Geographical Information Systems (GIS) research area have been evolving with time. Those systems have become useful beyond spatial and geographic information representation and computer aided analysis using maps.
Some of the most important fields of application for GIS are fleet control, tourism analysis and Meteorological analysis. For the last mentioned field, advisory and prediction models should be enhanced aiming the avoidance of critical damage associated to Hurricanes. Intelligent systems have become the optimal solution when decision-making situations are extreme and advanced reasoning is expected.
Existing models involve high mathematical analysis, which is complex for humans and also sometimes computational costs have to be considered. There are some artificial intelligence fields that are exploring the possibility of making inference about existing data, enriching the information and enhancing the obtained results. In the present work we propose a hybrid GIS which includes some behavioral aspects of intelligent systems for Hurricane analysis.
Table of Contents
I. INTRODUCTION
II. STATE OF THE ART
III. THE LAYING DATA MODEL
IV. REASONING OVER GIS APPLICATIONS
V. CONCLUSIONS
Objectives and Topics
The primary objective of this work is to address the limitations of existing Geographical Information Systems (GIS) in handling complex, human-like reasoning regarding the movement of spatial entities, specifically for hurricane analysis and prediction. By integrating an ontological model with advanced reasoning capabilities, the study aims to improve the accuracy of hurricane tracking, impact evaluation, and semantic trajectory analysis.
- Enhancement of GIS through intelligent systems and ontologies.
- Representation and semantic analysis of moving objects (hurricanes).
- Application of Qualitative Spatial Reasoning (QSR) and SWRL rules.
- Integration of an ontological model for semantic enrichment of mobility data.
- Development of a plugin-based reasoning engine for enhanced spatial analysis.
Excerpt from the Book
I. INTRODUCTION
The analysis of hurricanes and their impact in determinate areas is mandatory if we have to preserve human life and economic resources. To precisely predict how will evolve and behave one tropical storm in time is the key for meteorologists on this venue. Even we have precise mathematic and geo-graphic models for understanding this phenomena, the diverse nature and the high number of variables that interact in the life cycle of one hurricane makes extremely difficult to say we are exact in prediction, even more with a minimum probability of failure. The answer lies in the ”understanding of hurricanes as they mean”, taking into account what origin them, which factors have influence in their evolution and behavior and what features exactly characterize all them in general or what they have in common. Then we are considering semantic analysis. Moreover, we have to pay special attention to the analysis of the motion semantics, especially to the representation of movement of spatial entities and the associated reasoning. All these spatial objects that change their position or shape over time are called moving objects [14].
The analysis of motion semantics has become in an impor-tant issue for the correct representation and subsequent rea-soning about moving objects in the world (trajectory analysis, movement patterns recognition, movement prediction). When we represent planes or vehicles for tracking purpose, we can talk about moving points. For meteorologists hurricanes (that move or change their extension) can be represented by moving regions. Finally, when we represent or track something like a moving fleet of ships or convoys, which can increase or diminish their extension, we have then a moving line. Most of these application fields are extremely important and some of them need accurate information in order to avoid unwanted disasters, for example aircraft tracking.
Summary of Chapters
I. INTRODUCTION: This chapter highlights the necessity of semantic analysis for hurricane tracking and defines the importance of modeling moving objects to preserve life and resources.
II. STATE OF THE ART: This section reviews existing research in Qualitative Spatial Reasoning, Region Connection Calculus, and ontological approaches to spatiotemporal data representation.
III. THE LAYING DATA MODEL: This chapter proposes an ontological data model designed to capture the domain of moving objects and ensure interoperability through formal mapping.
IV. REASONING OVER GIS APPLICATIONS: This section details the architecture of the proposed GIS, focusing on its semantic extractor, reasoning engine, and practical applications like hurricane classification.
V. CONCLUSIONS: This final section synthesizes the findings, emphasizing the potential of human-like reasoning and ontological models to advance meteorological analysis in GIS.
Keywords
GIS, Hurricane Analysis, Intelligent Systems, Ontology, Movement Semantics, Spatiotemporal Reasoning, Qualitative Spatial Reasoning, Moving Objects, Trajectory Analysis, Knowledge Representation, SWRL, Semantic Enrichment, Meteorological Analysis, Reasoning Engine, Computational Models
Frequently Asked Questions
What is the core focus of this research?
The work focuses on enhancing Geographical Information Systems (GIS) by integrating ontological models and intelligent reasoning to better analyze hurricane behavior and movement.
What are the primary thematic fields addressed?
The primary fields include GIS, Artificial Intelligence, Spatiotemporal Knowledge Representation, Motion Semantics, and Meteorological Prediction.
What is the central research question?
The study explores how an ontology-driven GIS can bridge the gap between traditional spatial analysis and human-like reasoning to improve accuracy in critical scenarios like hurricane tracking.
Which scientific methodology is utilized?
The authors employ an ontological modeling approach combined with SWRL (Semantic Web Rule Language) rules and Qualitative Spatial Reasoning to infer new knowledge from existing mobility data.
What topics are discussed in the main body of the work?
The body covers current limitations in GIS, the proposal of a hybrid ontological data model, the architecture of a reasoning engine based on Pellet, and practical use cases such as hurricane and region classification.
Which keywords define this paper?
Key terms include GIS, Hurricane Analysis, Intelligent Systems, Ontology, Movement Semantics, and Spatiotemporal Reasoning.
How does the proposed system handle moving objects like hurricanes?
The system represents hurricanes as "moving regions" and uses an ontological framework to analyze their trajectory, evolution, and semantic characteristics, enabling more nuanced reasoning than traditional point-based methods.
What role does the Pellet reasoner play in this architecture?
The Pellet reasoner acts as the reasoning engine within the GIS, processing information stored in the ontology to generate new knowledge through inference, which is crucial for precise hurricane impact evaluation.
Why are standard GIS models considered insufficient by the authors?
Standard models often lack the ability to perform semantic reasoning and typically focus only on static or purely spatial/geographical features, neglecting the complex motion semantics required for accurate predictive analysis.
- Quote paper
- Proff. Yuniel Proenza (Author), 2016, Intelligent Analysis of Hurricane Data over GIS Applications, Munich, GRIN Verlag, https://www.grin.com/document/345132
