Fuzzy Difference Operators for Spatial Change Detection in 2D Spatial Scene

The technological progress in the field of artificial intelligence (AI) has brought new opportunities and challenges to the intelligent development and innovative research in fuzzy spatial relations, fuzzy theory is the basic theory of intelligent information processing, and the paper gives a brief analysis of fuzzy calculation method in spatial analysis and spatial relation calculation. In particular, the spatial relations of fuzzy objects are more difficult to express and describe accurately. This paper proposes a method to calculate the topological relations between fuzzy objects with 4-Intersection model and 9-Intersection model, in the analysis of spatial relations, the extension from deterministic entity to uncertain entity is realized with fuzzy set theory, the fuzzy space matrix is constructed, then fuzzy topological relations and fuzzy membership are calculated and output, the model simplifies many complex relations, and it can describe eight topological relations including disjoint, meet, overlap, covers, contains, covered-by, inside and equal. In practical application, the position of spatial objects can be controlled and adjusted according to topological relations. Through analysis of algorithm and fuzzy membership calculation, the model is effective in theory.

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.

Spatial modeling is one of the most important parts in the area of spatial relations, and it is necessary to develop a new model with high practicality. Firstly this paper analyzes the characteristics and defects of present models; secondly introduces in detail the construction method of quadtree histogram; thirdly cloud model are used to judge spatial directional relation. The experimental results show that the model is feasible. Computer vision is concerned with automatic extraction of useful information from images. The description for human space perception is an important task of the computer vision research. The description of spatial relation is a basic ability of human cognition, it is an important basic task for computer audio-visual information processing to build automatically the description of spatial relation between objects in the image. Spatial relation is mainly constituted of directional relation, topological relation and distance relation. The fundamental theories of topology relation and distance relation are comparatively perfect, but the fundamental theories of directional relation have not any unified standard. There are three main approaches for assessing the basic directional relation. The first one is based on cone model (1) which assimilates an object to the centroid, but it doesn't take into account shape, size and distance information. The second one is based on projection model such as minimum bounding rectangles (2), and directional relation matrix (3), etc., but these models assimilate an object to the minimum bounding rectangle, so shape, size and distance information also can't be taken into account. The third one is based on angle-histogram model (4). Given an object of target A and a reference object B, the angle-histogram is computed from the angles between any two points in both objects and normalized by the maximum frequency. This histogram represents the directional relations of the object A with respect to the reference object B. This model has taken into account shape, size and distance information. But this model has high computational complexity, so it is not practical. Numerous studies are based on this notion of angle-histogram, e.g., (5-8). In (5-7), R-histogram, R*-histogram and F-histogram are proposed, and they can reduce the computational complexity. In (8), a quadtree histogram model of spatial directional relation is proposed, and it can get high accuracy and small computational complexity together.

The spatial relations usually consist of topological, directional and measurement relations. It is not accurate to using single spatial relation to describe spatial scene. Double projections and interior-division matrix model in 3D space is proposed by dividing the reference object within interior rectangle box. The expression of direction relations is combined with interior, boundary and exterior direction relations. 11 transforming rules are proposed by the constraint between directional and topological relationships. Finally, the model is evaluated by Roop K.Goyal’s five required properties and the result shows the satisfaction.

Current study is focused on the GIS based spatial analysis of the land cover changes in the Sumava National Park, Czech Republic. The presentation includes overview of the environmental and biogeographical settings of the Sumava National Park and gives detailed technical description of the workflow (GIS part): remote sensing data capture, pre-processing, algorithm processing, image classification and spatial analysis. The research has been technically done using Quantum GIS (QGIS). Methodologically, current research highlighted technical questions of remote sensing data processing, mapping and classification by means of QGIS. Research steps included: 1. collecting, organizing and sorting data; 2. studying, reading and analyzing relevant literature; 3. develop a GIS project and methodology for spatio-temporal analysis of the land cover types and mapping change detection; 4. mapping data land cover types for 1991 and 2009. Spatial and temporal analysis of the Landsat TM scenes taken at 1991 and 2009 was used for detecting changes in the land cover types. Classification of the images was used to analyze changes in the SNP area that consist in different geobotanical land cover types. The results of image processing demonstrate that structure, shape and configuration of landscapes in SNP changed since 1991.

For qualitative spatial reasoning, there are various dimensions of objects. A considerable amount of effort has been devoted to 2D representation and analysis of spatial relations. Here we present an exposition for 3D objects. There are three types of binary relations between pairs of objects: topological connectivity, cardinal directions, and distance relations. The combinations of these relations can provide additional useful knowledge. The spatial databases include data and the spatial relations to facilitate end-user spatial querying, it also is important to associate natural language with these relations. Some work has been done in this regard for line-region and region-region topological relations in 2D, and very recent work has initiated the association between natural language, topology, and metrics for 3D objects. However, prior efforts have lacked rigorous analysis, expressive power, and completeness of the associated metrics. Herein we present a detailed study of new metrics required to bridge the gap between topological connectivity and size information for integrating reasoning in spatial databases. The complete set of metrics that we present should be useful for a variety of applications dealing with 3D objects including regions with vague boundaries.

Assessing spatial dynamics of a Pinus nigra subsp. salzmannii natural stand combining point and polygon patterns analysis

AN ASSESSMENT OF SPATIAL VARIATION OF LAND SURFACE CHARACTERISTICS OF MINNA, NIGER STATE NIGERIA FOR SUSTAINABLE URBANIZATION USING GEOSPATIAL TECHNIQUES

This article presents a spatial contrast-enhanced image object-based change detection approach (SICA) to identify changed areas using shape differences between bi-temporal high-resolution satellite images. Each image was segmented and intrinsic image objects were extracted from their hierarchic candidates by the proposed image object detection approach (IODA). Then, the dominant image object (DIO) presentation was labelled from the results of optimal segmentation. Comparing the form and the distribution of bi-temporal DIOs by using the raster overlay function, ground objects were recognized as being spatially changed where the corresponding image objects were detected as merged or split into geometric shapes. The result of typical spectrum-based change detection between two images was enhanced by using changed spatial information of image objects. The result showed that the change detection accuracies of the pixels with both attribute and shape changes were improved from 84% to 94% for the strong attribute pixel, and from 36% to 81% for the weak attribute pixel in study area. The proposed approach worked well on high-resolution satellite coastal images.

ABSTRACTHow do children allocate visual attention to scenes as they prepare to describe them multimodally in speech and co‐speech gesture? In an eye‐tracking study, Turkish‐speaking 8‐year‐old children viewed four‐picture displays depicting the same two objects in different spatial relations as they prepared to describe target pictures depicting left‐right relations. Children's visual attention was sustained on the target picture when they were planning descriptions that expressed the spatial relation multimodally in speech and gesture, but not unimodally in speech only. This pattern persisted regardless of the semantic relation between speech and gesture (i.e., for both complementary gestures that disambiguated speech and redundant gestures that supplemented already unambiguous speech). Importantly, visual attention patterns did not differ across description types while children were previewing the displays before message preparation. These results indicate that multimodal message preparation might place different demands on visual attention than unimodal message preparation, possibly due to the affordances of gestures for expressing spatial relations.SummaryWe test the idea that the way children attend to spatial relations prior to communication is related to how they end up describing them.Children's attention was sustained on spatial scenes when they were planning multimodal spatial descriptions in speech and gesture, but not unimodal descriptions in speech only.Planning multimodal descriptions was associated with sustained attention on the spatial scenes regardless of the semantic relation between speech and gesture.

We tested detection of changes to eye position, eye color (brightness), mouth position, and mouth color in frontal views of faces. Two faces were presented sequentially for 555 ms each, with a blank screen of 120 ms separating the two. Faces were presented either both upright or both inverted. Measures of detection (d') were calculated for several different degrees of change for each of the four dimensions of change. We first compared results to an earlier experiment that used an oddity design, in which subjects indicated which of three simultaneously viewed and otherwise identical faces had been altered on one of these four dimensions. Subjects in both of these experiments were partially cued, in that they knew the four possible types of changes that could occur on a given trial. The change-detection results correlated well with the oddity data. They confirmed that face inversion had little effect upon detection of changes in eye color, a moderate effect upon detection of eye-position or mouth-color changes, and caused a drastic reduction in the detection of mouth-position changes. An experiment in which uncued and fully cued subjects were compared showed that cueing significantly improved detection of feature color changes, but there was little difference between upright and inverted faces. Full cueing eliminated all effects of inversion. Compared to partial cueing, changes in mouth color were poorly detected by uncued subjects. Last, a change in the frequency of the base (unaltered) face in an experiment from 75% to 40% showed that increased short-term familiarity decreased the detection of eye changes and increased the detection of mouth changes, regardless of face orientation and the type of change made (color or position). We conclude that uncued subjects encode the spatial relations of features more than the colors of features, that mouth color in particular is not considered a relevant dimension for encoding, and that familiarization redistributes attention from more to less salient facial regions. Inversion effects are not simply an exaggeration of the salience effects revealed by withdrawing cueing, but represent an interaction of spatial encoding with salience, in that the greatest inversion effects occur for spatial shifts in less salient facial regions, and can be eliminated through the use of focused attention.

A concept of fuzzy three-dimensional Voronoi Diagram is presented for spatial relations analysis of real world three-dimensional geographical data, where it is an extension of well known two-dimensional Voronoi Diagram to three-dimensional representation with uncertain spatial relation information in terms of fuzzy set. It makes possible to analyze quantitatively complex boundaries of geographically intricate areas, to give human friendly fuzzy explanation of determining three-dimensional directions, and to express uncertain spatial relations by precise unified fuzzy description. It is applied to decide spatial direction relations of artificial geographicalmountain data, which includes 8 spatial directions with at most 60 relative direction relations, and it leads to detect threedimensional directions whereas the expression of traditional 4 directions and 12 relative directions indicate two-dimensional directions only. The proposed concept aims to discriminate neighbors’ class relations and spatial-temporal changes of specially appointed objects, and also aims to be a tool to achieve the intellective extraction and analysis of geographical data of a mountainous area located in northeast China.

Research on qualitative spatial reasoning has produced a variety of calculi for reasoning about orientation or direction relations. Such qualitative abstractions are very helpful for agent control and communication between robots and humans. Conceptual neighborhood has been introduced as a means of describing possible changes of spatial relations which e.g. allows action planning at a high level of abstraction. We discuss how the concrete neighborhood structure depends on application-specific parameters and derive corresponding neighborhood structures for the $\mathcal{OPRA}_m$ calculus. We demonstrate that conceptual neighborhoods allow resolution of conflicting information by model-based relaxation of spatial constraints. In addition, we address the problem of automatically deriving neighborhood structures and show how this can be achieved if the relations of a calculus can be modeled in another calculus for which the neighborhood structure is known.

Statistics is a branch of mathematics concerned with the collection, quantification, analysis, interpretation, and presentation of real-world data, and the use of probability theory to estimate population parameters with these data. Spatial statistics is a subset of statistics that is concerned with handling the special problems associated with geographically distributed data, which include spatial point patterns, regional and lattice measurement aggregations, irregularly spaced site-specific measurements on a surface, and image analysis. Meanwhile, econometrics is concerned with the application of statistical methods to the study of economic data and problems. When coining the term spatial econometrics in 1979, Paelinck and Klaassen characterized it as a subset of econometrics that is concerned with the role of spatial dependence in regional economic model response and explanatory variables, asymmetries in spatial relationships, the specification of geographic structure governing spatial interactions, and the explicit modeling of space. We outline and discuss principal similarities (e.g., testing for the presence of spatial autocorrelation) and differences (e.g., map generalization) between spatial statistics and spatial econometrics. In doing so, our goal is to help clarify past, present, and future relationships between these two subfields.

Unsupervised spatial self-similarity difference-based change detection method for multi-source heterogeneous images