5,928 research outputs found
Max-Min Fuzzy Relation Equations for a Problem of Spatial Analysis
We implement an algorithm that uses a system of max-min fuzzy relation equations (SFRE) for solving a problem of spatial analysis. We integrate this algorithm in a Geographical information Systems (GIS) tool. We apply our process to determine the symptoms after that an expert sets the SFRE with the values of the impact coefficients related to some parameters of a geographic zone under study. We also define an index of evaluation about the reliability of the results
A review of wildland fire spread modelling, 1990-present 3: Mathematical analogues and simulation models
In recent years, advances in computational power and spatial data analysis
(GIS, remote sensing, etc) have led to an increase in attempts to model the
spread and behvaiour of wildland fires across the landscape. This series of
review papers endeavours to critically and comprehensively review all types of
surface fire spread models developed since 1990. This paper reviews models of a
simulation or mathematical analogue nature. Most simulation models are
implementations of existing empirical or quasi-empirical models and their
primary function is to convert these generally one dimensional models to two
dimensions and then propagate a fire perimeter across a modelled landscape.
Mathematical analogue models are those that are based on some mathematical
conceit (rather than a physical representation of fire spread) that
coincidentally simulates the spread of fire. Other papers in the series review
models of an physical or quasi-physical nature and empirical or quasi-empirical
nature. Many models are extensions or refinements of models developed before
1990. Where this is the case, these models are also discussed but much less
comprehensively.Comment: 20 pages + 9 pages references + 1 page figures. Submitted to the
International Journal of Wildland Fir
Assessment of check damsâ role in flood hazard mapping in a semi-arid environment
This study aimed to examine flood hazard zoning and assess the role of check dams as effective hydraulic structures in reducing flood hazards. To this end, factors associated with topographic, hydrologic and human characteristics were used to develop indices for flood mapping and assessment. These indices and their components were weighed for flood hazard zoning using two methods: (i) a multi-criterion decision-making model in fuzzy logic and (ii) entropy weight. After preparing the flood hazard map by using the above indices and methods, the characteristics of the changeâpoint were used to assess the role of the check dams in reducing flood risk. The method was used in the Ilanlu catchment, located in the northwest of Hamadan province, Iran, where it is prone to frequent flood events. The results showed that the area of âvery lowâ, âlowâ and âmoderateâ flood hazard zones increased from about 2.2% to 7.3%, 8.6% to 19.6% and 22.7% to 31.2% after the construction of check dams, respectively. Moreover, the area of âhighâ and âvery highâ flood hazard zones decreased from 39.8% to 29.6%, and 26.7% to 12.2%, respectively
Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)
This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio
Application of Geographic Information Systems
The importance of Geographic Information Systems (GIS) can hardly be overemphasized in todayâs academic and professional arena. More professionals and academics have been using GIS than ever â urban & regional planners, civil engineers, geographers, spatial economists, sociologists, environmental scientists, criminal justice professionals, political scientists, and alike. As such, it is extremely important to understand the theories and applications of GIS in our teaching, professional work, and research. âThe Application of Geographic Information Systemsâ presents research findings that explain GISâs applications in different subfields of social sciences. With several case studies conducted in different parts of the world, the book blends together the theories of GIS and their practical implementations in different conditions. It deals with GISâs application in the broad spectrum of geospatial analysis and modeling, water resources analysis, land use analysis, infrastructure network analysis like transportation and water distribution network, and such. The book is expected to be a useful source of knowledge to the users of GIS who envision its applications in their teaching and research. This easy-to-understand book is surely not the end in itself but a little contribution to toward our understanding of the rich and wonderful subject of GIS
Three-dimensional hydrodynamic models coupled with GIS-based neuro-fuzzy classification for assessing environmental vulnerability of marine cage aquaculture
There is considerable opportunity to develop new modelling techniques within a
Geographic Information Systems (GIS) framework for the development of sustainable
marine cage culture. However, the spatial data sets are often uncertain and incomplete,
therefore new spatial models employing âsoft computingâ methods such as fuzzy logic
may be more suitable.
The aim of this study is to develop a model using Neuro-fuzzy techniques in a 3D GIS
(Arc View 3.2) to predict coastal environmental vulnerability for Atlantic salmon cage
aquaculture. A 3D hydrodynamic model (3DMOHID) coupled to a particle-tracking
model is applied to study the circulation patterns, dispersion processes and residence
time in Mulroy Bay, Co. Donegal Ireland, an Irish fjard (shallow fjordic system), an
area of restricted exchange, geometrically complicated with important aquaculture
activities.
The hydrodynamic model was calibrated and validated by comparison with sea surface
and water flow measurements. The model provided spatial and temporal information on
circulation, renewal time, helping to determine the influence of winds on circulation
patterns and in particular the assessment of the hydrographic conditions with a strong
influence on the management of fish cage culture.
The particle-tracking model was used to study the transport and flushing processes.
Instantaneous massive releases of particles from key boxes are modelled to analyse the
ocean-fjord exchange characteristics and, by emulating discharge from finfish cages, to
show the behaviour of waste in terms of water circulation and water exchange.
In this study the results from the hydrodynamic model have been incorporated into GIS
to provide an easy-to-use graphical user interface for 2D (maps), 3D and temporal
visualization (animations), for interrogation of results.
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Data on the physical environment and aquaculture suitability were derived from a 3-
dimensional hydrodynamic model and GIS for incorporation into the final model
framework and included mean and maximum current velocities, current flow quiescence
time, water column stratification, sediment granulometry, particulate waste dispersion
distance, oxygen depletion, water depth, coastal protection zones, and slope.
The Neuro-fuzzy classification model NEFCLASSâJ, was used to develop learning
algorithms to create the structure (rule base) and the parameters (fuzzy sets) of a fuzzy
classifier from a set of classified training data. A total of 42 training sites were sampled
using stratified random sampling from the GIS raster data layers, and the vulnerability
categories for each were manually classified into four categories based on the opinions
of experts with field experience and specific knowledge of the environmental problems
investigated.
The final products, GIS/based Neuro Fuzzy maps were achieved by combining modeled
and real environmental parameters relevant to marine fin fish Aquaculture.
Environmental vulnerability models, based on Neuro-fuzzy techniques, showed
sensitivity to the membership shapes of the fuzzy sets, the nature of the weightings
applied to the model rules, and validation techniques used during the learning and
validation process. The accuracy of the final classifier selected was R=85.71%,
(estimated error value of Âą16.5% from Cross Validation, N=10) with a Kappa
coefficient of agreement of 81%. Unclassified cells in the whole spatial domain (of
1623 GIS cells) ranged from 0% to 24.18 %.
A statistical comparison between vulnerability scores and a significant product of
aquaculture waste (nitrogen concentrations in sediment under the salmon cages) showed
that the final model gave a good correlation between predicted environmental
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vulnerability and sediment nitrogen levels, highlighting a number of areas with variable
sensitivity to aquaculture.
Further evaluation and analysis of the quality of the classification was achieved and the
applicability of separability indexes was also studied. The inter-class separability
estimations were performed on two different training data sets to assess the difficulty of
the class separation problem under investigation. The Neuro-fuzzy classifier for a
supervised and hard classification of coastal environmental vulnerability has
demonstrated an ability to derive an accurate and reliable classification into areas of
different levels of environmental vulnerability using a minimal number of training sets.
The output will be an environmental spatial model for application in coastal areas
intended to facilitate policy decision and to allow input into wider ranging spatial
modelling projects, such as coastal zone management systems and effective
environmental management of fish cage aquaculture
Investigation on soft computing techniques for airport environment evaluation systems
Spatial and temporal information exist widely in engineering fields, especially
in airport environmental management systems. Airport environment is influenced
by many different factors and uncertainty is a significant part of the
system. Decision support considering this kind of spatial and temporal information
and uncertainty is crucial for airport environment related engineering
planning and operation. Geographical information systems and computer aided
design are two powerful tools in supporting spatial and temporal information
systems. However, the present geographical information systems and computer
aided design software are still too general in considering the special features in
airport environment, especially for uncertainty. In this thesis, a series of parameters
and methods for neural network-based knowledge discovery and training
improvement are put forward, such as the relative strength of effect, dynamic
state space search strategy and compound architecture. [Continues.
Geomorphic Change Detection Using Multi-Beam Sonar
The emergence of multi-beam echo sounders (MBES) as an applicable surveying technology in shallow water environments has expanded the extent of geomorphic change detection studies to include river environments that historically have not been possible to survey or only small portions have been surveyed. The high point densities and accuracy of MBES has the potential to create highly accurate digital elevation models (DEM). However, to properly use MBES data for DEM creation and subsequent analysis, it is essential to quantify and propagate uncertainty in surveyed points and surfaces derived from them through each phase of data collection and processing. Much attention has been given to the topic of spatially variable uncertainty propagation in the context of the construction of DEM and their use in geomorphic change detection studies. However little work has been done specifically with applying spatially varying uncertainty models for MBES data in shallow water environments. To address this need, this report presents a review of literature and methodology of uncertainty quantification in a geomorphic change detection study. These methods are then applied and analyzed in a geomorphic change detection study using MBES as the data collection technique
Development and implementation of a GIS-based tool for spatial modeling of seismic vulnerability of Tehran
Achieving sustainable development in countries prone to earthquakes is possible with taking effective measures to reduce vulnerability to earthquakes. In this context, damage assessment of hypothetical earthquakes and planning for disaster management are important issues. Having a computer tool capable of estimating structural and human losses from earthquakes in a specific region may facilitate the decision-making process before and during disasters. Interoperability of this tool with wide-spread spatial analysis frameworks will expedite the data transferring process. In this study, the earthquake damage assessment (EDA) software tool is developed as an embedded extension within a GIS (geographic information system) environment for the city of Tehran, Iran. This GIS-based extension provides users with a familiar environment to estimate and observe the probable damages and fatalities of a deterministic earthquake scenario. The productivity of this tool is later demonstrated for southern Karoon parish, Region 10, Tehran. Three case studies for three active faults in the area and a comparison of the results with other research substantiated the reliability of this tool for additional earthquake scenarios
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