TopicIssue
Top ViewTop Cited
- Probability Estimation of Future Earthquakes in China Based on Improved PSHA Model
- Big Data GIS
- Self-adaptive Window Extension Strategies of Discontinuity Features for MVLL Algorithm
- Experimental Geography Based on Virtual GeographicEnvironments(VGEs)
- Big Data in Smart City
- An Improved Cellular Automata Model for Simulating Pedestrian Evacuation
- Web GIS Component
- Introduction to Urban Computing
- Detecting “Hot Spots” of Facility POIs Based on Kernel Density Estimation and Spatial Autocorrelation Technique
- On Construction of China’s Space Information Network
- LUR-based Simulation of the Spatial Distribution of PM2.5of Wuhan
- Reflections on Issues in National Geographical Conditions Monitoring
- Oblique Image Based Automatic Aerotriangulation and Its Application in 3D City Model Reconstruction
Download CenterMore >
LinkMore >
Display Method:
2021, 46(3): 309-317.
doi: 10.13203/j.whugis20190131
Abstract:
Objectives Change detection is a process of recognizing the state changes of ground surface by multiple observations. With the improvement of image data quality, it provides more possibilities for people to realize change detection. Traditional multi-temporal remote sensing image change detection is easily affected by the season in which the images were taken, solar altitude angle and shooting angle etc. In addition, the traditional calculation methods of change index, variables which susceptible to the interference of change object are often introduced, such as mean value, median value and so on. To solve such problems, we proposed a change detection method based on vector data. Methods Firstly, since traditional change detection method is always influenced by shooting season, shooting angle, etc, we use a vector-image method, which is different from the previous image-image method. With the application of this method, the change differences between the old and new images were calculated by using a similarity measurement method, and the change object will identified by a threshold value. The vector-image method using the vector data and the new time image data detect the changes. Secondly, the anomaly detection method in the data mining method can be introduced into the change detection method, hence the outlier has a fewer and different characteristics compared with the normal object. In this paper, we firstly got the object through incremental segmentation under the constraints of the previous vector image, then extracted its texture and spectral features to get the dataset by the principal component analysis transform. After that, using isolation forest method to calculate object's change index, we obtained the change threshold by Bayes method. Results We took two experiments, and the effectiveness of the proposed method was verified by comparing image-image and vector-image change detection methods, as well as Markov distance and isolation forest change methods, among which, the accuracy rate of experiment 1 is 0.923 5 and that of experiment 2 is 0.931 8. Conclusions By comparing the image-image method with the vector-image method, the experimental results show that the proposed method can not only improve the accuracy of change detection, but also improve the automation and intelligence of image-based change detection.
2021, 46(3): 318-325.
doi: 10.13203/j.whugis20190032
Abstract:
Objectives Shadows in high-resolution remote sensing images will cause objects information loss and image quality decline, which is not beneficial for relative applications. Current shadow compensation methods often take advantage of non-shadow information around the shadow area to increase the brightness, whereas there is an unsolved problem that the contrast cannot be enhanced well enough and self-adaptively. Wallis filter principle has been used in image dodging. However, when it is used in shadow compensation, contrast improvement is not as good as other methods, leading to poor compensation results. Therefore, an improved Wallis model compensation method is proposed in this paper to enhance the brightness and contrast better to restore the shaded information. Methods First, by adding compensation strength and stretch parameters, an improved Wallis model is designed. The strength parameter is positive to the brightness and contrast, and the stretch parameter is sensitive to the contrast. Therefore, the improved Wallis model is more efficient to adjust brightness and contrast. Moreover, an automatic parameters calculation strategy is further explored to customize a suitable compensation model for each shadow area. On one hand, the brightness average and deviation of the adjacent non-shadow region are calculated and used as the compensation target values. On the other hand, based on searching the same kinds of points around shadow boundaries, a series of non-shadow and shadow feature points are matched. Assumed the feature value of the non-shadow point is the approximate value of its responding shadow point, they can be used to calculate strength and stretch parameters automatically. Lastly, the brightness of each pixel in different shadow regions will be compensated by customized models to cover the shaded information self-adaptively. Results In this paper, three sets of comparative experiments are set up to analyze and compare the part compensation methods algorithm, original Wallis method in three images with ordinary object shadows and cloud shadows, respectively. The differences in brightness average and gradient average between the compensated value and the non-shadow target value are used to evaluate the compensation quality. The experimental results show that: (1) Original Wallis model is useful to enhance brightness to some extent, while it is insufficient to improve contrast. As a consequence, the visual compensated results are not acceptable as the other two methods. (2) Part compensation method can improve brightness and contrast effectively. However, it cannot adjust self-adaptively according to each shadow regions condition, leading to some over-compensated and some insufficient compensation results in the same image. (3) The proposed method results indicate the best compensation quality in different shadow regions because the improved Wallis model is more pointed to improve contrast and the automatically calculated parameters values are suitable to customize the compensation model for each shadow region. Conclusions Aiming at the contrast improvement of the current algorithm of automatic shadow compensation, an automatic compensation method based on an improved Wallis model is proposed in this paper. The experimental results show that the newly designed model is more effective to enhance brightness and contrast, which is useful for finding suitable parameters values. Combining with the strategy of automatic parameters calculation, its customized model can adaptively compensate each shadow. However, it should be pointed out that there are still some limitations about the shadow border compensation and the internal difference in one shadow area, which need to be further studied.
2021, 46(3): 326-334.
doi: 10.13203/j.whugis20190440
Abstract:
Objectives In order to solve the problems of the low accuracy and the slow speed of the existing video image flame detection methods, we propose a real-time video flame detection algorithm based on improved Yolo-v3 to achieve real-time and efficient detection of flames in the video. Methods Firstly, in the feature extraction stage, the multi-scale detection network is improved. We add a new-scale feature and then improved the networks ability to learn the shallow information of the images by further integrating multi-scale features. Using this method, the accurate identification of small flame is achieved. Secondly, in the target detection stage, we use the improved K-means clustering algorithm to optimize the multi-scale prior frames, and make them adapt to the changing posture and shape of the flame. Finally, after detecting video flames based on improved Yolo-v3, we use the unique flicker characteristics of the flame to check the video again, and eliminate the false detection frame in the detection result. And in this method the detection accuracy is further improved. Results In order to prove the effectiveness of our method, the video flames are detected from both accuracy and speed, and the results are compared with the advanced flame detection methods in recent years. The results show that the average accuracy rate of our method can reach 98.5%, the false detection rate is as low as 2.3%, and the average detection rate is 52 frames/s, so our method has better performance in terms of accuracy and speed. Conclusions The effectiveness of this method is proved through multiple sets of experiments. Comparing with the existing flame detection methods, our method can be more effectively applied to video flame detection.
2021, 46(3): 335-340.
doi: 10.13203/j.whugis20180500
Abstract:
Objectives Face swapping technology has important application value in entertainment, virtual reality, film and so on. However, existing methods are limited by face pose consistency and can not overcome the influence of occlusion. Methods We proposes a method of face swapping using convolutional neural network and tiny facet primitive. Firstly, detect the face using the cascade convolutional neural network and segment the face to determine the replacement region using fully convolutional network.Then, the Wallis transform is applied to adjust the skin color of the source image to make it consistent with the skin color of the face in the target image.After that, using facial key points detection method based on an ensemble of regression trees and Delaunay triangulation to construct the face triangulation network, then replacing faces based on tiny facet primitive. Finally, applying Poisson fusion to eliminate splicing traces between different images. Results We evaluate the performance of the proposed method compared with existing method through qualitative and quantitative experiments. Experimental results show that face segment can well solve the problem of occlusion such as cap, glasses, and hair.Moreover, when source image and target image have different face poses, replacing face area using tiny facet primitive separately performs better than using the whole face area. Conclusions Our method can well solve the problem of face pose consistency limitation and occlusion, which has certain practical application value.
2021, 46(3): 341-347.
doi: 10.13203/j.whugis20190122
Abstract:
Objectives Mine environmental problems are intensifying, and the environmental monitoring and evaluation of the mining area is an indispensable part of mine management. Previous researches have obtained effective results by evaluating the mining ecological environment through the remote sensing ecological index (RSEI). However, the calculation does not take into account that the environmental influence is regional under natural conditions of RSEI, and the geo-graphical location of the mining area has different effects on its surrounding ecological environment. The main purpose of this research is to propose a new remote sensing ecological index that is more in line with the ecological response mechanism based on the characteristics of the ecological environment of the mining area. Methods Aiming at the complex research area of large area feature type, this paper presents an improved ecological index named moving window-based remote sensing ecological index (MW-RSEI) which based on RSEI and moving window evaluation unit. MW-RSEI divides the ecological environment into four influencing factors: Greenness, wetness, dryness and heat. Each pixel in the study area is taken as the research object, and the extended window of the pixel is taken as the calculation range of each factor. The experiment assigns weight to the center pixel of each window through principal component analysis. Results The MW-RSEI and RSEI models were used to calculate in the study area, the results show that the mean value of MW-RSEI and RSEI in the study area were 0.522 and 0.459, the greenness and wetness had positive effect on the environment, and the dryness and heat had negative effects. Based on the MW-RSEI model, mine geomorphology destroys the regional ecological environment grade is worst and poor accounted for 85.40% of the overall area. MW-RSEI in line with the first law of geography. Its results are consistent with RSEI, and it shows more gradient information of the ecological environment around the mining area, which confirms the theory of dissipative structure in the ecological environment. Conclusions MW-RSEI refines the local characteristics of the ecological environment, and it can provide an effective basis for ecological environment monitoring and evaluation in mining areas.
2021, 46(3): 348-352.
doi: 10.13203/j.whugis20180487
Abstract:
Objectives The accuracy of plane segmentation using a region-growing algorithm remains an important and challenging topic for terrestrial laser scanning point clouds. The plane segmentation of a region-growing algorithm depends heavily on the seed point, as there are currently no universally valid criteria. Methods Firstly, we applied the tensor voting (including representation, communication, and decomposition) to calculate the plane strength of each input point. During the communication of the tensor voting, we should use varying numbers of votes to obtain plane strengths for different scales. Secondly, we set the threshold for plane feature strength and count the scale that is greater than the threshold. We then calculate the comprehensive plane strength and use it to determine seed points. Then, according to various criteria, including the angle threshold, the distance threshold, and the minimum region size, we used these seed points to perform the plane segmentation. Results On the basis of the traditional tensor voting method, the probability of point cloud feature recognition under various scales is fully considered. A multi-scale tensor voting method is proposed to realize plane segmentation, which realizes more accurate recognition of facade features. Finally, results of contrast experiments with principal component analysis and tensor voting show that the multi-scale tensor voting method is superior in segmentation accuracy. Conclusions For terrestrial laser scanned point clouds, the region-growing algorithm is a classic plane segmentation method and is seriously affected to a large extent by seed points. Although existing research results have shown that the tensor voting has the potential to detect distinct geometric structures, such as points, lines, and planes, determining seed points using tensor voting often is heavily disturbed by effects of scale(i.e., the voten umber). We propose multiscale tensor voting method to improve the selection of seed points in region growing for plane segmentation.
2021, 46(3): 353-359.
doi: 10.13203/j.whugis20190119
Abstract:
Objectives In recent years, the convergence of shield tunnel using the terrestrial laser scanning is more and more widely, but stations changed frequently have an extreme influence on monitoring efficiency. The position of endpoints will change with the tunnel deformation when the laser point clouds is applied to fit curve in order to calculate the coordinates of endpoints. Therefore, it is difficult to ensure that the same convergent endpoints are obtained at different times using fitting curve based on point clouds which have an influence on the precision of convergence. Methods Aiming at the problem of low efficiency of station-based 3D laser scanning, this paper introduces an economical, efficient and reliable mobile laser scanning monitoring method. For the calculation of convergence value, this paper introduces a new method based on tunnel expanded image in detail. Firstly, the expanded images of tunnel were obtained by the cylindrical projection of point clouds, the expansion of standard cylinder and gray rasterization, interpolation and gray enhancement of image. Secondly, it can accurately locate the section of point clouds of each ring in shield tunnel through the binaryzation of image, connected analysis, automatic identification and manual correction of ring cracks. Then, the positions between segments of each ring were manually drawn in the expanded image and the orientations of the fixed endpoints were deduced. Finally, the coordinates of the convergent endpoints were calculated and the convergences were calculated by fitting the segments. Results The results show that the difference between the repetitive results of the convergence value using mobile laser scanning is less than 1.5 mm. Conclusions The proposed calculation method can efficiently monitor the convergence of the single-circle shield tunnel with reliable accuracy.
2021, 46(3): 360-370.
doi: 10.13203/j.whugis20190132
Abstract:
Objectives To integrate processing of BDS-2 and BDS-3 satellites observations and to conduct the deeply merged strategy for enhancing the parameter solutions, the differences between BDS-2 and BDS-3 should be considered and analyzed. Methods Given the differences of BDS-2 and BDS-3 satellites, to fully utilize and fuse the observations, the inter-system bias (ISB) model of BDS-2/BDS-3 combined precise orbit determination is analyzed and improved. Firstly, to improve the accuracy and reliability of ISB, the singular value decomposition is introduced to extract the observation information of adjacent epoch. Secondly, the characteristics of ISB are analyzed, which indicts that the ISBs are significantly presented and related with the types of receivers based on the new signals of BDS-3 and BDS-2. Then, the correlations between ISB and orbit parameters are analyzed; the results suggest that the BeiDou orbit accuracy is affected more significantly than that of GPS. Finally, based on the estimated ISB series, the short-term prediction of ISB model is established by spectral analysis, which is inserted into the ultra-rapid precise orbit determination. Results With ultra-rapid orbit determination experiments, the proposed ISB prediction and estimation strategies can improve -0.4–1.0 cm and 0.8–4.1 cm for BDS-2 and BDS-3 orbit one-day overlapping, respectively. Conclusions Therefore, it is meaningful for improving the BDS-2/BDS-3 ultra-rapid combined precise orbit determination with the improved ISB estimation and prediction model.
2021, 46(3): 371-380.
doi: 10.13203/j.whugis20190107
Abstract:
Objectives In order to effectively extract useful information from time series of the global navigation satellite system(GNSS) sites, and improve the modeling accuracy of coordinate time series, this paper proposes a nonlinear motion modeling method combining wavelet decomposition and singular spectrum analysis. Experiments were carried out using global positioning system(GPS) vertical coordinate time series of 11 stations around the world from 1999 to 2018. Methods Firstly, the coordinate time series is decomposed into different scales by wavelet decomposition.And then the singular spectrum analysis(SSA) is performed on the high-frequency part and the low-frequency part of each layer. Finally, combine the fitting value that is the fitting coordinate time series, and the fitting effect of the new method was evaluated. Results The results show that, compared with the simple singular spectrum analysis method, the new method can extract useful information such as trend and period more accurately from the limited scale of the time series with noise. And reduce the partial period items in the singular spectrum analysis method to some extent, for example, the seasonal period item and the monthly period item are regarded as the probability of noise rejection, and the modeling accuracy is improved by 26%. Conclusions The purpose is to propose a nonlinear motion modeling method based on wavelet decomposition and singular spectrum analysis, so as to improve the modeling accuracy of coordinate time series.
2021, 46(3): 381-387.
doi: 10.13203/j.whugis20190093
Abstract:
Objectives CHZ-Ⅱgravimeter is the second generation platform gravimeter developed by China independently, for marine and airborne gravimetry. The attitude accuracy of gravimeter stabilized platform affects the measurement accuracy of gravity anomaly directly. The gravity vertical deflection is one error source affecting the horizontal attitude accuracy of the stabilized platform, so it is necessary to study the influence of gravity vertical deflection on the horizontal attitude accuracy of CHZ-Ⅱgravimeter stabilized platform. Methods According to the working principle of the inertial stabilized platform of CHZ-Ⅱ gravimeter, the integrated navigation model containing gravity disturbance of the platform inertial navigation system is established. The observability of the model in static state is analyzed, and the ultimate accuracy of platform horizontal attitude angle is given. Then, the influence of the vertical deflection on the horizontal attitude of the platform in three stages as base point comparison before surveying, operation on survey lines and base point comparison after surveying, is analyzed. The influence of attitude accuracy is discussed, and some valuable suggestions are given on whether to compensate the vertical deviation. Results The horizontal attitude angle accuracy of the platform is affected by the local vertical deviation and the horizontal component of accelerometer bias when comparing base point before survey. And it is decided whether to compensate the vertical deviation according to the direction of gravity disturbance. When comparing base point after survey, or operating on survey lines, the horizontal attitude angle accuracy of the platform is only affected by the vertical deviation of the platform location, and compensating the vertical deflection can improve the horizontal attitude accuracy of the platform. Conclusions When the accelerometer bias cannot be observed, whether to compensate the vertical deflection should be determined according to the direction of the vertical deflection. When the accelerometer can be observed, the horizontal attitude accuracy of the stabilized platform can be improved by the compensation of vertical deflection.
2021, 46(3): 388-394.
doi: 10.13203/j.whugis20190115
Abstract:
Objectives To solve the problem that the coefficient matrix and the observation vector have structured characteristics for many practical applications in the field of surveying and mapping, that is, the coefficient matrix and the observation vector contain fixed quantities (or even fixed columns) and random quantities, and the random quantities at different positions are linearly related. Methods Starting from the errors-in-variables (EIV) function model, the augmented matrix composed of the coefficient matrix and the observation vector is expressed as an affine function form, and the function model is reconstructed by the variable projection method. Then, a structured total least squares (STLS) estimation algorithm is derived by the Lagrange method. Results The example results show that the proposed algorithm is consistent with the existing weighted or structured total least squares estimation algorithms that can solve structured problem in the coefficient matrix and the observation vector. Compared with the weighted total least squares (WTLS) estimation algorithms, the proposed algorithm only needs to establish a positive definite weight matrix of independent random variables and reduces the number of estimates. Compared with other STLS estimation algorithms, the proposed algorithm takes into account the overall structure of the coefficient matrix and the observation vector. Conclusions This shows the effectiveness of the proposed algorithm. The STLS estimation and the WTLS estimation ensure the statistical optimality from the perspective of the function model and the stochastic model, respectively.
2021, 46(3): 395-401.
doi: 10.13203/j.whugis20190271
Abstract:
Objectives The first meteorological satellite for global navigation satellite system (GNSS) radio occultation (RO) observation of China, Fengyun-3C (FY-3C), whose products have been released since June 2014, was launched in 2013. But the references about the application of FY-3C RO data in the study of atmospheric boundary layer height (ABLH) are still not available. Methods Firstly, we derived ABLH values by the wavelet covariance transform (WCT) method, based on FY-3C RO refractive index data. Secondly, the feasibility of the method was verified by representative and statistical comparison with the ABLH inversion results of COSMIC (constellation observing system for meteorology ionosphere and climate) RO refractive index data. Then, we presented the global distribution of FY-3C ABLHs, and made a detailed analysis. Results The heights of steep transitions in the FY-3C RO refractivity index profiles of lower atmosphere, which correspond to the ABLHs, can be derived by using the WCT method with constraints on relative sharpness. The latitudinal differences and land-sea differences in the global distributions of ABLHs basically reflect the relationship between ABLH and climate and topography. Conclusions Because of the low precision and vertical resolution of FY-3C RO products in the lower atmosphere, the success rate for the inversion process is not high on the whole, and the representations on the detailed characteristics of the distribution of ABLH need to be improved.
2021, 46(3): 402-409.
doi: 10.13203/j.whugis20200489
Abstract:
Objectives The spatial optimization and reconstruction of rural settlement is one of the important content of promoting rural revitalization. Through livability and population flow analysis, to scientifically reconstruct rural settlement and optimize spatial allocation. Methods Starting with the basic needs of life, this paper takes Ezhou City as study area, builds a livability evaluation index system and evaluates the livability level of Ezhou City. We construct rural-urban population flow network through network analysis method and find the pattern of rural population flow, and integrate the combined characteristics of livability and the intensity of population flow to reconstruct rural settlement. Results The experimental results show that: (1)Overall, the livability of Ezhou City is relatively high. There is a small gap in survival guarantee function, while there are large gaps in life service function and life improvement function.(2)The population flows according to the priority order of the main urban area, the subordinate towns, and nearby advantageous towns. The radiation range of town is limited, and the existing point-axis structure cannot function well. It is urgent to develop central villages, general villages and basic villages to form a complete rural structure to drive region‐wide development.(3)Based on the livability and the intensity of population flow, rural settlements are divided into the type of relocation and demolition, the type of suburban integration and the type of agglomeration promotion (central village, general village and basic village). Conclusions The results facilitate to reshape the core of rural and complete the rural structure to promote the optimal allocation of resources. This paper will provide a decision-making basis for the reconstruction of rural settlement where population flows rapidly.
2021, 46(3): 410-416.
doi: 10.13203/j.whugis20190273
Abstract:
Objectives The extraction of boundary points and boundary lines is a very important work in land ownership confirmation. The traditional boundary points and boundary lines extraction method first needs to be judged manually, and then the attribute information corresponding to the boundary points and boundary lines is manually input into the attribute table according to the result of judgment. Excessive manual intervention not only makes the work inefficient, but also easy to cause all kinds of errors. Methods In order to solve the above problems, an optimization algorithm for boundary points and boundary lines extraction is proposed. The idea of the algorithm is as follows: (1) Using the modeling tools in ArcGIS to establish a set of data preprocessing model for all parcels, and generate the template files of boundary points and boundary lines through the model; (2) Read some attribute field information of parcel and template file by using GDAL (geographic data abstraction library); (3) Generate and automatically read parcel boundary points and boundary lines file. Results The experimental results show that this method can effectively avoid human intervention and greatly improve the extraction efficiency of boundary points and boundary lines. Conclusions In the actual production, especially in the extraction of large quantities of boundary points and lines, this method has considerable advantages and provides original technical support for similar land monitoring and management in China.
2021, 46(3): 417-426.
doi: 10.13203/j.whugis20190106
Abstract:
Objectives The heterogeneity of urban expansion degree at patch level deeply affects the evolution of urban physical morphology. Studying the factors and mechanisms affecting the degree of urban expansion are conducive to deepening the understanding of the expansion process, facilitating the control of urban spatial expansion and promoting the city's compact and sustainable development. Methods Firstly, we measured the degree of urban expansion of Wuhan City by the proximity expansion index (PEI), and analyzed the spatial distribution characteristics. Secondly, we divided Wuhan City into circles and calculated the expansion degree and speed of each circle, the connection between expansion degree and speed was verified by correlation analysis. Finally, a spatial regression model was constructed to explore the impact of nature, social economy, transportation, and planning on urban expansion degree. Results (1) The degree of urban expansion varied in space, the degree of urban expansion gradually increased from the urban peripheral to the outside. (2) The degree of urban expansion had a positive spatial correlation. (3) There was a strong positive correlation between the degree and the speed of expansion. (4) The traffic location, the control of planning, and the distance to the city center were the main influencing factors of the degree of urban expansion, and the influence degrees decreased in sequence. Conclusions The degree of urban expansion was not disorganized in spatial distribution, but was affected by some factors such as traffic location, planning, and closely related to the speed of expansion. Analyzing the influencing factors of urban expansion degree can provide useful suggestions for urban space management and control.
2021, 46(3): 427-433.
doi: 10.13203/j.whugis20200002
Abstract:
Objectives The visualization of cyberspace information is of great significance to reveal the rules and promote the cognition of cyberspace. Visualizing the nodes and their topological relationships in cyberspace without preprocessing often result in a large number of point coincidences and line crossings. Although the visualization result can be optimized by the node layout algorithms, the divided edge bundling technologies, the backbone extraction technologies and the methods of multi-scale representation of network routing, the spatial characteristic information of these nodes as cyberspace point cluster features cannot be maintained on a micro level of network structure. Therefore, by analyzing and quantifying various types of characteristic information of point cluster features in cyberspace from four aspects of statistical information, metric information, topology information and thematic information, two generalization methods are proposed. Methods (1) An aggregation method based on hierarchical clustering. First, organize the point cluster features into a hierarchical tree of which every final node community is in an appropriate and well-balanced size through multi-layer K-means clustering according to their topology information. Then aggregate these features by their community.(2)A selection method based on node importance measuring. After measuring the comprehensive importance of the each feature from the aspects of maintaining the structural stability and its service coverage area, select the more important ones and delete the relatively unimportant considering the whole network topology. Results A series of generalization experiments at different spatial scales were performed on the point cluster features incyberspace of an area in a central part of China through these two methods of aggregation and selection. The result shows that these methods can realize the automatic generalization of the point cluster features in cyberspace at different spatial scales while maintaining the spatial characteristics of these features. Conclusions The purpose is to provide an effective data processing method of quantitatively expressing the characteristics of cyberspace and accelerating the process of optimizing visualization results.
2021, 46(3): 434-441.
doi: 10.13203/j.whugis20190055
Abstract:
Objectives Constructing meaningful correspondence between two or more models is a very important basic research work. Regards the calculation issue of the correspondence between the partial 3D isometric shape and full shape, a new method for constructing the correspondence among shapes by computing 3D shape feature descriptors with partial functional map and localized manifold harmonics (LMH) operators is proposed. Methods Firstly, the LMH operator is generated by the spectral decomposition from the improved Laplace and the feature descriptor of the shape is calculated. Secondly, the initial correspondence between the partial shape and the full shape is constructed by the partial functional map theory. Then the dense correspondence between the partial shape and the full shape is iteratively calculated. Finally, the correspondence can be optimized by the greedy algorithm till convergence. Results Compared with the existing algorithms in TOSCA dataset, the feature descriptors constructed by the LMH operator used in this paper better reflects the intrinsic properties of some shapes than the feature descriptors constructed by Laplace-Beltrami operators, and the calculated correspondences between full and partial shapes (some with holes) are more accurate as well. Conclusions The new operator generated by the local manifold harmonics and the sparse correspondence calculated by the partial functional map method can be used to construct a more accurate dense correspondence and therefore it can reduce the isometric error to some extent.
2021, 46(3): 442-450.
doi: 10.13203/j.whugis20190136
Abstract:
Objectives According to general landslide susceptibility evaluation methods, landslide condition factors cannot be effectively selected. Methods The prediction model of landslide susceptibility index (LSI) is constructed by multiple adaptive regression spline (MARS), and the landslide susceptibility condition factors are automatically selected, and the landslide susceptibility map is produced by 15 landslide susceptibility factors. In addition, the accuracy of the model is compared between logistic regression (LR) and MARS. Results The results show that the accuracy of landslide susceptibility model constructed by MARS is better than LR. The accuracy of MARS success curve is 0.945 4, and the accuracy of MARS prediction rate curve is 0.923 8. At the same time, the model also selects the important influencing factors of landslide (elevation, slope angle, rainfall, distance to faults, NDVI, plan curvature, geological petrofabric). Conclusions Research suggests that the MARS is an effective method for landslide prediction in study area and can provide decision support for reducing nature disaster.
Articles online first have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
Display Method:
, Available online ,
doi: 10.13203/j.whugis20200221
Abstract:
The development of ICT (Information and Communications Technology) provides new challeng⁃ es and opportunities for modern cartography. Totally different from the traditional cartography in the fields of the research methods and themes, modern cartography trends to digital cyberspace from paper map, and cartographic theories are urged to be improved. However, the understanding of the theories about carto⁃ graphic virtual space have great differences within the professional domain, and the internal contradictions and transboundary invasion make map gradually become an appurtenance of Internet products. To learning from certain domains to analyse and handle them, challenges have prompted cartographic scholars to ex⁃ plore new fields. The development of "digits and culture" has pushed the game to the forefront of hightech. Games are often geographically significant, and maps of game are a combination of ICT and maps. Based on the cyberspace in game map with instances as the research subject, the paper explores the charac⁃ teristics and essence of game map and its implications to the real physical world by the dimensionalities, in⁃ teractivity, narrativity, exploration and cultural dissemination of game maps to discover the extension of cartography, which would replenish and perfect modern cartographic theory and promote its development.
The development of ICT (Information and Communications Technology) provides new challeng⁃ es and opportunities for modern cartography. Totally different from the traditional cartography in the fields of the research methods and themes, modern cartography trends to digital cyberspace from paper map, and cartographic theories are urged to be improved. However, the understanding of the theories about carto⁃ graphic virtual space have great differences within the professional domain, and the internal contradictions and transboundary invasion make map gradually become an appurtenance of Internet products. To learning from certain domains to analyse and handle them, challenges have prompted cartographic scholars to ex⁃ plore new fields. The development of "digits and culture" has pushed the game to the forefront of hightech. Games are often geographically significant, and maps of game are a combination of ICT and maps. Based on the cyberspace in game map with instances as the research subject, the paper explores the charac⁃ teristics and essence of game map and its implications to the real physical world by the dimensionalities, in⁃ teractivity, narrativity, exploration and cultural dissemination of game maps to discover the extension of cartography, which would replenish and perfect modern cartographic theory and promote its development.
, Available online ,
doi: 10.13203/j.whugis20200172
Abstract:
Aiming at the mixed observation data of multiple distribution forms, a P-model distributed mixed model is established. Considering that the mixed number in the model belongs to incomplete data, the EM algorithm is introduced to estimate the parameters of the mixed model and the P-model mixed model parameters are derived in detail The estimated iteration formula and the corresponding iteration steps are given. Finally, the mixed Gaussian distribution data, Laplacian distribution and Gaussian distribution mixed data, and the residual data of measured GPS observations are used to verify the correctness and adaptability of the formula in this paper. The results of the calculation examples show that, compared with the single probability distribution, the P-parameter hybrid model can accurately reflect the actual situation of the data distribution, and the model parameters estimated by the EM algorithm have higher accuracy.
Aiming at the mixed observation data of multiple distribution forms, a P-model distributed mixed model is established. Considering that the mixed number in the model belongs to incomplete data, the EM algorithm is introduced to estimate the parameters of the mixed model and the P-model mixed model parameters are derived in detail The estimated iteration formula and the corresponding iteration steps are given. Finally, the mixed Gaussian distribution data, Laplacian distribution and Gaussian distribution mixed data, and the residual data of measured GPS observations are used to verify the correctness and adaptability of the formula in this paper. The results of the calculation examples show that, compared with the single probability distribution, the P-parameter hybrid model can accurately reflect the actual situation of the data distribution, and the model parameters estimated by the EM algorithm have higher accuracy.
Articles just accepted have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
Display Method:
, Available online ,
doi: 10.13203/j.whugis20200098
Abstract:
Unmanned Aerial Vehicle; Antarctic Expedition; Climate Change; Photogrammetry; Glaciology; Ecology; Geomorphology
Unmanned Aerial Vehicle; Antarctic Expedition; Climate Change; Photogrammetry; Glaciology; Ecology; Geomorphology
Author Login
Review Login
Editor Login
Reader Login
Editorial Login
Editor-in-Chief Login
Start in 1957 Monthly
ISSN 1671-8860
CN 42-1676/TN
中国中文核心期刊
中国科技核心期刊
Ei核心期刊
Special Recommend
- All visit:
- Today's visit:
