Complex Spatial Objects Research Articles

CONTEXTS.py (CS.py): A supervised contextual post-classification method to access multiple dimensions of complex geospatial objects

The qualitative dimensions of visible features in space can be captured by connecting spatial configurations arranged in a variety of different ways to diverse conceptual spaces. By conceptual spaces, we intend mental concepts describing specific spatial configurations present in a geographical area, defined by the contextual relationships among their constitutive elements.This paper presents a new supervised post-classification method allowing the extraction of semantically complex spatial objects from a single image of the Earth as, for instance, diverse conceptual spaces referring to multiple dimensions of land use (temporal, cultural, social, etc.).Computationally, our method is operationalised by CONTEXTS.py (CS.py), a plugin written in Python for QGIS. CS.py relies on training areas, defined by the user at diverse scales, to identify and extract in the input image conceptual spaces whose spatial contexts have the same spatial features present in the training areas.Applied to a case study on the island of Sicily, where millennial land use dynamics have resulted in a mosaic landscape, CS.py could detect from an orthophoto diverse conceptual spaces of land use in an area ordinarily classified as one land cover, thus expanding the capabilities of geospatial analysis to reach additional qualitative dimensions of information from image data.•CS.py simplifies a supervised contextual post-classification routine in an easy-to-use, practical and accessible QGIS plugin;•CS.py joins a family of tools for supervised object-based classification (e.g. OTB, GRASS), providing, additionally, the possibility to include contextual information as spatial criteria to train the classification routine.•CS.py has broad applications in different disciplines investigating landscape from quantitative and qualitative perspectives, allowing both, as in multiple environments.

EXPERIMENTING TIN DATA STRUCTURE FOR REPRESENTING PLANE SURFACE AND SUBSURFACE SPATIAL OBJECTS - PRELIMINARY WORK

Abstract. Understanding and analyzing complex spatial objects involves the integration of surface, terrain, and subsurface data into 3D spatial models. However, describing and efficiently analyzing the connections between these data model is particularly challenging. This study aims to generate TIN data structure that enable the 3D representation of surface terrain subsurface integration. Furthermore, to ensure accurate representation within a unified 3D model, spatial relationships between the TIN data model could be obtained. Consequently, three – dimensional Triangular Irregular Networks (3D TIN) mesh of spatial objects representations and indexing structures were created. The integration of spatial objects, encompassing surface, terrain, and subsurface elements, is realized through a unified model. This synergy is achieved by combining the distinct 2D and 3D topology structures of each component. The resulting comprehensive model captures the intricate relationships and interactions within the spatial environment. This study provides additional insight into the representation and analysis of surface, terrain, and subsurface management in 3D spatial models. Hence, better decision making, resource management, underground utility installations, and evaluation of spatial objects will be made possible in our future work.

Improving the Efficiency of the EMS-Based Smart City: A Novel Distributed Framework for Spatial Data

The smart city system, which is a type of enterprise management system (EMS), automatically manages cities and schedules resources efficiently based on spatial data generated by devices, such as the Internet of Things and mobile. However, with the increasing deployment of technologies, including sensor and location-based services, their ever-growing spatial data are no longer managed efficiently by traditional EMS. To overcome this issue, we present SeFrame, which is a <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</u> patially <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</u> nabled <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">frame</u> work for improving the efficiency of smart city EMS based on a distributed architecture. The framework supports a set of spatial queries, including: The range query, k-nearest neighbors query, and spatial join query. It benefits greatly from using the buffer-enabled partition method to eliminate duplicate results. In each partition, the local index based on combination of the quad-tree and grid index (CQG) significantly improves the spatial query efficiency in memory. CQG manages complex spatial objects, including a point, polygon, and polyline. By taking full advantage of the local index, SeFrame accesses skewed spatial data in constant time. In experiments, we demonstrated that the proposed method delivered superior performance in terms of scalability and query efficiency, in most cases.

A Systematic Review of Spatial Approximations in Spatial Database Systems

Many applications rely on spatial information retrieval, which involves costly computational geometric algorithms to process spatial queries. Spatial approximations simplify the geometric shape of complex spatial objects, allowing faster spatial queries at the expense of result accuracy. In this sense, spatial approximations have been employed to efficiently reduce the number of objects under consideration, followed by a refinement step to restore accuracy. For instance, spatial index structures employ spatial approximations to organize spatial objects in hierarchical structures (e.g., the R-tree). It leads to the interest in studying how spatial approximations can be efficiently employed to improve spatial query processing. This article presents a systematic review on this topic. We gather relevant studies by performing a search string on several digital libraries. We further expand the studies under consideration by employing a single iteration of the snowballing approach, where we track the reference list of selected papers. As a result, we provide an overview and comparison of existing approaches that propose, evaluate, or make use of spatial approximations to optimize the performance of spatial queries. The spatial approximations mentioned by the approaches are also summarized. Further, we characterize the approaches and discuss some future trends.

Visual Parameter Selection for Spatial Blind Source Separation.

Analysis of spatial multivariate data, i.e., measurements at irregularly‐spaced locations, is a challenging topic in visualization and statistics alike. Such data are inteGral to many domains, e.g., indicators of valuable minerals are measured for mine prospecting. Popular analysis methods, like PCA, often by design do not account for the spatial nature of the data. Thus they, together with their spatial variants, must be employed very carefully. Clearly, it is preferable to use methods that were specifically designed for such data, like spatial blind source separation (SBSS). However, SBSS requires two tuning parameters, which are themselves complex spatial objects. Setting these parameters involves navigating two large and interdependent parameter spaces, while also taking into account prior knowledge of the physical reality represented by the data. To support analysts in this process, we developed a visual analytics prototype. We evaluated it with experts in visualization, SBSS, and geochemistry. Our evaluations show that our interactive prototype allows to define complex and realistic parameter settings efficiently, which was so far impractical. Settings identified by a non‐expert led to remarkable and surprising insights for a domain expert. Therefore, this paper presents important first steps to enable the use of a promising analysis method for spatial multivariate data.

Mining evolutions of complex spatial objects using a single-attributed Directed Acyclic Graph

Directed acyclic graphs (DAGs) are used in many domains ranging from computer science to bioinformatics, including industry and geoscience. They enable to model complex evolutions where spatial objects (e.g., soil erosion) may move, (dis)appear, merge or split. We study a new graph-based representation, called attributed DAG (a-DAG). It enables to capture interactions between objects as well as information on objects (e.g., characteristics or events). In this paper, we focus on pattern mining in such data. Our patterns, called weighted paths, offer a good trade-off between expressiveness and complexity. Frequency and compactness constraints are used to filter out uninteresting patterns. These constraints lead to an exact condensed representation (without loss of information) in the single-graph setting. A depth-first search strategy and an optimized data structure are proposed to achieve the efficiency of weighted path discovery. It does a progressive extension of patterns based on database projections. Relevance, scalability and genericity are illustrated by means of qualitative and quantitative results when mining various real and synthetic datasets. In particular, we show how such an approach can be used to monitor soil erosion using remote sensing and geographical information system (GIS) data.

Virtual and mixed reality in the study of the geometry of the crystal lattice

The article considers the possibility of using virtual and mixed reality in studying the geometry of the crystal lattice in the framework of the course of solid state physics. The application of mixed and virtual reality technologies in the study of various branches of physics is receiving more and more attention. Virtual reality headsets were used in practical and laboratory classes, where students had to create crystal structures and carry out modeling of various processes. When studying complex spatial objects of crystallography, virtual reality technology allowed students to familiarize themselves with the object of study in more detail, understand the structure of crystals and, accordingly, complete the task in a timely manner. At the same time, the prolonged use of virtual reality headsets led to rapid fatigue of students.

Representing spatial objects in data warehouses: a logical solution

Spatial data warehouse logical design involves mainly extending the techniques used in relational logical data warehouse design for the support of spatial objects, i.e., geometric objects in space. Spatial objects can have different geometric granularities and can be found at different hierarchical levels of a dimension in the logical model of a data warehouse. This paper addresses data warehouse logical design considerations for a consolidated representation of spatial and non-spatial data. The novelty of the model presented in this paper is the representation of spatial objects in a logical and semantically effective manner. With this approach, complex spatial objects can be modelled in a generic and user-friendly format. The model also includes ROLAP operations supporting the navigation across different dimensions' levels and the execution of queries. The functionality of the model is also provided by a number of example queries.

Shape similarity measurement model for holed polygons based on position graphs and Fourier descriptors

ABSTRACTIn geographic information retrieval and spatial data mining, similarity is used to resolve shape matching and clustering. Many approaches have been developed to calculate similarity between simple geometric shapes. However, complex spatial objects are common in spatial database systems, spatial query languages and Geographic Information Science (GIS) applications. With holed polygons, many similarity measurement approaches are restricted to address the relationships between holes or between the holes and the entire complex geometric shape. A successful method should remove the restrictions due to these complex relations and retain invariant during geometric translation (rotation, moving and scaling). To overcome these deficiencies, we utilize position graphs to describe the distribution of holes in complex geometric shapes by storing invariants, such as angles and distances. In addition, Fourier descriptors and the position graph-based method are used to measure the similarity between holed polygons. Experiments show that the proposed method takes into account the relationships in an entire complex geometric shape. It can effectively calculate the similarity of holed polygons, even if they contain different numbers of holes.

世界初の糊付けまで可能な折紙ロボットの開発

Creating complex spatial objects from a flat sheet of material using origami-folding techniques has attracted attention in science and engineering. It is extremely difficult to introduce highly versatile automation using machines to handle deformable objects such as a flat sheet of paper. This work proposes two machines for paper manipulations based on Lego NXT technology that use feedback error learning (FEL) with holographic neural networks (HNN) to perform precise and smooth manipulations of the paper. The first machine makes simple zigzag folding and the second machine glues the generated zigzag folded paper to generate complex 3D shapes. A new spring-back compensation algorithm is proposed to deal with paper's thickness increase after multiples folding and the change in gluing positions due to the paper spring-back phenomenon. The results demonstrate that proposed compensation approximates the generated motion trajectories to real paper fluctuations in the machines. Examples of round shapes and honeycomb patterns are shown.

Indexing Fuzzy Spatiotemporal Data for Efficient Querying: A Meteorological Application

Spatiotemporal data, in particular fuzzy and complex spatial objects representing geographic entities and relations, is a topic of great importance in geographic information systems and environmental data management systems. For database researchers, modeling and designing a database of fuzzy spatiotemporal data and querying such a database efficiently have been challenging issues due to complex spatial features and uncertainty involved. This paper presents an integrated approach to modeling, indexing, and efficiently querying spatiotemporal data related to fuzzy spatial and complex objects and spatial relations. As our case study, we design and implement a meteorological database application that involves fuzzy spatial and complex objects, and a spatiotemporal index structure, and supports various types of spatial queries including fuzzy spatiotemporal queries. Our implementation is based on an intelligent database system architecture that combines a fuzzy object-oriented database with a fuzzy knowledge base.

Unraveling metamaterial properties in zigzag-base folded sheets.

Creating complex spatial objects from a flat sheet of material using origami folding techniques has attracted attention in science and engineering. In the present work, we use the geometric properties of partially folded zigzag strips to better describe the kinematics of known zigzag/herringbone-base folded sheet metamaterials such as Miura-ori. Inspired by the kinematics of a one-degree of freedom zigzag strip, we introduce a class of cellular folded mechanical metamaterials comprising different scales of zigzag strips. This class of patterns combines origami folding techniques with kirigami. Using analytical and numerical models, we study the key mechanical properties of the folded materials. We show that our class of patterns, by expanding on the design space of Miura-ori, is appropriate for a wide range of applications from mechanical metamaterials to deployable structures at small and large scales. We further show that, depending on the geometry, these materials exhibit either negative or positive in-plane Poisson's ratios. By introducing a class of zigzag-base materials in the current study, we unify the concept of in-plane Poisson's ratio for similar materials in the literature and extend it to the class of zigzag-base folded sheet materials.

Vascular hippocampal plasticity after aerobic exercise in older adults.

Aerobic exercise in young adults can induce vascular plasticity in the hippocampus, a critical region for recall and recognition memory. In a mechanistic proof-of-concept intervention over 3 months, we investigated whether healthy older adults (60-77 years) also show such plasticity. Regional cerebral blood flow (rCBF) and volume (rCBV) were measured with gadolinium-based perfusion imaging (3 Tesla magnetic resonance image (MRI)). Hippocampal volumes were assessed by high-resolution 7 Tesla MRI. Fitness improvement correlated with changes in hippocampal perfusion and hippocampal head volume. Perfusion tended to increase in younger, but to decrease in older individuals. The changes in fitness, hippocampal perfusion and volume were positively related to changes in recognition memory and early recall for complex spatial objects. Path analyses indicated that fitness-related changes in complex object recognition were modulated by hippocampal perfusion. These findings indicate a preserved capacity of the aging human hippocampus for functionally relevant vascular plasticity, which decreases with progressing age.

GEOGRAPHIC OBJECTS: THEORY OR TECHNOLOGY DRIVEN?

Abstract. This article aims to compare the geo-graphic (spatial) objects in 2D (planar objects) proposed by CON.G.O.O. and ISO standards, and the ability of a number of GIS software to handle them. The results achieved so far showed that the actual technical possibilities are not always sufficient to support the complex spatial objects proposed by CON.G.O.O.

Provably correct and complete transaction rules for updating 3D city models

The shapes of our cities change very frequently. These changes have to be reflected in data sets representing urban objects. However, it must be assured that frequent updates do not affect geometric-topological consistency. This important aspect of spatial data quality guarantees essential assumptions on which users and applications of 3D city models rely: viz. that objects do not intersect, overlap or penetrate mutually, or completely cover one another. This raises the question how to guarantee that geometric-topological consistency is preserved when data sets are updated. Hence, there is a certain risk that plans and decisions which are based on these data sets are erroneous and that the tremendous efforts spent for data acquisition and updates become vain. In this paper, we solve this problem by presenting efficient transaction rules for updating 3D city models. These rules guarantee that geometric-topological consistency is preserved (Safety) and allow for the generation of arbitrary consistent 3D city models (Completeness). Safety as well as completeness is proven with mathematical rigor, guaranteeing the reliability of our method. Our method is applicable to 3D city models, which define--besides the terrain surface--complex spatial objects like buildings with rooms and storeys as interior structures, as well as bridges and tunnels. Those objects are represented as aggregations of solids, and their surfaces are complex from a topology point of view. 3D GIS models like CityGML, which are widely used to represent cities, provide the means to define semantics, geometry and topology, but do not address the problem of maintaining consistency. Hence, our approach complements CityGML.

Modeling and querying fuzzy spatiotemporal databases

Modeling spatiotemporal data, in particular fuzzy and complex spatial objects representing geographic entities and relations, is a topic of great importance in geographic information systems, computer vision, environmental data management systems, etc. Because of complex requirements, it is challenging to represent spatiotemporal data and its features in databases and to effectively query them. This article presents a new approach to model and query the spatiotemporal data of fuzzy spatial and complex objects and/or spatial relations. In our case study, we use a meteorological database application in an intelligent database architecture, which combines an object-oriented database with a knowledgebase for modeling and querying spatiotemporal objects.

Topological relationships between complex spatial objects

For a long time topological relationships between spatial objects have been a focus of research in a number of disciplines like artificial intelligence, cognitive science, linguistics, robotics, and spatial reasoning. Especially as predicates they support the design of suitable query languages for spatial data retrieval and analysis in spatial databases and geographical information systems (GIS). Unfortunately, they have so far only been defined for and applicable to simplified abstractions of spatial objects like single points, continuous lines, and simple regions. With the introduction of complex spatial data types an issue arises regarding the design, definition, and number of topological relationships operating on these complex types. This article closes this gap and first introduces definitions of general and versatile spatial data types for complex points , complex lines , and complex regions . Based on the well known 9-intersection model, it then determines the complete sets of mutually exclusive topological relationships for all type combinations. Completeness and mutual exclusion are shown by a proof technique called proof-by-constraint-and-drawing . Due to the resulting large numbers of predicates and the difficulty of handling them, the user is provided with the concepts of topological cluster predicates and topological predicate groups , which permit one to reduce the number of predicates to be dealt with in a user-defined and/or application-specific manner.

Constructive Volume Geometry

We present an algebraic framework, called Constructive Volume Geometryn (CVG), for modelling complex spatial objects using combinational operations. By utilising scalar fields as fundamental building blocks, CVG provides high‐level algebraic representations of objects that are defined mathematically or built upon sampled or simulated datasets. It models amorphous phenomena as well as solid objects, and describes the interior as well as the exterior of objects. We also describe a hierarchical representation scheme for CVG, and a direct rendering method with a new approach for consistent sampling. The work has demonstrated the feasibility of combining a variety of graphics data types in a coherent modelling scheme.

Analysis of two-step index structure for complex spatial objects

Abstract An efficient index structure for complex spatial objects is one of the most challenging requirements in non-traditional applications such as geographic information systems (GISs), computer-aided design (CAD), and multimedia databases. In this paper we first propose an extension of an existing index structure called the two-step index structure (TSIS). The TSIS integrates two index structures, one for original objects and the other for their decomposed components. Then, we present a cost model that predicts the performance of the TSIS. In contrast to several earlier investigations on this subject which only considered the filter step, we take into account the performance of the refinement step. Experimental results show that the cost model is accurate, the relative error being below 15%. The performance of our index structure is compared with that of a state-of-the-art index structure by experimental measurements. Our index structure outperforms the state-of-the-art index structure due to its ability to reduce a large amount of storage.

A raster-based method for computing Voronoi diagrams of spatial objects using dynamic distance transformation

The Voronoi diagram has been suggested as an appropriate model for the description of relations between spatial objects (Gold 1992) and it is the only possible solution (which is currently available) to dynamic (measurement-based) GIS (Wright and Goodchild 1997). A Voronoi diagram can be computed either in vector mode or in raster mode. Most existing methods are vector-based. However, vector-based methods are complex for line sets and area sets. To overcome this serious deficiency, attempts have also been made to use rasterbased methods. This paper describes a raster-based method for computing Voronoi diagrams of spatial objects (including points, line and areas) using dynamic distance transformation achieved by the dilation operator in mathematical morphology. Furthermore, an extension is presented to accommodate complex spatial objects.