication theory in the Web 2.0 environment.
In the C/S mode,according to the characteristics of data organization of tile map,the method is proposed by adopting ArcEngine customized layer to draw and project the Tile Map dynamically.The thread pool,asynchronous access technology,cache,and.Net memory management mechanisms are combined to improve the efficiency of the implementation process and user interoperability.In addition,taking into consideration that the tile mosaic technology on Win32 library is specially suitable for processing small amount of data,whereas the tile mosaic technology on open source GDAL library is fit for large amount of data,the two methods are combined to implement efficiently tile mosaic.Finally,the urban planning information inquiry system shows the feasibility of the proposed method.
Focusing on the civil engineering design,we explore an efficient,integrated engineering design and application prototype system using shared Web Map Service(WMS) data.First,directly targeted on WMS data server,a WMS data acquisition application program is implemented based on WMS public access protocol with efficient parallel multi-threaded network transmission of spatial data tiles,as well as double access mechanism combined local caching with network share strategy.Second,the prototype system achieves WMS remote data localization simulated application and distributed collaborative shared by independent download application program as well as embedded real-time threads.Third,fixing on the application of WMS data in engineering,we explore a series of tools such as coordinates transformation,image merging and CAD file produce,to promote the WMS data easily converted to all kinds of different plane engineering data with high-precision.Finally,We take full advantage of WMS data organizational characteristics and develop an unified global 3D prototype platform to express and integrate various WMS data sources.The experiments show that the techniques and methods we adopted are effective and efficient.
We get some experiment data by flying on global multi-area and multi-level 3D terrain at different machine configuration.Then using the method of partial least-squares regression,we do study and analysis on the 11 hardware elements which affect 3D visualization system running capability.There is high collinearity in the data,making the least-squares regression not reliable.Using the partial least squares regression,the effect of collinearity can be mitigated effectively,and the affected complexion about 3D visualization system running efficiency by hardware elements can be easily reflected.We conclude that the main hardware affecting elements to 3D visualization system are CPU basic frequency,L2 Cache,and Memory,and L2 Cache plays an important role on the running speed of 3D visualization system.
Taking remote sensing images,fundamental geographic information data and statistical data as data sources,15 indicators were selected to construct a composite vulnerability index for assessing vulnerability to soil erosion of Poyang Lake ecological economic zone.A profile of the spatial distribution of vulnerability to soil erosion in this region shows that there is a spatial differentiation of vulnerability and the ranks of vulnerability of assessing units cluster in the middle and the high.The middle vulnerable units are located in the southeast and high vulnerable units are in the northeast lakeside of Poyang Lake.There is an obviously differentiation in spatial distribution between the soil erosion vulnerability and soil erosion status.We additionally analyzed the formation of soil erosion vulnerability from driving forces,sensitivity and response capability jointly by which vulnerability is determined.