60,168 research outputs found
Modeling emergency management data by UML as an extension of geographic data sharing model: AST approach
Applying GIS functionality provides a powerful decision support in various application areas and the basis to integrate policies directed to citizens, business, and governments. The focus is changing toward integrating these functions to find optimal solutions to complex problems. As an integral part of this approach, geographic data sharing model for Turkey were developed as a new approach that enables using the data corporately and effectively. General features of this model are object-oriented model, based on ISO/TC211 standards and INSPIRE Data Specifications, describing nationwide unique object identifiers, and defining a mechanism to manage object changes through time. The model is fully described with Unified Modeling Language (UML) class diagram. This can be a starting point for geographic data providers in Turkey to create sector models like Emergency Management that has importance because of the increasing number of natural and man-made disasters. In emergency management, this sector model can provide the most appropriate data to many "Actors" that behave as emergency response organizations such as fire and medical departments. Actors work in "Sectors" such as fire department and urban security. Each sector is responsible for "Activities" such as traffic control, fighting dire, emission, and so on. "Tasks" such as registering incident, fire response, and evacuating area are performed by actors and part of activity. These tasks produce information for emergency response and require information based on the base data model. By this way, geographic data models of emergency response are designed and discussed with "Actor-Sector-Activity-Task" classes as an extension of the base model with some cases from Turkey
Towards spatio‐temporal data modeling of geo‐tagged shipping information
Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science
"Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.Spatio-temporal data models deal with capturing information characterized by both spatial and temporal semantics. In this paper we review current approaches for spatio-temporal data modelling and present out initial results for selecting the most relevant approach: Object-Oriented modeling for means of modeling geo-tagged shipping information. The shipping information is provided by the well-known LLLOYD’s lists dataset. We have introduced the case study and dataset characteristics used in the research project and presented our data model in Unified Modeling Language (UML). The model focuses on spatio-temporal events where characteristics are categorized as thematic, spatial and temporal attributes. The paper follows up with discussion on the selected approach and results, and finally ends with presenting the future outlook
Smart Geographic object: Toward a new understanding of GIS Technology in Ubiquitous Computing
One of the fundamental aspects of ubiquitous computing is the instrumentation
of the real world by smart devices. This instrumentation constitutes an
opportunity to rethink the interactions between human beings and their
environment on the one hand, and between the components of this environment on
the other. In this paper we discuss what this understanding of ubiquitous
computing can bring to geographic science and particularly to GIS technology.
Our main idea is the instrumentation of the geographic environment through the
instrumentation of geographic objects composing it. And then investigate how
this instrumentation can meet the current limitations of GIS technology, and
offers a new stage of rapprochement between the earth and its abstraction. As
result, the current research work proposes a new concept we named Smart
Geographic Object SGO. The latter is a convergence point between the smart
objects and geographic objects, two concepts appertaining respectively to
A storage and access architecture for efficient query processing in spatial database systems
Due to the high complexity of objects and queries and also due to extremely
large data volumes, geographic database systems impose stringent requirements on their
storage and access architecture with respect to efficient query processing. Performance
improving concepts such as spatial storage and access structures, approximations, object
decompositions and multi-phase query processing have been suggested and analyzed as
single building blocks. In this paper, we describe a storage and access architecture which
is composed from the above building blocks in a modular fashion. Additionally, we incorporate
into our architecture a new ingredient, the scene organization, for efficiently
supporting set-oriented access of large-area region queries. An experimental performance
comparison demonstrates that the concept of scene organization leads to considerable
performance improvements for large-area region queries by a factor of up to 150
An open and extensible framework for spatially explicit land use change modelling in R: the lulccR package (0.1.0)
Land use change has important consequences for biodiversity and the
sustainability of ecosystem services, as well as for global
environmental change. Spatially explicit land use change models
improve our understanding of the processes driving change and make
predictions about the quantity and location of future and past
change. Here we present the lulccR package, an object-oriented
framework for land use change modelling written in the R programming
language. The contribution of the work is to resolve the following
limitations associated with the current land use change modelling
paradigm: (1) the source code for model implementations is
frequently unavailable, severely compromising the reproducibility of
scientific results and making it impossible for members of the
community to improve or adapt models for their own purposes; (2)
ensemble experiments to capture model structural uncertainty are
difficult because of fundamental differences between implementations
of different models; (3) different aspects of the modelling
procedure must be performed in different environments because
existing applications usually only perform the spatial allocation of
change. The package includes a stochastic ordered allocation
procedure as well as an implementation of the widely used CLUE-S
algorithm. We demonstrate its functionality by simulating land use
change at the Plum Island Ecosystems site, using a dataset included
with the package. It is envisaged that lulccR will enable future
model development and comparison within an open environment
Can geocomputation save urban simulation? Throw some agents into the mixture, simmer and wait ...
There are indications that the current generation of simulation models in practical,
operational uses has reached the limits of its usefulness under existing specifications.
The relative stasis in operational urban modeling contrasts with simulation efforts in
other disciplines, where techniques, theories, and ideas drawn from computation and
complexity studies are revitalizing the ways in which we conceptualize, understand,
and model real-world phenomena. Many of these concepts and methodologies are
applicable to operational urban systems simulation. Indeed, in many cases, ideas from
computation and complexity studies—often clustered under the collective term of
geocomputation, as they apply to geography—are ideally suited to the simulation of
urban dynamics. However, there exist several obstructions to their successful use in
operational urban geographic simulation, particularly as regards the capacity of these
methodologies to handle top-down dynamics in urban systems.
This paper presents a framework for developing a hybrid model for urban geographic
simulation and discusses some of the imposing barriers against innovation in this
field. The framework infuses approaches derived from geocomputation and
complexity with standard techniques that have been tried and tested in operational
land-use and transport simulation. Macro-scale dynamics that operate from the topdown
are handled by traditional land-use and transport models, while micro-scale
dynamics that work from the bottom-up are delegated to agent-based models and
cellular automata. The two methodologies are fused in a modular fashion using a
system of feedback mechanisms. As a proof-of-concept exercise, a micro-model of
residential location has been developed with a view to hybridization. The model
mixes cellular automata and multi-agent approaches and is formulated so as to
interface with meso-models at a higher scale
Image databases: Problems and perspectives
With the increasing number of computer graphics, image processing, and pattern recognition applications, economical storage, efficient representation and manipulation, and powerful and flexible query languages for retrieval of image data are of paramount importance. These and related issues pertinent to image data bases are examined
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