Topological error correcting in GIS

Directional relations, topological relations and metric relations are the basic spatial constraint in the geometric space. The three kinds of spatial relations are not isolated and restrict each other. In this paper, we focus on the effect of topology and distance on the representation of directional relations and present a description mechanism of directional relations considering topology and distance. In this new model, (1)topological constraint is analyzed as the basis of directional relations categories; (2)distance relations is the other factor of representation of directional relations and distinguish the directional relations of different positions in the same ray line; (3)depending on the analysis of the capability of exiting directional relations models to represent the restraint from the topological relations and distance, a category mechanism based on the topological relations and distance is proposed to improve the accuracy of the directional description. This model combines the restraint from topological and distance relations and consummates the representation of directional relations. Experiments show excellent efficiency in view of directional description.

Information about the relative size of spatial regions is often easily accessible and, when combined with other types of spatial information, it can be practically very useful. In this paper we combine a simple framework for reasoning about qualitative size relations with the Region Connection Calculus RCC-8, a widely studied approach for qualitative spatial reasoning with topological relations. Reasoning about RCC-8 relations is NP-hard, but a large maximal tractable subclass of RCC-8 called H8 was identified. Interestingly, any constraint in RCC-8 - H8 can be consistently reduced to a constraint in Ĥ8, when an appropriate size constraint between the spatial regions is supplied. We propose an O(n3) time path-consistency algorithm based on a novel technique for combining RCC-8 constraints and relative size constraints, where n is the number of spatial regions. We prove its correctness and completeness for deciding consistency when the input contains topological constraints in Ĥ8. We also provide results on finding a consistent scenario in O(n3) time both for combined topological and relative size constraints, and for topological constraints alone. This is an O(n 2 ) improvement over the known methodsKeywordsSpatial RegionBasic RelationTopological RelationSpatial ReasoningSize ConstraintThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This paper derives and compares two strategies for minimizing topological constraints in a query expressed by a visual example: (1) elimination of topological relations that are implied uniquely by composition and (2) restriction to topological relations that relate near-neighbor objects, as determined by a Delaunay triangulation. In both cases, the query processing approach is to solve a constraint satisfaction problem over a graph of binary topological relations. Individuals and the combination of the composition- and neighborhood-based strategies were implemented and compared with respect to their ability to reduce topological constraints, and with respect to the quality of the results obtained by a similarity-based searching that uses these pre-processing strategies. The main conclusion of this work is that similarity queries that are formulated in a visual language should exploit the metric characteristics of the configuration, even if only topological constraints are considered for making matches.KeywordsQuery ProcessingDelaunay TriangulationConstraint Satisfaction ProblemSpatial ObjectTopological RelationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Abstract. High-latitude terrestrial ecosystems are key components in the global carbon cycle. The Northern Circumpolar Soil Carbon Database (NCSCD) was developed to quantify stocks of soil organic carbon (SOC) in the northern circumpolar permafrost region (a total area of 18.7 × 106 km2). The NCSCD is a geographical information system (GIS) data set that has been constructed using harmonized regional soil classification maps together with pedon data from the northern permafrost region. Previously, the NCSCD has been used to calculate SOC storage to the reference depths 0–30 cm and 0–100 cm (based on 1778 pedons). It has been shown that soils of the northern circumpolar permafrost region also contain significant quantities of SOC in the 100–300 cm depth range, but there has been no circumpolar compilation of pedon data to quantify this deeper SOC pool and there are no spatially distributed estimates of SOC storage below 100 cm depth in this region. Here we describe the synthesis of an updated pedon data set for SOC storage (kg C m−2) in deep soils of the northern circumpolar permafrost regions, with separate data sets for the 100–200 cm (524 pedons) and 200–300 cm (356 pedons) depth ranges. These pedons have been grouped into the North American and Eurasian sectors and the mean SOC storage for different soil taxa (subdivided into Gelisols including the sub-orders Histels, Turbels, Orthels, permafrost-free Histosols, and permafrost-free mineral soil orders) has been added to the updated NCSCDv2. The updated version of the data set is freely available online in different file formats and spatial resolutions that enable spatially explicit applications in GIS mapping and terrestrial ecosystem models. While this newly compiled data set adds to our knowledge of SOC in the 100–300 cm depth range, it also reveals that large uncertainties remain. Identified data gaps include spatial coverage of deep (> 100 cm) pedons in many regions as well as the spatial extent of areas with thin soils overlying bedrock and the quantity and distribution of massive ground ice. An open access data-portal for the pedon data set and the GIS-data sets is available online at http://bolin.su.se/data/ncscd/. The NCSCDv2 data set has a digital object identifier (doi:10.5879/ECDS/00000002).

A new GRASS GIS fuzzy inference system for massive data analysis

The spatial characteristics and structure of the exhibition display design are summarized through the analysis of the topological relationship of the exhibition display spatial structure, and the RCTG algorithm in IBM technology is applied to extract the above-described exhibition spatial topological relationship. Based on the actual situation of the exhibition design, the structural space constraint relationship is determined, and at the same time, the model API provided by the BIM platform is called to construct the component model based on the topological constraint relationship. Aiming at the problems of large differences in lighting distribution and large differences in color in the process of exhibition display design, we optimize such problems through visual element processing operations and realize visual element configuration from three aspects: color, picture, and white space. A case study of the exhibition designed in this paper is conducted by setting the model parameters. The results present that in the simulation analysis of scene combination optimization when, the entry rate grows to 18vis./min, at this time, the user’s overall exhibition viewing satisfaction reaches the peak, and the optimal limit number of people is 46. In addition, in the lighting analysis of the side interface + top interface of the exhibition, 30% high side windows + 25% decentralized strip skylights (B1+F1) have the highest values of each lighting, the proportion of area with a lighting coefficient of >2% (99.497%), the proportion of area with an illuminance of 400lux (91.571), the average lighting coefficient (7.046), and the uniformity of lighting (0.192). This study verifies the practical feasibility of research on exhibition display design based on topology optimization through experimental analysis.

Comprehensive park management to fulfill the NPS mission requires an accurate inventory of the geologic features of a park unit, but Comprehensive park management to fulfill the NPS mission requires an accurate inventory of the geologic features of a park unit, but park managers may not have the needed information, geologic expertise, or means to complete such an undertaking; therefore, the Geologic Resources Inventory (GRI) provides information and resources to help park managers make decisions for visitor safety, planning and protection of infrastructure, and preservation of natural and cultural resources. Information in the GRI report may also be useful for interpretation. park managers may not have the needed information, geologic expertise, or means to complete such an undertaking; therefore, the Geologic Resources Inventory (GRI) provides information and resources to help park managers make decisions for visitor safety, planning and protection of infrastructure, and preservation of natural and cultural resources. Information in the GRI report may also be useful for interpretation. This report synthesizes discussions from a scoping meeting for Redwood National and State Parks (referred to as the “parks” throughout this report) held in 2004 and a follow-up conference call in 2019. Two GRI–compiled GIS data sets of the geology and geohazards of the parks are the principal deliverables of the GRI. The GRI GIS data are available on the GRI publications website http://go.nps.gov/gripubs and through the NPS Integrated Resource Management Applications (IRMA) portal https://irma.nps.gov/App/Portal/Home. Enter “GRI” as the search text and select a park from the unit list. Writing of this report was based on those data and the interpretations of the source map authors (see “GRI Products” and “Acknowledgements”). A geologic map poster illustrates the geology GRI GIS data set and serves as a primary figure for this GRI report. No poster was prepared for the geohazards GRI GIS data set. Additionally, figure 7 of this report illustrates the locations of the major geologic features in the parks. Unlike the poster, which is divided into a northern and southern portion to show detail while accommodating the parks’ length, figure 7 is a single-page, simplified map. The features labeled on figure 7 are discussed in the “Geologic History, Features, and Processes” chapter. To provide a context of geologic time, this report includes a geologic time scale (see "Geologic History, Features, and Processes"). The parks’ geologic story encompasses 200 million years, starting in the Jurassic Period. Following geologic practice, the time scale is set up like a stratigraphic column, with the oldest units at the bottom and the youngest units at the top. Organized in this manner, the geologic time scale table shows the relative ages of the rock units that underlie the parks and the unconsolidated deposits that lie at the surface. Reading the “Geologic Event” column in the table, from bottom to top, will provide a chronologic order of the parks’ geologic history. The time scale includes only the map units within the parks that also appear on the geologic map poster; that is, map units of the geohazards data are not included. Geology is a complex science with many specialized terms. This report provides definitions of geologic terms at first mention, typically in parentheses following the term. Geologic units in the GRI GIS data are referenced in this report using map unit symbols; for example, map unit KJfrc stands for the Cretaceous (K) and Jurassic (J) Franciscan Complex (f), Redwood Creek schist (rc), which underlies a portion of the Redwood Creek watershed (see “GRI Products”).

Topological integrity constraints control the topological properties of spatial objects and the validity of their topological relationships in spatial databases. These constraints can be specified by using formal languages such as the spatial extension of the Object Constraint Language (OCL). Spatial OCL allows the expression of topological constraints involving crisp spatial objects. However, topological constraints involving spatial objects with vague shapes (e.g., regions with broad boundaries) are not supported by this language. Shape vagueness requires using appropriate topological operators (e.g., strongly Disjoint, fairly Meet) to specify valid relations between these objects; otherwise, the constraints cannot be respected. This paper addresses the problem of the lack of terminology to express topological constraints involving regions with broad boundaries. We propose an extension of Spatial OCL based on a geometric model for objects with vague shapes and an adverbial approach for topological relations between regions with broad boundaries. This extension of Spatial OCL is then tested on an agricultural database.KeywordsObject Constraint LanguageIntegrity ConstraintSpatial ObjectTopological RelationTopological ConstraintThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

India is one of the world's regions that is most vulnerable to natural disasters, which results in yearly in Hyderabad also losses of property, infrastructure, and human lives. Monitoring and evaluating the floods and other disasters can be done from a unique vantage point by using air and space-based observations of the globe. Geospatial technology has significantly enhanced flood research, particularly in the first three phases of floods. Specifically, there are three phases: a) preparation for floods; b) monitoring for floods; and c) recovery from floods (damage assessment and mitigation phase). Agriculture, socioeconomic, communication, population, and infrastructure data are all included in the GIS data set that was developed during the preparation phase. In the event of a serious flood crisis in Hyderabad, this can be utilised in conjunction with the flooding data to adopt an evacuation strategy, rehabilitation planning, and damage assessment.

Geographic Information Systems (GIS) are being applied with increasing frequency, and with increasing sophistication, in international relations and in political science more generally. Their benefits have been impressive: analyses that simply would not have been possible without GIS are now being completed, and the spatial component of international politics—long considered central but rarely incorporated analytically—has been given new emphasis. However, new methods face new challenges, and to apply GIS successfully, two specific issues need to be addressed: measurement validity and selection bias. Both relate to the challenge of conceptualizing nonspatial phenomena with the spatial tools of GIS. Significant measurement error can occur when the concepts that are coded as spatial variables are not, in fact, validly measured by the default data structure of GIS, and selection bias can arise when GIS systematically excludes certain types of units. Because these potential problems are hidden by the technical details of the method, GIS data sets and analyses can sometimes appear to overcome these challenges when, in fact, they fail to do so. Once these issues come to light, however, potential solutions become apparent—including some in existing applications in international relations and in other fields.

This paper examines the strength of relationships between objectively measured broad dimensions of the urban environment, which underlie the structure of the urban environment in South East Queensland, and related subjectively measured evaluations of the urban environment. Data for the objective dimensions were gained from GIS data sets and the Australian population census while data for the subjective evaluations were gained from the 2003 Survey of Quality of Life in South East Queensland. The objective and subjective data were then linked by geocoding the location of residents responding to this survey. Generalised Linear Modelling was used to test the strength of relationships between objective dimensions and subjective evaluations of the urban environment which were found to be weak. Some psychological, social, and residential relocation process explanations are discuss as well as implications for urban quality of life theory and urban planning.

Three-dimensional topological relationships serve as a theoretical foundation for quality control, update processing, and spatial analysis of three-dimensional spatial data in real-world three-dimensional GIS. The existing 3D topological relationship models are all basic relationship models that cannot distinguish the refined topological relationship between the line and the body with multiple intersections. In this study, we develop a 3D refined topological relationship description framework that draws from the two-dimensional refined topological relationship model, defines the unit intersection between the line and the body based on manifold topology, and proposes a method for describing the unit intersections between the line and the body considering Euler numbers and adjacency types. In total, 23 basic types between the line and the body are deduced. An example is provided to illustrate the distinguished refined topological relationship between the line and the body with multiple intersections. Subsequently, an algorithm for determining the basic type of line/body is developed. Finally, a line/body refined topological relationship computation prototype system is developed using the Nef polyhedron model, C++ language, and an open-source geometric algorithm library, and the effectiveness of our method is verified using actual building and pedestrian data.

The integration of the raster data cube alongside another form of geospatial data (e.g., vector data) raises considerable challenges when it comes to managing and representing it using knowledge graphs. Such integration can play an invaluable role in handling the heterogeneity of geospatial data and linking the raster data cube to semantic technology standards. Many recent approaches have been attempted to address this issue, but they often lack robust formal elaboration or solely concentrate on integrating raster data cubes without considering the inclusion of semantic spatial entities along with their spatial relationships. This may constitute a major shortcoming when it comes to performing advanced geospatial queries and semantically enriching geospatial models. In this paper, we propose a framework that can enable such semantic integration and advanced querying of raster data cubes based on the virtual knowledge graph (VKG) paradigm. This framework defines a semantic representation model for raster data cubes that extends the GeoSPARQL ontology. With such a model, we can combine the semantics of raster data cubes with features-based models that involve geometries as well as spatial and topological relationships. This could allow us to formulate spatiotemporal queries using SPARQL in a natural way by using ontological concepts at an appropriate level of abstraction. We propose an implementation of the proposed framework based on a VKG system architecture. In addition, we perform an experimental evaluation to compare our framework with other existing systems in terms of performance and scalability. Finally, we show the potential and the limitations of our implementation and we discuss several possible future works.

Spatiotemporal topological semantic information has attracted a lot of attention recently when exploring high‐level human movement features in geographic contexts. Although topological semantics between a trajectory and individual spatial objects have been studied extensively, few studies have focused on movements in the specific context of spatial infrastructures, such as road networks. This study proposes a topological trajectory model that integrates the topological semantics of trajectory data related to road networks and regions in a unified framework. The proposed model considers key points during a trajectory and establishes a topological intersection model to describe key points’ semantics. With the topological semantics of the trajectory–road network obtained, the road network’s semantic relation is derived directly from the topological relation between road networks and regions. This model can intuitively express the semantic relations of the three elements, trajectory, road network, and region, which helps spatial queries and analyses of network constrained movements. A case study of real traffic data shows that more detailed semantic information can be obtained based on this model.

Information systems designs are increasingly concerned with entity relationships and technical programmatic approaches to solutions architecture as opposed to semantic based, business focused information architecture that places business definitions at the centre of the information system design and implementation. The disconnect between information technology and business is perpetuated by an overly prescriptive information technology technical design method that fails to incorporate qualitative and normative aspects of business, where information is structured and delivered according to business. The paper will discuss various decision support and semantic approaches to information design and delivery and argue that the traditional modes of solution delivery do not include meaning making of the data elements which are essential to business information reporting and analytics. The meaning making aspect identified is linked to data dictionary or business data glossary that allows for the discovery of semantic meaning from the SQL Server. Using Christian Fürber’s methodology on semantic programming, the analytics team developed a semantic model that enabled detailed definition of fields and the discovery of information using semantic search functionality embedded in the SQL Server. The project provided semantic data framework that provided business with the capability for semantic reconciliation and data sets that were further integrated with Tableau visualization and SQL auto processes.