Spatial Topological Relations Research Articles

AN APPROACH TO ALLEVIATE THE FALSE ALARM IN BUILDING CHANGE DETECTION FROM URBAN VHR IMAGE

Building change detection from very-high-resolution (VHR) urban remote sensing image frequently encounter the challenge of serious false alarm caused by different illumination or viewing angles in bi-temporal images. An approach to alleviate the false alarm in urban building change detection is proposed in this paper. Firstly, as shadows casted by urban buildings are of distinct spectral and shape feature, it adopts a supervised object-based classification technique to extract them in this paper. Secondly, on the opposite direction of sunlight illumination, a straight line is drawn along the principal orientation of building in every extracted shadow region. Starting from the straight line and moving toward the sunlight direction, a rectangular area is constructed to cover partial shadow and rooftop of each building. Thirdly, an algebra and geometry invariant based method is used to abstract the spatial topological relationship of the potential unchanged buildings from all central points of the rectangular area. Finally, based on an oriented texture curvature descriptor, an index is established to determine the actual false alarm in building change detection result. The experiment results validate that the proposed method can be used as an effective framework to alleviate the false alarm in building change detection from urban VHR image.

A Spatial-Constraint-Based Feature Point Matching Algorithm for the Positioning of Multiple IC Instances

With the development of integrated circuit (IC) chips, the semiconductor industry has begun using many ultrathin chips. To prevent cracking when they are picked up by the machinery, the precise pose of every chip must be provided using the image matching approach. Traditional feature point matching methods are robust to the pose changes of a single chip, but they are not effective for positioning multiple IC instances in one image. To solve this problem, a novel spatial-constraint-based feature point matching algorithm that uses both local information and the spatial topological relationship between feature points to divide the feature points among different IC instances is proposed. Various experiments using images captured of RFID chip pick-up equipment demonstrate that our algorithm results in correct positioning for multiple IC chips; is robust to translation, rotation, scaling, shearing and perspective transformation; and is not sensitive to occlusion and clutter. This algorithm may have many applications in the field of IC manufacturing and packaging.

Point cloud simplification with preserved edge based on normal vector

This paper presents a point cloud simplification algorithm with preserved edge based on normal vector. Because edge points have more distinct features than non-edge points, these special points should always be preserved in the point cloud simplification process. The proposed algorithm establishes the spatial topology relationship for each point using octree first, then identifies and retains edge points using a simple but effective method. For non-edge points, delete the least important points until user-specified data reduction ratio is reached. The importance of a non-edge point is measured using the average of the Euclidean distances (based on normal vector) from the point to estimated tangent plane at its each neighborhood point. The experimental results on three test point cloud data sets and two practical data sets of our own demonstrate that the proposed algorithm performs much better compared with other methods.

Effective Management of High Rate Spatio-Temporal Queries in Wireless Sensor Networks

Handling high rate queries have always posed a challenge in wireless sensor networks (WSNs) owing to their resource constrained nature. This paper proposes a scheme that performs centralized and distributed optimization to improve the scalability of the high rate spatio-temporal queries in WSNs. Queries are optimized centrally based on multiple criteria such as spatial topological relationships, temporal and attribute correlations. An energy efficient load balanced clustered tree routing based on minimum bounding rectangle spatial indexing scheme is employed to aid the in-network optimization of queries. Two algorithms have been proposed to carry out a centralized and distributed optimization that works adaptively on queries switching between optimal and sub-optimal modes to handle multiple concurrent queries reliably. Simulation results show that the proposed scheme is highly scalable for large scale spatio-temporal queries and also has the added advantage of minimizing the energy consumption due to query and data transmission.

Research on Topology Association Rules Algorithm Based on Spatial Constraints

Spatial topological relation is an important and typical multilayer spatial relation, when Apriori is used to mining spatial constraint topology association rules, it will has some repeated computing. And so this paper proposes an algorithm of spatial constraint topology association rules mining based on complement set, which is used to mining spatial multilayer transverse association rules with constraint condition from spatial database. This algorithm generates candidate frequent topological itemsets with constraint condition not only by down-top search strategy as Apriori, but also by computing complement set of candidate from down-top search strategy, which is suitable for mining any spatial topological frequent itemsets with constraint condition. This algorithm compresses a kind of spatial topological relation to form an integer. By the way, firstly, the algorithm may efficiently reduce some storage space when creating mining database. Secondly, the algorithm is fast to obtain topological relation between two spatial objects, namely, it may easily compute support of candidate frequent itemsets. Finally, the algorithm may fast generate candidate via double search strategy, i.e. one is that it connects (k+1)-candidate frequent itemsets with constraint condition of k-frequent itemsets as down-top search strategy, the other is that it computes complement set of (k+1)-candidate frequent itemsets with constraint condition. The result of experiment indicates that the algorithm is able to extract spatial multilayer transverse association rules with constraint condition from spatial database via efficient data store, and it is very efficient to extract any frequent topology association rules with constraint condition.

On the identification and establishment of topological spatial relations by autonomous systems

Human beings use spatial relations to describe many daily tasks in their language. For a mobile robot to be useful in daily life, it is necessary to have navigation algorithms capable of identifying and establishing spatial relations. To date in robotics, the navigation problem has been thoroughly researched as a task of guiding a robot from one spatial coordinate to another. Therefore, there is a difference in degree of abstraction between the language of human beings and the algorithms used in robot navigation. This article introduces a piece of research performed on the use of topological relations for the formalisation of spatial relations and navigation. So far, topological relations have been applied widely in geographical information systems and also in spatial logics. There are some proposals in robot navigation which use them for planning but there is no research about making decision in robot navigation. Our research focuses on decision-making methods to establish spatial relations. The main result is a new heuristic, called the Heuristic of Topological Qualitative Semantics (HTQS), which allows the identification and establishment of spatial relations decision-making from a set of actions. To demonstrate its effectiveness, HTQS has been implemented in the form of agents that can move in a two-dimensional virtual environment. HTQS opens a new door to designing algorithms for navigation based on the identification and establishment of spatial relations.

Spatial Topological Relationship for Remote Sensing Image Analysis

For remote sensing imagery, spatial relationships are extracted by segmentation and classification. Unlike traditional vector relationships, spatial relationship reasoning is equivalent to constraint satisfaction problems in the image process. Based on 9-intersect model, the paper discuss spatial topological relationship between image objects to provide a theoretical and technical support for low levels of image segmentation, high-level analysis.

Spatial Topological Relationship for Remote Sensing Image Analysis

For remote sensing imagery, spatial relationships are extracted by segmentation and classification. Unlike traditional vector relationships, spatial relationship reasoning is equivalent to constraint satisfaction problems in the image process. Based on 9-intersect model, the paper discuss spatial topological relationship between image objects to provide a theoretical and technical support for low levels of image segmentation, high-level analysis.

The Only Way Is Up? Ordinary Topologies of Ramallah

AbstractThis article seeks to conceptualize and value some of the quotidian geographies responsible for contemporary forms of urban change. The starting point for the argument is an attempt to account for recent urban change in the Palestinian city of Ramallah, particularly the proliferation of apartment buildings, using emerging work on verticality. It is argued that work on verticality focuses empirically on prominent cities and spaces of violent conflict, invokes the vertical as politically suspect and offers a theorization of space that is topographical in nature. Consequently, accounts of verticality have produced narratives that obscure topological spatial relations. This article seeks to make space for such topologies, which it is argued are crucial to producing urban and political life itself in many contexts. The concept of ordinary topologies is proposed as a means of attending to the complex and undervalued practices that are thought to be normal (but not static) and common within and across intensive or qualitative spatio‐temporal relations. This approach is fleshed out through a discussion of changing topographic–topological landscapes in Ramallah. In particular, it is argued that the increasingly verticalized landscape of the city, embodied in rapidly proliferating apartment buildings, must be understood in relation to frequent journeys to other places and changing family relations.

Research on Vector Spatial Data Storage Schema Based on Hadoop Platform

Cloud computing technology is changing the mode of the spatial information industry which is applied and provides new ideas for it. Since Hadoop platform provides easy expansion, high performance, high fault tolerance and other advantages, we propose a novel vector spatial data storage schema based on it to solve the problems on how to use cloud computing technology to directly manage spatial data and present data topological relations. Firstly, vector spatial data storage schema is designed based on column-oriented storage structures and key/value mapping to express spatial topological relations. Secondly, we design middleware and merge with vector spatial data storage schema in order to directly store spatial data and present geospatial data access refinement schemes based on GeoTools toolkit. Thirdly, we verify the middleware and the data storage schema through Hadoop cluster experiments. Comprehensive experiments demonstrate that our proposal is efficient and applicable to directly storing large-scale vector spatial data and timely express spatial topological relations.

Boundary Points De-Noising and Simplification Based on Spatial Connectivity

A de-noising and simplification approach based on spatial connectivity is proposed which is applied to deal with the boundary points of point cloud. First, grid method is used to represent the spatial topology relationship of the scattered point cloud and calculate the k-nearest neighbors for each data point. Then boundary points are extracted according to uniform distribution of point cloud. And next, an algorithm for boundary points simplification of point cloud is presented to further simplify boundary points. Consequently, not only the details characteristics are reserved well, but also the boundary points are simplified. The experimental result shows that the proposed approach can not only reserve characteristics of both details and boundaries but also realize de-noising and simplification of point cloud.

A grid-based spatial data model for the simulation and analysis of individual behaviours in micro-spatial environments

As crowd simulation in micro-spatial environment is more widely applied in urban planning and management, the construction of an appropriate spatial data model that supports such applications becomes essential. To address the requirements necessary to building a model of crowd simulation and people–place relationship analysis in micro-spatial environments, the concept of the grid as a basic unit of people–place data association is presented in this article. Subsequently, a grid-based spatial data model is developed for modelling spatial data using Geographic Information System (GIS). The application of the model for crowd simulations in indoor and outdoor spatial environments is described. There are four advantages of this model: first, both the geometrical characteristics of geographic entities and behaviour characteristics of individuals within micro-spatial environments are involved; second, the object-oriented model and spatial topological relationships are fused; third, the integrated expression of indoor and outdoor environments can be realised; and fourth, crowd simulation models, such as Multi-agent System (MAS) and Cellular Automata (CA), can be further fused for intelligent simulation and the analysis of individual behaviours. Lastly, this article presents an experimental implementation of the data model, individual behaviours are simulated and analysed to illustrate the potential of the proposed model.

Gas monitoring data anomaly identification based on spatio-temporal correlativity analysis

Based on spatio-temporal correlativity analysis method, the automatic identification techniques for data anomaly monitoring of coal mining working face gas are presented. The asynchronous correlative characteristics of gas migration in working face airflow direction are qualitatively analyzed. The calculation method of asynchronous correlation delay step and the prediction and inversion formulas of gas concentration changing with time and space after gas emission in the air return roadway are provided. By calculating one hundred and fifty groups of gas sensors data series from a coal mine which have the theoretical correlativity, the correlative coefficient values range of eight kinds of data anomaly is obtained. Then the gas monitoring data anomaly identification algorithm based on spatio-temporal correlativity analysis is accordingly presented. In order to improve the efficiency of analysis, the gas sensors code rules which can express the spatial topological relations are suggested. The experiments indicate that methods presented in this article can effectively compensate the defects of methods based on a single gas sensor monitoring data.

Land Use Patch Generalization Based on Semantic Priority

Land use patch generalization is the key technology to achieve multiscale representation. We research patches and achieve the following. (1) We establish a neighborhood analysis model by taking semantic similarity between features as the prerequisite and accounting for spatial topological relationships, retrieve the most neighboring patches of a feature using the model for data combination, and thus guarantee the area of various land types in patch combination. (2) We establish patch features using nodes at the intersection of separate feature buffers to fill the bridge area to achieve feature aggregation and effectively control nonbridge area deformation during feature aggregation. (3) We simplify the narrow zones by dividing them from the adjacent feature buffer area and then amalgamating them into the surrounding features. This effectively deletes narrow features and meets the area requirements, better generalizes land use features, and guarantees simple and attractive maps with appropriate loads. (4) We simplify the feature sidelines using the Douglas-Peucker algorithm to effectively eliminate nodes having little impact on overall shapes and characteristics. Here, we discuss the model and algorithm process in detail and provide experimental results of the actual data.

Similarity Measuring of Spatial Topological Relations Based on Topological Predication

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.

Research on Identification of Comprehensive Pipeline Headroom in Certain Area

The comprehensive pipeline is a kind of important facilities and equipment and the key to normal operation in metro station, and the certain design requirement of various pipelines’ headroom in specific spatial region need to be met. As a technology centralized upon information and based on three-dimensional mode, BIM technology can express three-dimensional model of metro comprehensive pipeline imaginatively, provide the spatial topological relations among pipelines and relevant detecting calculations. In this paper, the necessity of identification of headroom of metro comprehensive pipeline is deeply analyzed, and then the article designs identification algorithms of headroom of metro comprehensive pipeline according to BIM technology. This algorithm can detect the pipelines which not meet the design requirements of headroom on BIM platform efficiently, thus we can improve design efficiency and quality and liberate labors so that designers can be engaged in more complex design work

Topological spatial relations for active visual search

If robots are to assume their long anticipated place by humanity’s side and be of help to us in our partially structured environments, we believe that adopting human-like cognitive patterns will be valuable. Such environments are the products of human preferences, activity and thought; they are imbued with semantic meaning. In this paper we investigate qualitative spatial relations with the aim of both perceiving those semantics, and of using semantics to perceive. More specifically, in this paper we introduce general perceptual measures for two common topological spatial relations, “on” and “in”, that allow a robot to evaluate object configurations, possible or actual, in terms of those relations. We also show how these spatial relations can be used as a way of guiding visual object search. We do this by providing a principled approach for indirect search in which the robot can make use of known or assumed spatial relations between objects, significantly increasing the efficiency of search by first looking for an intermediate object that is easier to find. We explain our design, implementation and experimental setup and provide extensive experimental results to back up our thesis.

Region level annotation by fuzzy based contextual cueing label propagation

This paper investigates the challenging issue of assigning given image-level annotations to precise regions on images. We propose a novel label to region assignment (LRA) technique called Fuzzy-based Contextual-cueing Label Propagation (FCLP) with four parts: First, an image is over-segmented into a set of atomic patches and the local visual information of color features and texture features are extracted. Second, fuzzy representation and fuzzy logic are used to model spatial invariants of contextual cueing information, especially for the imprecise position information and ambiguous spatial topological relationships. Third, labels are propagated inter images and intra images in visual space and in contextual cueing space. Finally, the fuzzy C-means clustering based on K-nearest neighbor (KNN-FCM) is utilized to segment the images into semantic regions and associate with corresponding annotations. Experiments on two public datasets demonstrate the effectiveness of the proposed technique.

A spatial topological routing solution for emergency responding in 3D subway area

With the fast expanding of cities, people spend more time on travelling among complex built–up areas such as large subway station. When the emergency event appears, people need a routing method that provides the optimised path fast and a path–finding solution that utilises spatial topological relationship to finish the inner building routing is sounding for this task. The introduced 3D spatial routing solution divides a specific routing problem into several minor routing problems across the related spatial regions to acquire optimised performance. The experiment shows that the spatial relationship introduced into solution increases the speed of the whole route generation significantly, and still maintains a high quality of the path–finding results. In conclusion, the proposed solution has represented a new meaningful approach to apply spatial topological relationship into emergency path–finding solutions for subway areas.

Geospatial technologies and digital geomorphological mapping: Concepts, issues and research

Geomorphological mapping plays an essential role in understanding Earth surface processes, geochronology, natural resources, natural hazards and landscape evolution. It involves the partitioning of the terrain into conceptual spatial entities based upon criteria that include morphology (form), genetics (process), composition and structure, chronology, environmental system associations (land cover, soils, ecology), as well as spatial topological relationships of surface features (landforms). Historically, the power of human visualization was primarily relied upon for analysis, introducing subjectivity and biases with respect to selection of criteria for terrain segmentation and placement of boundaries. This paper reviews new spatio-temporal data and geocomputational approaches that now permit Earth scientists to go far beyond traditional mapping, permitting quantitative characterization of landscape morphology and the integration of varied landscape thematic information. Numerous conceptual, theoretical, and information-technology issues are at the heart of digital geomorphological mapping (DGM), and scientific progress has not kept pace with new and rapidly evolving geospatial technologies. Consequently, new capabilities exist but numerous issues have not been adequately addressed. Therefore, this paper discusses conceptual foundations and illustrates how geomorphometry and mapping approaches can be used to produce geomorphological information related to the land surface and landforms, process rates, process–form relationships, and geomorphic systems.