Similarity measuring of spatial topological relations is the important part of similarity measuring of spatial data, and also is the basic and key technology of spatial data retrieval and spatial scene query. Its meaning is to measure the similarity of topological relationships between multiple data entities in different sources, different sources scales of the same region. Common topological relations have been abstracted into nine topological predications. Current researches mainly focus on the topological relations similarity measuring between two simple entities, but mostly do not involve topological relations similarity measuring for the entire data sets, as well as the complex line targets. In this paper we present a method of measuring simple topological relations based on 9- intersection matrix, that is, the distance between two 9- intersection matrixes as the simple topological relations distance to measure the differences between two simple topological relations, so that we can get a simple topological relations similarity. Then considering the quantity similarity and dimension similarity between entity sets, we can get the simple topological relations similarity measuring model between entity sets. In this paper we establish a similarity measuring model of complex topological predication by using the strategy of decomposing- combination based on the simple topological relations similarity measuring model. Firstly, the complex topology relationship is broken down into a number of local topological relationships. Then through a combination of local topological relations similarity, we get the complex topology relationship similarity measuring model. At last, the method is used to measure similarity of different scales and different sources data. Experimental results show that the selection of cartographic generalization impact the topological relations similarity between entity sets mostly, and other factors with smaller impacts to the experimental data in this article. Experimental results also demonstrate that the topological relations similarity can be used to measure the changing degree of topological relations caused by the cartographic generalization.
In recent years, how to implement a efficient storage management on massive geo-spatial data and ulteriorly web service for a broad variety of users, has becomes an increasingly hot issue in the field of geographical information science, with the explosive growth of Earth Observation System(EOS) data and the flourish of the new geography paradigm. A cloud storage system to provide distributed cloud-enabled storage management and services for massive geo-spatial data with an integrity of both vector and raster formats is proposed in this paper in the light of their intrinsic differences. Based on three-tier layer architecture, we put forward its implementation strategy and method of cloud storage management for raster and vector data respectively based on NoSQL database system, followed by a universal data access interface. The novel technolgies, which include distribute graph database-Neo4J and parralel graph compute framework on massive vector data storage and process were introduced. In our research, using the distributed file system-HDFS and the column family database-HBase as a container to store massive raster data with a distributed space index technique, and the distributed graph database system-Neo4J is used to store massive vector data in view of the constraints of ACID with a R-tree space index. Under the unified framework of Geographical Knowledge Cloud platform GeoKSCloud developed by our research group as a successor of GeoKSCloud, its core components — spatial data aggregation centre (GeoDAC) software has been in shape with aim to provide some distributed spatial data storage management and access services for all types of end users. A tesbed is established with serveral 5 physical nodes and accordingly 7 virtual nodes with different areas and operational systems. We carried out an elaborate comparison between GeoDAC and open source GIS software — PostGIS to validate vector data reading & writing performance. The preliminary results indicated that, although GeoDAC has no accelerated write performance than PostGIS, but it gains significant powerful reading or spatial query performance than PostGIS. Inside GeoDAC, space-partitioned massive data is distributed on the cluster and spatial query operation is implemented in parallel, consequently an enhanced rate of spatial query is gained. The achieved techniques and system in our work will provide a variety of users a powerful tool for further in-depth processing and owns a broad application prospects.
Address geocoding is a kind of address matching method based on spatial technique. It is the process of transforming a description of a location, such as coordinates, the address or the name of a place, to a location on the earth’s surface. Address geocoding technologies started late in China, many cities just start capturing the geo coding address data. Many topics need to be explored, such as address code structure and geo coding data management. The authors analyzed the current address geocoding rules. The street is regarded as the same level distinct restriction as the courtyard in the current strardards. At this point they think that the spatial characters of the street are weakened. On the basis of relevant national standards, they put forward the definition amendment of city standard address geocoding. In the amendment, as distinct restriction, street becomes independent and is in front of courtyard. Thus, an entity must belong to one street and the address code must contain the street’s code. Usually it is difficult to do address matching with many types of address data because the address data store in different database tables by the entity types. Using streets as spatial reference system, according to the street onward direction, they well integrate the doorplates, address points and parcels together and put forward the new unified street geocoding model: street address chain model. In this model, geocoding is not simple address string matching any more, it also makes well use of the streets’direction, parcels’adjacency and other spatial characters to assist address geocoding process. This can provide model support for future address matching. The example about street address chain model of address geocoding is given. Predictably, this new address geocoding model will improve the match rate and accuracy greatly.
There is a decline in the quality of the original carrier when watermarking is embedded using the traditional technology. It can not meet the requirement of high-precision occasion and under the circumstance when original carrier data can not be tampered. Because the technology of reversible watermarking can completely recover the data of original vector map, it is highly suitable for the copyright protection with the high-precision requirement, for instance, military maps and maps provide evidence for the court. At present, the researches of reversible watermarking algorithm for image field become more mature, while the current reversible watermarking algorithm for vector map mainly refers to the relevant methods of the image field, having not fully considered the organization characteristic of the vector data, so the robustness is not strong. Aimed at the above issue, this paper carries out relevant researches on the algorithm of reversible watermarking of vector map. Based on the invariance of the basic spatial relationship of the points in vector map before and after conventional map operation, a robust reversible watermarking algorithm of vector map is introduced to resolve the problem. Firstly, Douglas- Poiker algorithm is used to classify the points of each feature into characteristic points and none characteristic points. Then the angle, constituted by the lines of each none characteristic point and two adjacent characteristic points, is computed by this algorithm. Finally, the watermarking bit is mapped by the angle and the water information is embedded into none characteristic point by modulating the angle mentioned above. The experiment shows that the watermarking using this paper’s algorithm not only has the transparency and reversibility of the general reversible watermarking, but also has good robustness to normal attacks, for instance, rotating, zooming, translating, feature ordering, graphic carving, data compressing, and graphic simplification, etc.
Oceanic front is a narrow transitional zone that the penetration of sea is obviously different between two or more waters there, and it plays an important role in the national production, national defense, marine and weather. Based on the modified theory of universal gravity, sea surface temperature (SST) data near the Kuroshio front are used for front detection. The theory of universal gravity assumes that each image pixel is a celestial body with a mass represented by its value. According to the law of universal gravity, the forces of the pixels in the 3 × 3 neighbourhood exerted on the central pixels can be calculated. Because fronts are susceptible to the noise and intense of fronts are commonly low, a modified method are proposed to solve these problems in this article. This method firstly eliminates the pixels that values equal to 0. Then in order to decrease the reliance on the brightness level of original data, a normalization step is applied to each 3×3 neighbourhood and next based on image enhancement function, each normalized 3×3 area can be enhanced. Finally, the theory of universal gravity is applied to enhanced data for front detection. The algorithm was tested and compared with conventional methods using in the fronts detection such as Sobel, Jensen-Shannon. The results show that compared to conventional methods in some areas, the proposed algorithm can decrease noise while not cause fronts discontinuous.
With the fast development of GIS technology and improvement of the GIS application technology, higher requirements have been put forward to the spatial database connectivity and accessibility. This study first proposes a comparative analysis on cross-sectoral large-scale shared connection to spatial database, thus to point out the hard-to-achieve synchronization updating during different data types conversion. Direct data access model cannot be fully compliance with the data type updating. The spatial extension model of the relational database is dissatisfactory in performances as well as professional spatial analysis. The support of Web Service model is insufficient for non-standard spatial data types; the protocols provided by software providers are of great specificity and difficulty to be extended by third parties. Then in this article, the interfaces of heterogeneous databases connectivity are analyzed deeply. Currently there are two categories of interfaces which are the relational database access interfaces and spatial database standard interfaces. Based on the analysis, the article proposes the ‘Opening Geospatial Database Connectivity (OGDC)’interfaces mechanism and specifications to provide a completely new model that a series of standard interfaces provided by several GIS platform software providers is jointly realized by database providers or data providers based on these standard interfaces. Detailed introductions are presented for the OGDC designs, technical features, implementation techniques, and applications. Finally, the feasibility and advantages of these proposed standards and specifications are demonstrated by a prototype using the OGDC from the domestic-developed distributed spatial database software‘BeyonDB’. And the prototype shows that OGDC could perfectly take account of the functionality, the efficiency and the usability of the spatial database connectivity, thus to provide a new application model for the standardized sharing and continual utilizing of the heterogeneous spatial database.
Three-dimensional (3D) visualization of geographical scene is an important technique in Virtual Geographical Environment (VGE) research for a broad variety of complex natural phenomena and geographical processes. Because geographical scenes are in general highly complex, large scale and with strong interactivity features, traditional single computer single-screen display method usually fails to meet the application requirements of user immersion, large field of view, and high-resolution visualization. Multi-screen display technique is an effective way to solve this problem. In the human-computer interaction of 3D geographical scenes visualization, in addition to supporting to control by hand through the input of keyboard, the system also supports automatically roaming along the path designed in advance. The path for automatically roaming is generated by Cardinal interpolation method which have some advantages: setting simply, good shape retention, and roaming smoothly. In this paper, a new synchronous visualization technique and system for time-sequential 3D geographical scenes displaying and roaming is introduced. The system is based on a stand-alone computer with multi-screens, using vegetation cover changes prior to, during and after the soil erosion control in Changting County, Fujian Province as an example. The software architecture, implementation techniques such as scene construction with three viewports, synchronous display and synchronous route roaming with three screens, vector layer symbolization, embedded broadcasting real-world scene pictures of 3D scene are discussed; thread synchronization mechanism is introduced; a 3D geographical scene was constructed to reflect the changes of soil erosion extent at three different time periods by overlaying true color remote sensing satellite images and DEM. This system has been used for showing the achievement of soil erosion control, and the effect sounds good. In addition to providing a strong immersion and big impact environment, the system also features dynamic change, enormous information, and strong expression. It has unique application capability for visualizing dynamic geographical scene. Last, these function modules are integrated in the 3D information system for synthetizing and management of virtual forest landscape (VisForest) which was designed and developed by research group coming from Spatial Information Research Centre of Fujian.
Traditional single computing environment cannot meet the needs of geographic model sharing, because of its limitations on storage, computing resources and program transfer. Distributed geospatial model sharing could avoid those limitations, so distributed sharing architecture of remote sensing inversion models for polar sea ice-ocean parameters is brought forward based on SOA construction and OGC specifications, which can provide the overall framework and the top-level guidance for studying the key technologies of polar sea ice-ocean parameters remote sensing inversion model service composition and constructing specific composition applications. The distributed sharing architecture focuses on the model services. Detail discussion is carried out on model service interface and interoperation problems related to model services. The polar sea ice-ocean param-eters remote sensing inversion model sharing services platform is designed and developed to help implementing polar sea ice-ocean parameters remote sensing inversion model sharing. In this paper, we analyzed the design guidelines of polar sea ice-ocean parameters remote sensing inversion model sharing service platform, and further studied the key technologies involved in the polar sea ice-ocean parameters remote sensing inversion model sharing service platform. The sharing platform is the connector of model and the clients, and can realize the data conversion and function collaborative. With the help of the sharing platform, model developer could only focus on model algorithm, and the sharing platform will take care of building model service, and interacting with model clients. Several models are adapted, including sea ice concentration remote sensing inversion model and polynya morphologic remote sensing inversion model, to demonstrate the advantages of distributed sharing architecture of polar sea ice-ocean parameters remote sensing inversion models.
Maps of different scales contain different contents and have different social and economic functions. The production and database building of these maps are an important and difficult part of GIS database building. In the past, maps of small scales could be obtained mainly through stepped generalization of large-scaled maps by using digital map generalizing software, which was characterized by low-efficiency, time-consuming, difficult upgrading and unstandard quality. This paper aims at a research on how to establish spatial topological relationship, build database of maps of fundamental scales, accomplish intelligent generalization of adjacent-scaled maps, nonadjacent-scaled maps and randomly-scaled maps, then automatically establish database of maps of various corresponding scales with high speed, guarantee of timely data updating and maitainance of multi-scaled map database. This method, by making use of the integrity, adaptability, applicability, advanced calculation and extraordinary analyzing ability of GIS database, could overcome the disadvantages of traditional methods, ensure the consistency and real time of the database, meet needs from all professions and of all levels, and facilitate the building of urban DSM and three dimensional real models, having the advantages of low cost, high speed, great accuracy, good applicability and map-providing according to needs. The practice of Xiangtan Digital City Project has proved the feasibility and social value of the GISidMAPR® system proposed by this research.
In the past decades, climate change and human activities accelerated land use/land cover change and then promoted regional environmental changes in the Inner Mongolia Autonomous Region. In this article, we describe spatial and temporal characteristics and analyze driving factors of land use/land cover changes on regional and prefectural scales according to three periods of land use/land cover data, conversion rates, dynamic degree and the converted matrix. The result shows that, there are obvious regional differences and similarities in changes of land use/land cover in the Inner Mongolia Autonomous Region, which affected by topographic factors. (i) From 1980s to 2000, the main changes of land use/land cover are grassland reclamation at plain cultivation areas (94 000 hm2/a) and grassland degradation and desertification at highland steppe areas (72 000 hm2/a), which is owing to climate change, population growth and a series of political and economic macro-policy; (ii)The reclamation of cultivated land had been strongly controlled in plain cultivation areas by the "Grain for Green" policy since 2000, while the tends of grassland degradation and desertification in the banded regions at the northern edge of the plain cultivation areas (11 000 hm2/a) and highland steppe areas (133 000 hm2/a) had been increased, which is affected by the precipitation fluctuations and population growth factors. The result indicates that, plain cultivation areas become more susceptible to national macroeconomic policies, and highland steppe areas become more susceptible to changes of precipitation, which is under big pressure of economic development and population growth. These findings provide a basis for the sustainable use and the scientific management of land resources in the Inner Mongolia Autonomous Region.
