scholarly journals Scoping a Vocabulary for Spatial Relations Properties

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Dalia E. Varanka
Keyword(s):  
English Language ◽  
Environmental Science ◽  
Spatial Relation ◽  
Spatial Relations ◽  
Data Networks ◽  
Physical Processes ◽  
Geographic Space ◽  
Open Geospatial Consortium ◽  
Human Use ◽  
Topographical Mapping

<p><strong>Abstract.</strong> Spatial relations are essential for knowledge representation, yet the scope of a corpus of geospatial terms, such as exists for RDF or OWL, is not yet recognized. A vocabulary of geospatial relations may align with several existing models within RDF and OWL; among which are relation primitives as defined in upper ontology; regional topological relations such as those expressed by the Open Geospatial Consortium (OGC) GeoSPARQL standard; and mereotopologic relations as are researched in related semantic literature. One semantic area that is theorized among linguists, but not well defined within formal logic are verb-preposition combinations. The objective of this study in-progress is to 1. Define a corpus of spatial relation terms, 2. Place such relation classes within a framework of existing semantic axioms, and 3. To identify the types of spatial relation terms that need more research. To understand and enrich the vocabulary of geospatial feature properties for semantic technology, English language spatial relation predicates were analysed in three standard topographic feature glossaries. Five major classes of spatial relation predicates were identified from the analysis. First, part-whole relations are modelled throughout semantic and linked-data networks. The remaining classes are spatially descriptive and geometric relations; physical processes happening in space; human use of geographic space, such as land use; and spatial preposition spatial relations. These categories are commonly found in the ‘real world’ and support environmental science based on digital topographical mapping. The hypothesis is that a broad set of spatial relation expressions, form the basis for expanding the range of possible queries for topographical data and mapping applications.</p>

scholarly journals Goal, source, and route preverbs in Latin: their interaction with spatial datives

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Víctor Acedo-Matellán
Keyword(s):  
Spatial Relation ◽  
Spatial Relations ◽  
Syntactic Analysis ◽  
Dative Case ◽  
Configurational Theory

Abstract Prefixed verbs in Latin may take an argument in the dative case, interpreted as the ground of the spatial relation codified by the preverb. This phenomenon is constrained by the semantics of that spatial relation: while preverbs encoding a location, a goal, or a source of motion generally accept the dative argument, preverbs encoding a route do not. I propose a syntactic analysis of this phenomenon, framed within the Spanning framework. I assume an analysis of the spatial dative as an applied argument interpreted as a possessor of the final location of motion. Developing a configurational theory of spatial relations, I show how only the syntax-semantics of the preverbs interpreted as encoding a location, be this final (a goal), initial (a source), or unrelated to motion (a static location), is compatible with the projection of an Appl(icative)P integrating the dative argument. By the same token, pure route preverbs, involving a path but not a location, are correctly predicted to disallow the projection of ApplP, and hence the spatial dative.

scholarly journals EXPRESSION AND ORGANIZATION OF GEOGRAPHIC SPATIAL RELATIONS BASED ON TOPIC MAPS

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1257-1261
Author(s):  
H. J. Liang ◽  
H. Wang ◽  
T. J. Cui ◽  
J. F. Guo
Keyword(s):  
Information Science ◽  
Spatial Database ◽  
Spatial Relation ◽  
Spatial Relations ◽  
Geographical Information ◽  
Knowledge Network ◽  
Effective Management ◽  
Topic Maps ◽  
Complex Knowledge ◽  
Topic Map

Spatial Relation is one of the important components of Geographical Information Science and Spatial Database. There have been lots of researches on Spatial Relation and many different spatial relations have been proposed. The relationships among these spatial relations such as hierarchy and so on are complex and this brings some difficulties to the applications and teaching of these spatial relations. This paper summaries some common spatial relations, extracts the topic types, association types, resource types of these spatial relations using the technology of Topic Maps, and builds many different relationships among these spatial relations. Finally, this paper utilizes Java and Ontopia to build a topic map among these common spatial relations, forms a complex knowledge network of spatial relations, and realizes the effective management and retrieval of spatial relations.

scholarly journals Peer review declaration

2021 ◽  
Vol 941 (1) ◽  
pp. 011002
Keyword(s):  
Peer Review ◽  
English Language ◽  
Environmental Science ◽  
Reference List ◽  
Scientific Content ◽  
Double Blind ◽  
Content Quality ◽  
Scientific Standards ◽  
Academic Debate

Abstract All papers published in this volume of IOP Conference Series: Earth and Environmental Science have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Double-blind • Conference submission management system: MeisterTask CRM • Number of submissions received: 72 • Number of submissions sent for review: 57 • Number of submissions accepted: 39 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 54% • Average number of reviews per paper: 2 • Total number of reviewers involved: 6 • Any additional info on review process: In general, each article was checked for scientific content, quality of the English language and technical formatting. Reviewers rated the following (5 excellent, 1 poor): Relevance to the themes; Contribution to academic debate; Structure of the paper; Standard of English; Appropriateness of abstract; Appropriateness and number of keywords; Appropriateness of the research/study method; Literature review; Relevance and clarity of drawings, graphs, and tables; Results and findings; Discussion and conclusions; Reference list. In the absence of a scientific component of an article, authors right to revision was rejected. In other cases, correction notes were sent to authors. • Contact person for queries: Anastasia Kulachinskaya, [email protected]

The Integrative Nature of Geography

2019 ◽  
Vol 10 (2) ◽  
pp. 39-46 ◽  
Author(s):  
Christopher F. Labosier
Keyword(s):  
Environmental Science ◽  
Science Curriculum ◽  
Science Classroom ◽  
Environmental Issues ◽  
Decision Makers ◽  
Social Dimensions ◽  
Physical Processes ◽  
Research Experiences ◽  
The Social ◽  
Definition Of

A firm definition of geography is often elusive and at times, the field is criticized for borrowing heavily from other disciplines. However, this article argues that the real strength of geography is its integrative nature. The purpose of this article is to discuss geography's integrative nature and how this strength can be integrated into the undergraduate environmental science curriculum. Two brief examples are provided from the author's own teaching and research experiences. Concept mapping in an introductory environmental science class allows students to visualize the complexity and integrative nature of environmental issues. In the atmospheric science classroom, students are introduced not only to the physical processes of weather hazards, but to the social dimensions as well. It is imperative that future scientists, advocates, and decision makers learn to critically integrate across disciplines to solve the world's most pressing environmental issues.

Fuzzy Three-Dimensional Voronoi Diagram and its Application to Geographical Data Analysis

2012 ◽  
Vol 16 (2) ◽  
pp. 191-198
Author(s):  
Mian Dai ◽  
◽  
Fangyan Dong ◽  
Kaoru Hirota
Keyword(s):  
Voronoi Diagram ◽  
Three Dimensional ◽  
Spatial Relation ◽  
Spatial Relations ◽  
Mountainous Area ◽  
Two Dimensional ◽  
Spatial Direction ◽  
Geographical Data ◽  
Direction Relations ◽  
Complex Boundaries

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.

Hemispheric Processing of Categorical and Coordinate Spatial Relations in the Absence of Low Spatial Frequencies

2002 ◽  
Vol 14 (2) ◽  
pp. 291-297 ◽  
Author(s):  
Matia Okubo ◽  
Chikashi Michimata
Keyword(s):  
Visual Field ◽  
Spatial Frequency ◽  
Right Hemisphere ◽  
Spatial Relation ◽  
Spatial Relations ◽  
Right Visual Field ◽  
Spatial Frequencies ◽  
Categorical Task ◽  
The Right ◽  
Coordinate Spatial Relations

Right-handed participants performed the categorical and coordinate spatial relation judgments on stimuli presented to either the left visual field—right hemisphere (LVF-RH) or the right visual field—left hemisphere (RVF-LH). The stimulus patterns were formulated either by bright dots or by contrast-balanced dots. When the stimuli were bright, an RVF-LH advantage was observed for the categorical task, whereas an LVF-RH advantage was observed for the coordinate task. When the stimuli were contrast balanced, the RVF-LH advantage was observed for the categorical task, but the LVF-RH advantage was eliminated for the coordinate task. Because the contrast-balanced dots are largely devoid of low spatial frequency content, these results suggest that processing of low spatial frequency is responsible for the right hemisphere advantage for the coordinate spatial processing.

The Role of High Spatial Frequencies in Hemispheric Processing of Categorical and Coordinate Spatial Relations

2004 ◽  
Vol 16 (9) ◽  
pp. 1576-1582 ◽  
Author(s):  
Matia Okubo ◽  
Chikashi Michimata
Keyword(s):  
Visual Field ◽  
Spatial Frequency ◽  
Right Hemisphere ◽  
High Spatial Frequency ◽  
Spatial Relation ◽  
Spatial Relations ◽  
Right Visual Field ◽  
Spatial Frequencies ◽  
Low Pass ◽  
Categorical Task

Right-handed participants performed categorical and coordinate spatial relation tasks on stimuli presented either to the left visual field-right hemisphere (LVF-RH) or to the right visual field-left hemisphere (RVF-LH). The stimuli were either unfiltered or low-pass filtered (i.e., devoid of high spatial frequency content). Consistent with previous studies, the unfiltered condition produced a significant RVF-LH advantage for the categorical task and an LVF-RH advantage for the coordinate task. Low-pass filtering eliminated this Task × Visual Field interaction; thus, the RVF-LH advantage disappeared for the categorical task. The present results suggest that processing of high spatial frequency contributes to the left hemispheric advantage for categorical spatial processing.

Kinematic Simulation Using Qualitative Mechanism Models

1995 ◽  
Author(s):  
Jihong Liu ◽  
Masanori Igoshi ◽  
Eiji Arai
Keyword(s):  
Conceptual Design ◽  
Spatial Relation ◽  
Spatial Relations ◽  
Quantitative Information ◽  
Design Stage ◽  
Kinematic Simulation ◽  
Conceptual Design Stage ◽  
Support Tools ◽  
Mechanical Products ◽  
Structural Descriptions

Abstract When trying to use computers to aid designers at the conceptual design stage, it becomes clear that many traditional methods and support tools are incompetent because they mainly deal with sufficient and quantitative information. However, at the conceptual design stage, information is insufficient and mostly qualitative. The focus of this paper is on representing and reasoning about the geometry and motion of physical objects for mechanical conceptual design. A new concept, called qualitative spatial relation space (QSRS), is introduced to describe mechanisms of mechanical products by referring to the qualitative spatial relations between their components. A qualitative kinematic simulation system has been implemented to enable verification of functions of products at the conceptual design stage. The system derives motions of components caused by other components’ specified motions from the qualitative structural descriptions of products, and puts brief and comprehensible functional interpretations of products.

scholarly journals Image-Text Joint Learning for Social Images with Spatial Relation Model

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Jiangfan Feng ◽  
Xuejun Fu ◽  
Yao Zhou ◽  
Yuling Zhu ◽  
Xiaobo Luo
Keyword(s):  
Large Scale ◽  
Clustering Algorithm ◽  
Semantic Analysis ◽  
Spatial Relationship ◽  
Spatial Relation ◽  
Spatial Relations ◽  
Image Features ◽  
Sensor Technology ◽  
Joint Learning ◽  
Social Images

The rapid developments in sensor technology and mobile devices bring a flourish of social images, and large-scale social images have attracted increasing attention to researchers. Existing approaches generally rely on recognizing object instances individually with geo-tags, visual patterns, etc. However, the social image represents a web of interconnected relations; these relations between entities carry semantic meaning and help a viewer differentiate between instances of a substance. This article forms the perspective of the spatial relationship to exploring the joint learning of social images. Precisely, the model consists of three parts: (a) a module for deep semantic understanding of images based on residual network (ResNet); (b) a deep semantic analysis module of text beyond traditional word bag methods; (c) a joint reasoning module from which the text weights obtained using image features on self-attention and a novel tree-based clustering algorithm. The experimental results demonstrate the effectiveness of using Flickr30k and Microsoft COCO datasets. Meanwhile, our method considers spatial relations while matching.

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