Internet generates a plenty of texts which contain abundant geographic semantic information, and bring massive opportunities for deep mining and knowledge discovery. Meanwhile, heterogeneous and dynamic web texts make a surge in the number and type of geographic entity's attributes and the complexity of geographic semantic relations, which present a unprecedented challenge to geographic information retrieval, spatial analysis and reasoning, and intelligent location based services. Firstly, we describe the process of extracting geopgraphic informantion from web texts, summarize the research status and major issues which include geographic entity recognition, locating, attribute extraction, relation construction and event extraction. Secondly, we introduce some popular open sources used for geographic information extraction. Lastly, we discuss and look ahead to the development trends of this domain in future.
Modeling spatial relations and their scale changes has been one of the important topics in GIS science. This paper discussed the geometric-based and relational-based representation of geographic information. The first representation aims to store, manage, and analyze geometric data with coordinates, and concentrates on the geometric locations, shapes and distributions of spatial objects, thus it is termed as geometric representation. The latter uses symbols to qualitatively represent, communicate and infer spatial relationships between spatial objects based on people’s cognition and understanding, thus it is termed as relational representation. This paper mainly focused on summarizing the latest progress in theories, methods and applications about the relational representation. First, the above-mentioned two representations were compared and their scale changes were highlighted. It is discovered that the geometric representations of same geographic entities vary at different spatial scales, so do the relational representations vary between geographic entities. This type of changes in relational representations strongly associates with cartographic generalization operators, which affects the changes of shapes, sizes and structures of spatial objects. Second, the influences of the generalization operators, which include shape simplification, merging of areal objects, attribute induction and spatial dimension reduction, on spatial relations were analyzed, and related methods were presented for deriving and modeling the scale changes of topological and directional relations which was caused by the four operators. Third, combined with multi-scale spatial relations, a technological framework for analyzing multi-scale datasets was presented. We also illustrated the concepts and solutions for detecting the consistency of multi-scale data, and tested them practically with case studies to demonstrate their efficiency. Finally, it can be concluded that the generalization operators and modeling methods play important roles in analyzing and understanding multi-scale spatial datasets.
Both direction relationships and metric relationships are important spatial relationships. Independent representation model for direction relationships and metric relationships have appeared in large numbers. However, direction relationships and metric relationships have not been overall considered and the existing composition models have many drawbacks. Therefore, based on improvement of cone shaped direction relationships model and qualitative metric relationships model, an integrated representation model is proposed and the two spatial relationships are studied in a unified framework. To begin with, the direction relationships are classified into eight types by the improvement of cone shaped direction relationships model and the metric relationships are divided into three categories. Eight direction relationships include east, north, west, south, northeast, northwest, southwest and southeast relationships. And three matric relationships, which include near, middle and far matric relationships, are set forth. Then, a 7×7 matrix is used to depict direction relationships and metric relationships in a unified framework, and it is detailed but relatively complex. Moreover, a 3×3 matrix, which replaces the above mentioned 7×7 matrix, is introduced to represent the direction and metric relationships. The range of the element in the matrix is descripted. The number of the matrix is set forth. Because not all the integrated relationships for direction and metric relationships are valid, five rules about the integrated representation model for direction and metric relationships are defined to exclude the invalid matrix. To verify the effectiveness of the integrated model, an example is given to testify the resultant relationships by applying the integrated model. Results show that this integrated representation model can improve the representation effect of the spatial relationships.
Generalized three prism (GTP) is an important 3D spatial data model which is widely used for geological modeling. In recent years, with the development of computer visualization technology, GTP geological model construction method based on drilling data is maturing. However, the research on the 3-D profile cutting algorithm of GTP spatial data model still focuses on the single plane cutting section, and lacks mature algorithms to support the multiple efficient arbitrary plane section of single GTP model. Research on multiple cutting method of GTP model is one of the most important requirements of the 3D geological model applications in practice; at the same time, multiple GTP cutting algorithm can also provide efficient technical support for the spatial operations of GTP model and 3D geometric entities. The current generalized three prism (GTP) cutting algorithms are not suitable for dealing deviate borehole data with dimension reduction method or tetrahedral mesh generating method, and would lead to excessive data redundancy and low algorithm efficiency. In addition, it is unable to realize multiple arbitrary cutting operations, and could not support the more complicated spatial analyses of geological model. This article proposed an improved dynamic tetrahedral mesh generating method to reduce the data redundancy by restructuring the retained polyhedron, which is constructed after cutting operation, based on topological spatial relations. The multiple arbitrary cutting problems were solved and several "plane-body" single cutting operations were combined into a single "body-body" composite cutting operations to realize the 3D geological model space analyses. This paper focused on multiple arbitrary cutting plane section problems of the GTP body based on the analysis of the GTP body element characteristics, proposed a solution which aims to make up the deficiencies of the research on the arbitrary and in multiple cutting plane section of GTP body element in the field of three-dimensional geological modeling. Application examples show that: the above three points could improved GTP cutting operation speed and are able to realize complicated spatial analyses such as space excavation and tunneling simulation more efficiently.
DEM-based generation of high quality contours with properties of convexity, smoothness and flatness has gradually become a key research area for creating contour maps. The existing generation methods have some deficiencies including hardness, intersection and abnormal closure of contours generated in the terrain change areas, such as channels and ridges. In view of the above-mentioned facts, taking a 1:50 000 DEM in the loess hilly region as the test data set, this paper analyzes the basic conditions of reconstruction contours based on densified DEM grid with high quality and efficiency, and examines the accuracy of different interpolation approaches in the process of this reconstruction. Utilizing the comparative analysis, this paper proposes a novel method to generate and represent contours with high quality based on densified DEM grid scheme and terrain shading technique. Experiment results show that: (1) the interpolation approaches include bilinear function, cubic convolution, local quadratic polynomial, and completely regularized spline function. In view of the extreme values, the discrete degree, and the spatial distribution of elevation numerical error, regularized spline function is the optimal interpolation method to reconstruct surface morphology, followed by local quadratic polynomial, cubic convolution, and bilinear interpolation. (2) The contours, which are generated by densified DEM grid via the complete regularized spline function with taking 4×4 DEM grid cells as a search circle, are more accurate and smoother. In the above process, the resolution of densified DEM grid is the actual distance of 0.1mm in the visualized maps. (3) For the terrain with a known generalization scale, there exists an optimal resolution threshold for the DEM. To reproduce the original contours with high quality, the corresponding resolution of DEM cannot be lower than the optimal threshold. (4) The superposition technique between contours and DEM hillshadings attached with a white mask could effectively enhance the three-dimensional effect of contour maps and hence make high quality contour maps incorporating scalability and imaginability.
Fragile watermarking technique has been viewed as an effective method to achieve content authentication, which not only detect any modifications that occurred, but also locate the modified areas. Based on fragile watermarking technology, an accurate authentication scheme based on point constraint block is proposed, which detects the malicious attacks with high accuracy while ensuring to locate exactly the tampered area for vector geographic data. Our innovative strategy is based on point constraint block and uses the spatial relationships between the elements of data points. In the authentication information embedding process, vector geographical data is divided into blocks according to the method of point constraint block, and the spatial positional relationship between the data points of each block is reordered by the "Zig-Zag" pattern, so as to establish an organized positional relationship between data points. Then, for each point, the fragile watermark information is generated by its adjacent point, and is embedded into the current point. In the process of content authentication, the extracted watermark information is compared with the generated watermark information, and the comparative result is used to judge whether the data have been updated. The proposed algorithm is furthermore compared with the method that is based on a uniform block, and the experimental results show that the proposed authentication algorithm can accomplish accurate authentication when the data is updated, and it has the ability to achieve the accurate authentication of deleted elements. Meanwhile, when data modifications are detected, it can locate and mark the modification positions.
Location decision of any logistics distribution center meets multiple constraints, such as the specific spatial environment, the single assignment constraint, the capacity of warehouses and the minimum cost of capital. This paper proposed a model based on refined ant colony algorithm and GIS tools to solve Single Source Capacitated Facility Location Problem (SSCFLP). Firstly, a location selection model was established, which met the target of minimizing the total cost. Secondly, by combining ant colony algorithm and local search, the refined bi-level ant colony optimization to solve the SSCFLP problem was proposed. The solving process was divided into two layers: the layer of choosing facilities and the layer of assigning demands. These two layers were associated with each other. In each iteration, the ants would generate solutions by selecting new sets of facility locations from the candidate sites according to the capacity constraint, and establish the assignment of each customer to a selected facility location using pseudorandom search. The iteration-best solution was optimized and memorized using local search. Then the global optimal solution could be attained through conducting multiple iterations. Finally, a location decision case of the car logistics distribution center in Binhai district was constructed. Site selection space was constructed based on GIS tools, considering demands, candidate sites and shipping cost, and other spatial factors, such as land use, hydrology and terrain. The experimental results revealed that the method was efficient and could find reasonable scheme for determining location and allocation. It had certain academic significance to other similar problems.
Variable-scale visualization technique has been widely applied in the representation of road network data. The main focus of this technology is to highlight the dense central area in a limited map layout with large-scale display method. On the other hand, the marginal and assistant map contents, which are relatively unimportant, will be displayed in small-scale. However, in previous studies, methods using coordinate transformation formula may cause excessive map deformation and spatial conflict among road elements. To solve these problems, a quadratic programming model is proposed to improve the visual effect of variable-scale transformation. In this paper, a line distortion rule based on road grade is constructed. In addition, a spatial conflict constraint rule based on support vector machine is applied to eliminate topological errors of road network. Finally, the road network data in Zengcheng District of Guangzhou city are used to testify the purposed model and the method in this paper. The result shows that this model can dynamically improve the visual effect of variable-scale. Conclusively, this paper provides a new idea to deformation controlling and spatial conflict elimination in the field of variable-scale visualization research.
In Internet era, geospatial web services (GWSs) are the primary approaches to share and interoperate geographical data. After more than ten years of development and the widely adoption on specifications, an increased number of geospatial web services have been published and are available for online public access. To obtain those geographical data, it is necessary to find an effective approach to locate and discover GWSs among massive web resources. Currently, the most widely used methods in practical for GWSs discovering are either based on Google Search API or based on generic web crawler. But the aforementioned approaches have some shortages, such as relatively inefficient search performance, irrelevant results, and low precision on GWS identification. To partially address the above issues, this paper developed a topic crawler to harvest GWSs based on the modified Best First Search strategy. The core of the proposed algorithm is that through combining the topic relevance of the link text and the topic relevance of the webpage text synthetically to predict the crawling priority of the unvisited URL. Then, we can utilize the priority thresholds to filter out the irrelevant URLs and narrow the search range at the same time. Moreover, a capabilities document detecting operation is added to GWSs recognition process to improve the search precision. Finally, we use the most widely adopted GWS specification: Web Map Service (WMS), which is proposed by Open Geospatial Consortium (OGC), as a case study. Two groups of experiments were conducted to compare the proposed method and a generic web crawler. The experimental results verified the feasibility of the proposed algorithm.
The explosion of available Geographic Grid resources in a wide range of Earth Science System application domains is shifting the paradigm of Earth Data Science. To exploit and acquire further insights and knowledge based on archived Geographic Grid resources, the existing infrastructures and techniques need to be scaled up and scaled out. However, adding more nodes does not provide a real analytics capability improvement if it is implemented without a corresponding analytics service interfaces among these nodes. The development of standard-based online analytics services is considered as one of the potential solutions and is becoming indispensable to strengthen mutual integration between Geographic Grid information systems and other information systems. In this study, standard-based Geographic Grid models and analytics operations are reviewed and discussed by considering different web communication protocols, making it possible to explore different modular coupling and application profiling. Based on the probe of OGC Web Coverage Processing Language (WCPS) specifications and relevant Web Coverage Service (WCS) 2.0 core and extension specifications, a web interoperability study is carried out to prototype an interoperable Geographical Grid analytics service. Accordingly, the research concludes the coupling patterns, principle issues and application directions for future explorations on Geographical Grid Analytics web applications. The result shows that the coupling of WCPS and OGC WCS 2.0 can effectively improve the interoperability of Geographical Information Application Infrastructure in terms of Earth Science System monitoring and forecasting, so as to provide an effective support to National Digital Information Infrastructure Initiatives.
Identifying human behavior patterns embedded in massive mobile phone data records is a research hotspot and difficulty of study in geography. While lots of researches are aiming at investigation of the mobility characteristics of mobile phone users, studies focusing on the stay of mobile phone users and their stay patterns are relatively little. The spatio-temporal heterogeneous regularity is vital for understanding the urban human dynamic and optimizing urban system. Therefore, this paper explored the stay patterns of mobile phone users in order to understand the human mobility patterns and their features. According to the spatial and temporal constraints of human routine and travel behavior, this paper defined the stay conditions and the stay patterns of urban mobile phone users, and come up with methods of identifying and extracting stay patterns from massive mobile phone data records. Then, we took about 7.9 million mobile phone users’ one day data records in Shenzhen City in China as an example, processed them with the designed method, and identified some typical stay patterns which covered about 98% of the urban mobile phone users. In addition, we conducted statistical analysis for urban mobile phone users’ stay patterns and analyzed their spatial distribution with respect to different administrative districts combining with the city’s land use pattern. Furthermore, we dissected the heterogeneous characteristics of the spatial distribution of different stay pattern’s users and the stay frequencies against different administrative districts over a 22-hour period. The study shows: (1) 15 types of stay patterns can cover 98% urban mobile phone users’ behavior and their stay locations are no more than 4 in one day. The stay patterns with 2 stay locations shows the highest probability that nearly half of the mobile phone users have this tendency. (2) The spatial distribution of the 15 stay patterns in the city is evidently heterogeneous, which is subjected to the urban land use. We found that the higher proportion of leisure and entertainment land in a certain administrative district, the stay patterns with more stay locations in this region are likely to occur. (3) The heterogeneity of the stay frequency for different urban administrative district is strongly related to its permanent resident population, population density and major function of the district. The study conclusions are useful in understanding the population characteristics of urban phone users’ behavior, the activity patterns and urban residents’ commuting behavior. Moreover, it can provide important references for scientific decisions of urban land use, urban transportation planning and prediction.
The spatio-temporal and multi-dimensional visualization of atmospheric pollution dispersion simulation result can effectively demonstrate the spatial distribution of air pollution dispersion, which could provide an important reference to the quick analysis and effective emergency decision-making.The CALPUFF model can effectively simulate the diffusion process of pollution with respect to changes of time and space.The existing visual expression methods for atmospheric pollution simulations havesome common deficiencies, such as the ineffective integration of geographic information, the missing of important dimension features, etc. In this paper, the authors firstly analyzed both the CALPUFF model and its integration with component GIS, which provides a technical support for the integration of simulation results and geographical information. Secondly, with the support of GIS visualization technology, the preprocessing and vector plotting method for the simulated wind field results from CALPUFF model was given, and the preprocessing and raster rendering method for the simulated density field results from CALPUFF model was also provided. Thirdly, based on the three-dimensional terrain scene, the visualization method for atmospheric pollution dispersion was discussed. The integrated visual expression strategy of the CALPUFF model simulation results and the three-dimensional terrain scenes was then obtained. Finally, we took the Fuzhou City as a study area, and the three-dimensional terrain scenes of Fuzhou was constructed using the component GIS. According to the framework of WPF(Windows Presentation Foundation), the spatial and temporal multi-dimensional visualization simulation of wind fields and density fields was implemented. The experiment result shows that the spatial and temporal multi-dimensional visualization method given in the paper can be effectively integrated with the three-dimensional terrain scenes, and can also simultaneously achieve the processes of dynamic diffusion within the temporal dimension and multi-level distribution within the spatial dimension for the simulation results. The spatial and temporal multi-dimensional visualizations method can provide a good reference to other studies and applications.
Many complicated geographic phenomena such as dam-break flood were complex giant systems, and the dynamic development of their spatiotemporal process is more important than the final formation of the spatial pattern. Therefore, the simulation and analysis of spatiotemporal process and the disaster forecasting warning have become a hot research direction in the field of geographic information science. Meanwhile, with the popularization of Web-GIS technology, the integration of real-time content on web and the visual expression of geographic spatiotemporal process simulation are also demanded by the public urgently. With the rapid development of web service, network technology and their applications in GIS, it is possible to realize the visualization analysis, share and manage distributed spatial data on different clients. After analyzing the latest Web-GIS technology, this paper focuses on the simulation and visual analysis of dam-break flooding spatiotemporal process in the network environment, which can be implemented by applying HTML5, WebGL, Ajax, Web Service technology and other technologies. Some key technologies, which include rapid computing of spatiotemporal process model, B/S network architecture construction, three-dimensional scene rendering optimization, and dynamic interaction analysis, are also discussed in details. Finally, a prototype system was constructed and an experiment of the network simulation and visual analysis of a dam-break flood spatiotemporal process case was conducted on a study region. Experimental results showed that the methods addressed in this paper could successfully publish spatiotemporal process information, conduct online impact analysis and realize the three-dimensional visualization representation under the network environment, which could meet different requirements of browsing, querying and analyzing. It can provide an efficient support to dam-break management and emergency decision-making.
Xihu national nature protection area, the natural barrier of Dunhuang oasis, is located in the west of Hexi Corridor. Due to the climatic change and overdevelopment of land and water resources, the ecological environment problems such as wetland degradation and desertification have become more severe in the recent decades. The area of wetland, interpreted by multi-temporal remote sensing images, has decreased by 42.5%, from 17.2 thousands hm2 to 9.9 thousands hm2 from 1989 to 2013. The wetland evolution has a tendency of fragmentation, with its patch number increasing from 32 to 51 and the mean patch area declining from 537 hm2 to 213 hm2. The centroid of wetland moved southwest for about 11.59 km. It reveals that the wetland has a tendency of slowly moving to the southwest due to the development of Dunhuang city that located in the east of the wetland. The factor analysis is used to classify the driving factors related to wetland evaluation. Lastly, projection pursuit model is developed to analyze the influence of various driving factors on the wetland evaluation. The modeling result simultaneously illustrates that the wetland was in rapidly degenerated state during 23 years of the period between 1980 and 2013. The result also indicates that over-utilization of surface water and groundwater for agricultural land development is the radical reason of wetland degradation. The secondary motivation factors are glacier depletion and runoff decline caused by climatic change. In the 1990s, the wetland could keep a relatively steady state with the agricultural acreage remaining at 27 thousands hm2. Therefore, it is suggested that the scale of land use should be kept at this level, or the use of surface water and groundwater should be reduced to the level in the early 1990s through the applications of saving water, changing crop type, as well as transferring water from nearby basins. The research results could provide considerable supports to wetland protection and the integrated river-basin development planning and management.
Cloud-top height is an important factor in weather forecasting and monitoring. Accurate cloud-top height has important scientific significance for improving the quality of both weather analyses and numerical weather prediction. The geometric method to calculate cloud-top height using stereo image pair obtained from meteorological satellites has been recognized as providing relatively high precision, and has practical importance. However, this method does not fully consider cloud movement and typically assumes ideal ellipsoids in theory. Thus, the calculated cloud-top height still has a relatively large error in practice. In this study, cloud-movement speed was introduced into the collinearity equation of photogrammetry. We established a model to calculate the cloud-top height from the ASTER images (3B and 3N) with digital photogrammetry and remote sensing technology. Firstly, we created a stereo pair from ASTER images obtained on 25th September 2012. Then, the cloud-movement speed was calculated through matching cloud points. Finally, the cloud-top heights with and without consideration of wind speed were both calculated. Compared with ground control points, the model error is determined to be within two pixels (about 30 meter). We further compared our results with MISR products, and found that the cloud-top height determined without using wind speed is consistent with the height obtained from MISR, the difference between them is about 300 meters. Our cloud-top height determined with wind speed considered, however is about 1400 meters higher than that of MISR without wind considered. Marchand and Naud had identified in their research that the cloud-top height obtained from MISR is about 1000 meters lower than Lidar observation. This implies that our results with consideration of wind speed are closer to the Lidar observations. Due to the fact that our method for determining cloud-top height is dependent on the cloud moving speed, and the results with wind speed included have led to a good estimation of cloud-top height, we conclude that the wind speed should be included in algorithms for cloud-top height determination.
The paper is based on the images of Chinese No. 3 Resource Satellite (ZY-3), the first civil high-resolution surveying and mapping satellite. A method combined with object-oriented approach and morphology ideas is developed in this paper, which not only extracted the information of buildings and shadows from the test sites (Fangzhuang Community in Beijing and the software park in Xiamen) successfully, but also estimated the shadow lengths automatically. Morphological Building Index(MBI) and Morphological Shadow Index(MSI) calculated from the merged images are used to extract information from city buildings and shadows. Subsequently, we estimate the building heights based on the lengths of shadows and their geometric relationship with the sun, the satellite and the buildings. Finally, we use field survey data to evaluate the accuracy of extraction and analyze the source of errors. In the example of Fangzhuang Community, the average relative error of the calculated building heights is 7.08%, and more than 80% of the building heights’ relative error is less than 10%. Moreover, 90% of the buildings’ absolute error is less than 6 meters. The relatively large errors mostly occurred on buildings that have low building heights with inconspicuous shadows, and high-rise buildings with overlapped shadows due to the high density of constructions. Meanwhile, the test site in Xiamen showed the reliability and accuracy of the method. 94.3% of the buildings’ absolute error is less than 5 meters, and the correlation coefficient between the actual heights and the estimated heights is around 0.992. Results demonstrate that the proposed method is able to accomplish building extraction and building height estimation effectively from high-resolution images. In addition, the experiment gives a preliminary indication of the Satellite ZY3, about its immense potential in applications on urban information extraction.
As an important land cover type of the Earth’s surface, snowpack has a huge effect on water cycle, climate change, environment and human activities. The snow covers are sensitive in indicating climate change and extreme weather events. Thus, it is significant to map the snowpack’s distribution and study the change trend of its time series. This study is focused on the use of the MODIS, AMSR-E, AMSR2 and MWRI data in winter (from November to March) from 2002 to 2013 to develop a retrieval model of daily snow distribution in Xinjiang. The technical process of establishing this model is divided into the following steps. First, data fusion was employed to handle the Terra and Aqua MODIS snow cover products, reduce the proportion of cloud pixels, and maximize the percentage of snow pixels, because the cloud has more mobility and it can change rapidly during the Terra and Aqua transit time. Second, AMSR-E, AMSR2 and MWRI data were used to retrieve daily snow cover map. Third, the two snow cover products were fused to produce cloud-free snow cover products. Based on the proposed approach, daily snow cover data of the entire Xinjiang were extracted for the winter days from 2002 to 2013. After that, the snow-covered days were extracted from the daily snow cover data using a statistical approach. For example, if a pixel location on the images was identified “snow” in three consecutive days, it was recognized as the type of “snow” and the count of days is “3”; otherwise, it was recognized as “non-snow” type. This algorithm was adopted to avoid mistakes in counting snow-covered days when the pixel location was only covered by snow within a short period that is less than a day. The method complies with the continuity aspect of the “snow cover” definition. The number of days covered with snow was finally retrieved for each pixel location in every winter using this proposed algorithm. The map of the averaged snow-covered days shows that the snow-covered days of Xinjiang have a close relationship with terrain, and the number of the snow-covered days in the mountainous areas is bigger than that in the basin and urban areas. The snow packs were mainly distributed in the northern part of Xinjiang. From November to January, snow-covered days increased because the temperature decreased, while from January to March, the number of the snow-covered days decreased with the rise of temperature. The snow-covered days of Xinjiang reveal some fluctuations from 2002 to 2013. The monthly snow-covered days showed significant correlation with the monthly average temperature and the number of days in a month having temperature lower than 0℃. The snow-covered days have no obvious relationship with snowfall. In recent years, the gravity centre of the snow-covered days in Xinjiang area has a southward and eastward movement trend, which may relate to the global warming. Further studies are needed to explain this issue in future.
