Applied GIS
a free, electronic, refereed
journal
ABSTRACTS IN ENGLISH
2011
–
7(2): Using a GIS-based, Hitchcock
algorithm to optimize parking allocations for special events, by Sarasua, W.A., Malisetty, P.
& Chowdhury, M.
[Abstract 
;Full
text 
].
Clemson, a
small college town in South Carolina, deals with a massive over-saturation of its
transportation system during special events, especially during home football
games, resulting in total system failure. This research has developed a methodology to
optimize parking, using a Geographic Information System (GIS)-based transshipment algorithm, and it has produced great time savings
compared with the individual, “manual” efforts of thousands of drivers
attempting to find spaces where available. As such, this research constitutes an
effective implementation of the Hitchcock Transportation Algorithm for solving
a transshipment problem applied to parking lot
distribution. Because the Hitchcock Algorithm
considers the network cost for distributions, it gives very realistic solutions,
and so a system equilibrium that minimizes overall system delay has been achieved
through optimal parking assignment combined with pre- and post-game traffic
control strategies. This has been
validated using a simulation model that was developed for evaluating the strategies.
7(1): Remote
sensing of land cover’s effect on surface temperatures: a case study of the
urban heat island in Bangalore, India by S. Ambinakudige.
[Abstract ;Full text .
Urbanization
has substantially altered the earth’s surface, and cities’ impervious surfaces
for anthropogenic activities often generate an urban heat island (UHI). This paper analyses the effects of the UHI in Bangalore,
which in recent years has witnessed
tremendous in-migration of people and expansion of infrastructure due to rapid
growth of its information technology, biotechnology and manufacturing sectors. Temperature values extracted from the Landsat satellite’s Enhanced Thematic Mapper
Plus (
2010
–
6(2): Land use change detection for environmental management:
using multi-temporal satellite data in the Apodi
Valley of northeastern Brazil by Boori,
M.S. & Amaro,
V.E.
[Abstract ;Full text ].
In this study maximum-likelihood, supervised classification along with
post-classification change detection was applied to satellite images for 1986,
1989, 1996, 2001, and 2009, in order to map land-cover changes within the Apodi
Valley region of northeastern Brazil.
The supervised classification was carried out on the six reflective
bands and ground truthed. The classification results were then further refined
using ancillary data, visual interpretation and expert knowledge of the area
along with GIS. Post-classification
change detection then generated a change image in the form of
cross-tabulations. Fifteen land cover
classes existed within the area, and reclamation processes during the 1990’s
changed them substantially, with conflicting changes being caused primarily by
lack of both stability and consistency in the government’s land use
policies. The result was extensive
vegetation degradation and water logging in parts of the study area.
6(1): A support system that delineates location-choice sets for firms seeking office space by Manzato, G.G., Arentze, T.A., Timmermans, H.J.P. & Ettema, D.
[Abstract ;Full text ].
Factors
influencing the location decisions of offices include traffic, accessibility,
employment conditions, economic prospects and land-use policies. Hence tools
for supporting real-estate managers and urban planners in such multidimensional
decisions may be useful. Accordingly, the objective of this study is to develop
a GIS-based tool to support firms who seek office accommodation within a given
regional or national study area. The tool relies on a matching approach, in
which a firm’s characteristics (demand) on the one hand, and environmental
conditions and available office spaces (supply) on the other, are analysed
separately in a first step, after which a match is sought. That is, a
suitability score is obtained for every firm and for every available office
space by applying some value judgments (satisfaction, utility etc.). The latter
are powered by a focus on location aspects and expert knowledge about the
location decisions of firms/organizations with respect to office accommodation
as acquired from a group of real-estate advisers; it is stored in decision
tables, and they constitute the core of the model. Apart from the delineation
of choice sets for any firm seeking a location, the tool supports two
additional types of queries. Firstly, it supports the more generic problem of
optimally allocating firms to a set of vacant locations. Secondly, the tool allows
users to find firms which meet the characteristics of any given location.
Moreover, as a GIS-based tool, its results can be visualized using GIS features
which, in turn, facilitate several types of analyses.
2009
–
5(3): Application of GIS-based computer modelling to planning for adaption to climate change in rural areas by Sposito, V., Benke, K., Pelizaro, C. & Wyatt, R.
[Abstract ;Full text ].
A
5(2): Using
Rational Polynomial Coefficients (RPC) to generate digital elevation models - a
comparative study
by
Jain, K., Ravibabu,
M.V., Shafi,
J.A. & Singh, S.P.
[Abstract ; Full text ].
Models based on
Rational Polynomial Coefficients (RPC) have recently sparked considerable
interest within the remote sensing community because of their simplicity and
accuracy. Indeed, some commercial,
high-resolution, satellite imagery data are now supplied with RPC even though
they do not disclose their physical sensor model. RPC, with stereo pairs, enable full
photogrammetric processing including 3-D reconstruction, generation of digital
elevation models (DEMs), orthorectification,
block adjustment and feature extraction. In the light of this we here present a
complete methodology for generating a DEM from stereo satellite images by using
rational polynomial coefficients of the imaging geometry. We also conduct a study of the accuracy and
performance, in terms of generating a stereo images-based DEM using RPC within
three well known software packages. Our results are evaluated using sample data
that was captured by IKONOS.
5(1):
Optimizing landscape value for man and
nature: a case study of land-suitability mapping to conserve biodiversity in Lawaan, Eastern Samar,
Philippines by Casas, E.V. & Baguinon, N.T.
[Abstract ;Full text ].
We show how to identify “hotspot” biodiversity areas on
which to base relevant policies and management options whenever traditional,
community-based, resource management puts biodiversity conservation at risk, as
is the case in Lawaan,
Eastern Samar, Philippines. Digital spatial data integration revealed
that the lower elevation areas are under the heaviest human pressure and also
have the highest biodiversity. This
calls for a set of procedures for engaging the full range of stakeholders to
identify areas for preservation.
Accordingly, we combined Social Based (SB) and Environmental Based (EB)
maps to identify four different classifications and identify the locations of
“very critical” and “critical” areas that need priority if
biodiversity-conservation efforts are to be effective. We also report the results of deploying
developed protocols that are designed to support regular updates, thereby
accommodating stakeholder interests so that an environmentally-based, zone map
can form a basis for consensus building and preservation-zone protection via
community enforcement.
2008 -
4(4):
Development of an open source-based
spatial data infrastructure by Stefanakis, E. & Prastacos, P.
[Abstract ;Full text ].
A pilot regional Spatial
Data Infrastructure (SDI) has recently been
developed for the Heraklion Prefecture in Crete , Greece , using Geographic Free and Open Source
Software (GeoFOSS). This
SDI is compatible with the geospatial standards and specifications introduced
by the Open Geospatial Consortium (OGC) and it distributes the geospatial
content on the web through widely accepted services (e.g., WMS, WFS, WCS and
CSW). This paper presents the architecture, the components and the
functionality of the Heraklion SDI. Specifically, it focuses on the map server, along with
the services that provide accessibility to the data repositories, the spatial
database server, the metadata and data catalog, the
visualization tools and the web-client interface.
4(3):
Ortho-rectified, oblique, aerial photography
for verifying and updating spatial data by Bulman, D.
[Abstract ;Full text ].
This paper explains how ortho-rectification of frame camera, aerial
photography is fairly complex, and the difficulties associated with rectifying
oblique aerial photos (OAPs) from small format photography have been so
problematic that the approach has been little used and seldom described within
the literature. Recent advances in photogrammetric software, however, have now
made conventional, frame camera photogrammetry
more convenient and more easily able to deal with the ortho-rectification of space-borne and air-borne
sensors as well as hand-held film and digital cameras. Consequently, it is now
possible to use oblique photography to correct vertical photographs - provided
that we address issues related to image distortion and ensure that the
reliability of extracted features is sufficient for their use within Geographic
Information Systems (GIS). This will be demonstrated by showing that oblique
photographs taken with a hand-held, 35 mm camera during a reconnaissance flight
over a weed infested area can be ortho-rectified
using modern software, thereby clarifying this approach's status as a useful
aid for delineating infestations for the purpose of say, ground truthing, verification of
remotely sensed image analysis or simply contributing towards more
comprehensive aerial mapping. The example used here may seem trivial but it
actually illustrates, clearly, how a spraying pattern, while possibly too
refined to show in a satellite image, can be mapped as a reference for
monitoring weed infestations. This example is not intended to be a rigorous
application of the technique, but simply a demonstration of its possibilities
whenever there is a need to quickly or frequently update existing spatial data
and environmental records in a much more cost-effective way than would be
possible through deployment of the much more expensive, conventional, aerial
survey methods.
4(2):
Using geovisualisation to support participatory problem
structuring and decision making for an urban water utility in Uganda by Kizito, F., Ngirane-Katashaya, G. & Thunvik, R.
[Abstract ;
Full text ].
This paper describes the application of geovisualisation to facilitate participatory
identification and structuring of problems in an urban water supply system in
customer complaints, was done. The maps so produced were key in bringing the various stakeholders and decision
makers to a common understanding of the problem issues, and helped in the
formulation of alternative courses of action. Furthermore, with the
establishment
of a formal discussion forum for problem analysis and decision making,
structured participatory decision making was entrenched within the company’s
work ethos. It is hoped that in future, the coupling of the geovisualisation tools with the existing operational
databases in the
company will result in the development of a functional spatial decision support
system and a dynamic framework for system performance monitoring and
reliability assessment.
4(1):
Evaluating forest harvesting to reduce its
hydrologic impact with a spatial decision support system by
Zhang, Y., Barten, P.K., Sugumaran, R. & DeGroote, J.
[Abstract ;
Full text ].
Timber harvesting changes the condition of forest
ecosystems, which are a major influence on the characteristics of headwater
streams. Such characteristics include the quantity and timing of base flow and
storm flow, concentrations of sediment and dissolved nutrients, water
temperature, and the stability of the stream channels. This paper explores
previous studies dealing with the relationship between timber harvesting
and its hydrologic effects, especially long term water yield increase. The
watershed disturbance threshold theory is raised and investigated in detail.
The development and evaluation of a spatial decision support system, the
Harvest Schedule Review System (HSRS), is then described. The HSRS will aid in
the minimization of hydrological impacts of forest harvesting, along with its
related, negative environmental influences. It provides
a spatially and temporally explicit tool for users to analyze the hydrologic impact of forest harvest
schedules.
2007
-
3(12):
Exploratory GIS modelling for
assessing potential conflict in
[Abstract ;
Full text ].
This paper presents a simple methodology (preliminary and
exploratory) to model potential hotspots of land-users' conflict at regional
level in preparation of a dispute system design.
3(11):
Web-based GIS for mapping voting
patterns at the 2004 Australian federal election by Shyy, T, Stimson, R. & Chhetri, P.
[Abstract ;
Full text ].
This paper describes a Web-based geographical information
system (GIS) for mapping voting patterns at the 2004 Australian federal
election at the polling booth level. The locations of polling booths are geocoded and linked with national
digital datasets, including 2001 census data. The Web-based GIS can generate
maps displaying patterns of voting for political parties across polling booths
with overlays data showing the demographic and socio-economic characteristics
of populations within the surrounding polling booth catchments. A
classification functionality consisting of equal interval, quantile, median-based natural breaks and location
quotient may be used to generate different map displays. The Web-based GIS has
been developed as an information dissemination and analysis tool not only to
benchmark voting outcomes but also to visualise relationships between voting
patterns and demographic and socio-economic data.
3(10):
Categorising
inconsistencies between national GIS data in Central Europe: case studies from
the borders triangle of
[Abstract ; Full text ].
Operational environmental management of
European landscapes requires geographical information which is valid and
coherent across national borders and only takes natural boundaries as criteria
for ordering. However, when combining GIS data from different countries,
national borders appear as artificial breaks in many medium- and large-scale
thematic GIS, for example, topographical, geological or soil information
systems. Inconsistencies in GIS data can be categorised into three types: (1)
country specific deviations, (2) inconsistencies due to different data
surveying and management procedures and (3) errors. Some of the
inconsistencies, such as national attribute names, can be ruled out by simple
modifications of the data models without changing the structure of the national
databases themselves. Others, such as soil typologies, have to be addressed by
intensified co-operation between national authorities. It is concluded that for
practical and financial reasons, pragmatic solutions are required in order to
integrate national data into a European framework.
3(9):
A comparison of spatial disaggregtion techniques as applied to population
estimation for South East Queensland (SEQ),
[Abstract ; Full text ].
The accuracy of spatial disaggregation techniques largely
depends on their underlying density assumptions and the quality of the data
applied. This paper presents the results of a comparative investigation of four
spatial disaggregation methodologies to determine their relative accuracies.
These methodologies include binary dasymetric, a
regression model, a locally fitted regression model and threeclass dasymetric, each of which provides different solutions for explaining
spatially heterogeneous density when population data is spatially
disaggregated. In contrast to previous studies, we apply the spatial disaggregation
techniques to a comparably larger and more varied geographical area which
allows the spatial disaggregation techniques to be more rigorously tested.
Results indicate that the three-class dasymetric technique
generates higher levels of accuracy compared to the other spatial
disaggregation techniques and this result is more conclusive than previous
findings.
3(8):
Per-pixel and sub-pixel
classifications of high-resolution satellite data for mangrove species mapping by Kanniah, K.D., Ng S.W.,
Shin, A.L.M. & Rasib,
A.W.
[Abstract ; Full text ].
High spatial resolution sensors such as IKONOS and QuickBird, are expected to classify mangrove
species more accurately than coarse spatial resolution satellite images.
Conventional per-pixel classification techniques could not improve the
classification accuracy when such high-resolution images are applied. Such
failure has encouraged the invention of more sophisticated and deterministic
techniques i.e. subpixel
classifications. In this study, the mangrove forest at Sungai Belungkor,
3(7):
Assessing the relationship between
shire winter crop yield and seasonal variability of the MODIS NDVI and EVI
images by Fontana, D.C., Potgieter, A. B. & Apan, A.
[Abstract ; Full text ].
Australian researchers have been developing robust yield
estimation models, based mainly on the crop growth response to water
availability during the crop season. However, knowledge of spatial distribution
of yields within and across the production regions can be improved by the use
of remote sensing techniques. Images of Moderate Resolution Imaging Spectroradiometer (MODIS)
vegetation indices, available since 1999, have the potential to contribute to
crop yield estimation. The objective of this study was to analyse the
relationship between winter crop yields and the spectral information available
in MODIS vegetation index images at the shire level. The study was carried out
in the Jondaryan and Pittsworth shires,
3(6):
Optimization of health facility
locations in Osh City ,
[Abstract ; Full text ].
Basic information regarding location of existing facilities,
their accessibility and development trends, in relation to socio-economic
structure of a city is needed in order to prepare its developmental plan.
Re-location of any service may not be feasible economically, but
location-allocation models can be used to identify new potential locations.
This study is an attempt to simulate new potential locations and evaluate the
feasibility of optimization models for planning additional health facility in
the
3(5):
GIS software selection: a
multi-criteria decision making approach by Eldrandaly, K.
[Abstract ; Full text ].
Building a new GIS project is a major
investment. Choosing the right GIS software package is critical to the success
and failure of such investment. The problem of selecting the most appropriate
GIS software package for a particular GIS project is a multi criteria decision
making (MCDM) problem. Solving this problem requires consideration of a
comprehensive set of factors and balancing of multiple objectives in
determining the suitability of particular software for building a defined GIS
application. In this paper a MCDM technique, analytic hierarchy process (AHP),
is used to assist system developers to select the most appropriate GIS software
for a specific application. An AHP decision model is formulated and applied to
a hypothetical case study to examine its feasibility in solving GIS software
selection problem. The use of the proposed model indicates that it can be
applied to improve the decision making process and to reduce the time taken to
select a GIS software.
3(4): GIS-based
spatial analysis of child pedestrian accidents near primary schools in
[Abstract ; Full text ].
In
3(3):
The impact of neighbourhood size on
the accuracy of cellular automata-based urban modelling by Liu,Y.
[Abstract ; Full text ].
Cellular automata are discrete dynamic models in which
behaviour is specified in terms of local relations. This technique has recently
been advantageously applied to modelling of the urban development process.
However, the behaviour of the model is affected by spatial scale, including
cell size and neighbourhood extent. Therefore, it is important to examine the
impacts of various neighbourhood scales on the model's behaviour and outcome.
In this paper we configured a cellular automata model of urban growth in
3(2):
Prioritising areas for dugong
conservation in a marine protected area using a spatially explicit population
model by Grech,
A. & Marsh, H.
[Abstract ; Full text ].
The Great Barrier Reef World Heritage Area (GBRWHA) covers
an area of approximately 348,000km2 making it the world's largest World
Heritage Area / marine protected area complex. Dugongs (Dugong dugon) inhabit the shallow
protected waters of the GBRWHA, and were an explicit reason for the region's
World Heritage listing. To manage dugongs effectively in the GBRWHA, it is
critical to understand their spatial relationship with their environment and
the human activities that threaten them. We demonstrate how a spatially
explicit dugong population model can be used to prioritise conservation
initiatives for dugongs in the GBRWHA. We used information collected from
dugong aerial surveys in conjunction with geostatistical techniques, including universal kriging, to develop a model of
dugong distribution and abundance. After completing the model, we conducted
frequency analyses to categorise relative dugong density and distribution to
identify areas of low, medium or high conservation value. As dugongs extend
over a wide distributional range, prioritising areas of conservation value has
the potential to be an important basis for administering management resources.
We conclude that spatially explicit population models are an effective
component of species conservation management, particularly for species that
range over large, complex and dynamic regions.
3(1):
A methodology for spatial fuzzy
reliability analysis by Simonovic
[Abstract ; Full text ].
Natural hazard risk assessment requires quantification of
uncertainty that is spatially and temporally variable. Spatial variability of
risk has been rarely considered in the past research. This paper presents a new
methodology to capture the spatial uncertainty as well as the subjectivity
associated with the natural hazard risk analysis. The fuzzy set theory has been
integrated with the geographic information system (GIS) in the development of
the methodology for spatial reliability analysis. Paper explores the spatial
extension of three fuzzy reliability indices i.e. (1) combined
reliability-vulnerability, (2) robustness, and (3) resiliency. Fuzzy risk and
reliability are quantified within a GIS framework and maps showing spatial
variability of three fuzzy indices are developed. The proposed methodology has
been applied to flood hazard management. It has been found that the application
of spatial fuzzy reliability analysis provides additional information to flood
managers regarding the spatial variability of flood risk and aids in the
development of a sustainable flood management options.
2006
-
2(3):
Editorial - Strategic thinking for improved
regional planning and natural resources management by Victor
A.Sposito, Ray Wyatt &
Christopher J. Petit
[Abstract ; Full text].
This special theme issue of Applied GIS further widens the scope of
our journal by edging it closer to the “policy support” pole of the GIScience continuum. It contains
several creative articles showing how practicing planners of natural resources
and the environmental have managed to exploit the power of GIS and remote
sensing in order to improve strategic thinking. More specifically, this issue
showcases innovative GIS-related work being led by the Department of Primary Industries (DPI)
in the State of Victoria, Australia. All authors either work for, or
collaborate with this department's research division, which is known as Primary Industries Research Victoria ( PIRVic). Moreover, in the
spirit of providing informed decision support for rural and regional policy
makers, the selected articles describe and explain actual working projects that
have usually generated tangible results already. This editorial begins,
therefore, by outlining the basic philosophy of PIRVic . It then describes a “systems framework
for spatial decision making” in which each paper can be situated. Finally, we
briefly describe the nature and context of each article.
Applying an index of adaptive capacity to climate change
in north-western
[Abstract ; Full text].
Climate change calls for strategic planning that builds
resilience in vulnerable areas to manage the associated risks. This paper
discusses how adaptive various communities and industries are to climate change
in the North West of Victoria (also known as the Victorian wheat belt),
Spatial (GIS-based) decision support system for the
Westernport region by Claudia Pelizaro & David McDonald
[Abstract ; Full text].
This paper presents the conceptual design of a spatial
decision support system (SDSS) proposed for Victoria's Westernport region that
aims for the sustainable and integrated (whole-of-catchment) management of
regional natural resources. It is a solution integrating a range of approaches
including, GIS technology, a scenario management tool, state-of-art terrestrial
and marine models, environmental management strategy evaluation and multi-criteria
techniques. Traditionally, GIS are key
to (spatial) data management, but lack problem domain modelling capability.
This means additional processing or analytical capabilities are needed to
extend functionality for decision making. The Westernport SDSS builds upon a
GIS but draws on models and data processing systems and interacts with other
parts of an overall information system to support decision-making. This system
utilises a number of models that are interlinked through a cascade of their
results. Put simply, one set of model results input into the next in a
modelling chain. The system will derive a set of socio-economic-environmental
measures (performance indicators), such as land use, nutrient and sediment
concentration in water (water quality measures), and other relevant indicators
for coastal and bay ecosystems. Users will then be able to systematically
compare alternative natural resource management plans and strategies in light
of multiple and possibly conflicting criteria. By integrating relevant models
within a structured framework, the system will promote transparency of policy
development and natural resources management.
Using GIS in Landscape Visual Quality Assessment by Yingxin Wu, Ian Bishop, Hemayet Hossain & Victor Sposito
[Abstract ; Full text].
Landscape Visual Quality
(LVQ) ‘assessment has become a core component of landscape architecture,
landscape planning and spatial planning. Different
approaches for assessing the scenic qualities of landscapes have been developed
in the last few decades. Two contrasting paradigms, expert/design approach and
community perception-based approach, have dominated methodology development. In
the expert-design approach the landscape visual quality is defined by
biological and physical (or biophysical) values, while the perception-based
approach emphasises the human view (subjective) of the landscape. This paper
outlines a methodology combining expert and perception approaches to assess the
LVQ. The application of information technology to landscape analysis dates back
to the early work in computer-based mapping. Much of the early work on what
became Geographic Information Systems (GIS) and three-dimensional landscape
modelling was carried out by landscape architects and landscape planners. In
the past years, significant advances in computers and GIS have enabled analysis
of vast amounts of spatial information, which is the foundation of the
methodology described in this paper. The methodology is explained in detail
through its application to assess the LVQ of the Mornington Peninsula Shire,
Melbourne, in the State of Victoria, Australia. There are six stages in the
procedure: viewpoints selection; calculation of factor indices based on Visual
Exposure Modelling; landscape preference rating; use of statistical methods
(such as multiple regression model) to determine the key predictors of LVQ;
application of the formula thus generated to assess the LVQ of viewpoints; and
use of spatial interpolation to map LVQ across the study area. The results are
discussed in the last section of this paper with reference to key
methodological issues. Results show that the perceived LVQ increases with the
area of water visible, the degree of wilderness and percentage of natural
vegetation, and the presence of hills. On the other hand, it decreases with the
presence of perceived negative human-made elements such as roads and buildings.
Using GIS and a land use impact model to assess risk of
soil erosion in West Gippsland by Joanne
McNeill, Richard MacEwan & Doug Crawford
[Abstract ; Full text].
The Land Use Impact Model (LUIM) is a spatially explicit
tool developed by the Department of Primary Industries Victoria, and the
GIS-based modelling of regional conservation significance
by Victor A Sposito & Elizabeth Morse-McNabb
[Abstract ; Full text].
This paper explains an approach for appraising the extent
and quality of native vegetation and identifying significant habitats at
strategic regional and local levels. The Vegetation and Habitat Conservation
Significance Framework (hereafter the framework) is formulated through a
planning process which includes seven stages from defining the ‘Purpose of the
study' (Stage 1) to ‘Implementation and monitoring' (Stage 7). The cornerstone
of the framework is the formulation, in Stage 3, of a Regional Habitat Significance
Model which integrates the Analytic Hierarchy Process (AHP) with Geographic
Information System (GIS). An expert workshop (Stage 4) is an integral part of
model construction and should comprise 10 to 15 persons including environmental
and land use scientists, ecologists, planners and landscape architects with
good knowledge of vegetation, biodiversity and habitat matters, as well as
relevant decision-makers. Experts are provided with all the data sets generated
in Stage 2, and limitations and advantages of each data set are discussed. The
initial construction of the model (undertaken at Stage 3) is validated, or
modified, and then its components are weighted through consensus of the
experts. The GIS platform permits the ongoing improvement and input of the
latest, relevant information and the preparation of a new assessment in a
cyclical planning process. The method is predominantly explained by reference
to its application in the rural shire of
Evolutionary computing for optimizing a region's
distribution of agricultural production by
Ray Wyatt & Hemayet Hossain
[Abstract ; Full text].
This paper describes a GIS-based software package that
incorporates a ‘genetic algorithm' to optimize crops' distribution across any
region. Such optimization is powered by maps of where one finds the most
suitable conditions for each crop, or each crop's current local yields, market
price, market demand or transport costs. Our program's output is the crops
distribution which achieves maximum economic return, or minimal environmental
damage, or optimal fit with either present- or post-climatic-change soil suitability
or minimum transport cost. The package can be implemented within any region
where the necessary input data exists in Ascii and image format, and it incorporates a
number of features that make it transparent and flexible. Such user
friendliness encourages even laypersons to experiment with the genetic algorithm's parameters, almost as
if they are playing a computer game, to see whether or not they can find an
even more optimal crops distribution than they found previously. The package
also functions as a useful exploratory tool for seeing how current patterns
would have to be modified if a more optimal crops distribution were achieved,
thereby generating decision support type insights into possible repercussions
of tampering with the status quo. Our package's functionality will be
demonstrated through a case study implementation within the agricultural region
of South Gippsland,
Geographical visualization: A participatory planning
support tool for imagining landscape futures by Christopher J Pettit, William Cartwright & Michael
Berry
[Abstract ; Full text].
The geographical visualization of urban and regional
landscapes is a powerful technique for engaging actors involved in
decision-making processes. Tools developed can empower professional and citizen
alike to make better-informed decisions. The paper reports on collaborative
research being undertaken to develop and apply a range of 3D geographical
visualization products to enhance both planning and scientific communication
processes. In this paper we discuss some developments and applications of 3D
geographical visualization tools and work being undertaken to evaluate the
effectiveness of such tools for solving spatial planning problems. The paper
concludes by discussing the lessons learnt in undertaking a cross-disciplinary
approach to developing and applying landscape visualization tools and offers
some future research directions with respect to technical specifications and
the usefulness of geographical visualization as a participatory planning
support tool.
A strategic approach to climate change impacts and
adaptation by Victor A. Sposito
[Abstract ; Full text].
This paper describes a strategic approach to examining
potential climate change impacts on agricultural, forestry and regional/rural resources.
It outlines a holistic framework that links impacts with adaptation actions
that is consistent with new thoughts on preparing society for climate change.
The assessment of the potential impacts is a logical extension of the land
resource evaluation models described in the paper by Hossain et al. (2006) since it links land
suitability analysis modelling, developed by Primary Industries Research
Victoria (PIRVic), with
climate change impacts modelling developed by the Commonwealth Scientific and
Industry Research Organisation (CSIRO). The Framework is illustrated by its
applications in two regions in the State of Victoria, AUSTRALIA. The project
described in this paper is part of a joint national and state effort in
Sustainable land resource assessment in regional and
urban systems by Hemayet Hossain, Victor Sposito & Carys Evans
[Abstract ; Full text].
This paper reports on two models that have been developed
using ArcView Model Builder
to map suitability for agricultural and urban land uses. Both models use a
GIS-based multiple criteria modelling approach combining empirical data with
experts' judgement. The Agricultural Suitability Model considers soil,
landscape and climate criteria; whereas the Urban Buildability Model assesses biophysical,
socio-economic and spatial phenomena to define locational suitability from a sustainable
development perspective. These models have been used to help develop strategic
development plans for several rural shires in
2(2)
:
Editorial - A brief history of metropolitan
planning in Melbourne, Australia by Jun Tsutsumi & Ray Wyatt
[Abstract ; Full text].
... the history of Melbourne's
metropolitan planning, which we will examine here on the basis that one needs
to look backwards to see where a city is currently positioned, as well as the
direction in which it could go in the future. We will then highlight some of
the insights provided by the theme papers, along with some of their
policy-relevant implications
Time series analysis of the skyline and employment
changes in the CBD of Melbourne by Jun Tsutsumi & Kevin O'Connor
[Abstract ; Full text].
This paper covers historical and micro level analyses of
floor space and employment in the CBD of Melbourne during the last two decades.
The time-series patterns and processes of high-rise building provision in the
CBD are also focused on. The CBD has experienced very complicated changes over
the last two decades. While particular types of urban functions, say finance
and insurance offices and many retail activities, have been dispersed to the
suburbs, newly emerged activities have replaced the old and traditional ones.
Despite the growth of suburban cores (office and retail), the CBD of Melbourne
has still kept its strong centrality through a role as the main location of
office activity in particular. Historical and micro level viewpoints provide a
new understanding of the metropolitan area. The key question must be ‘Why is the role of the CBD of
Melbourne still so strong, given substantial dispersal of population and
economic activity to suburban locations?'
The development of diverse suburban activity centres in
[Abstract ; Full text].
Sustainable urban form presents the most
critical problem facing most metropolitan areas following the suburbanization
of urban functions in the 20th Century.
The changing socio-economic structure of
[Abstract ; Full text].
This paper explores a new phase of urban development based
on a case study of
A comparative study of metropolitan multi-nucleation:
Suburban centres and commuter flows within the metropolitan areas of
[Abstract ; Full text].
The suburbanization of various functions has generated
“Suburban Downtowns” or typical “Edge Cities” in
GIS-based evaluation of Personal Rapid Transit (PRT) for
reducing car dependence within
[Abstract ; Full text].
Metropolitan
Accessibility analysis for housing development in
Singapore with GIS and multi-criteria analysis methods by Xuan Zhu, Suxia Liu & Mun-ching Yeow
[Abstract ; Full text].
This paper presents a study on accessibility analysis for
public housing development in Choa
Chu Kang/Bukit Panjang
area,
The spatial analysis of spectral data: extracting the
neglected data by Brian Lees
[Abstract ; Full text].
Remotely sensed data are a key input to GIS-based spatial
decision support systems for land cover and land use application areas. One of
the major sources of error in the input of processed remotely sensed data to
GIS is in the process of classification. Particularly important is the degradation
of the data from the interval to nominal level of measurement. This is less
significant in cultural landscapes where boundaries predominate, but it becomes
an important source of error in natural, and disturbed natural, environments
where gradients exist. Use of the G i
* local statistic as an alternative approach to processing remotely sensed data
proved very successful, replicating the level of discrimination achieved by
conventional classification and field labelling in a much shorter time, whilst
avoiding the errors associated with conversion of the data from the interval to
nominal level of measurement.
2(1):
[Abstract ; Full text].
Authors from many parts of the world are
represented in this, the first issue for volume two of Applied GIS .
Indeed, two of the papers have authors from across the globe, suggesting that
international collaboration is surely very productive.
Validation and sensitivity analysis of a mineral
potential model using favourability functions by Tsehaie Woldai, Alberto Pistocchi & Sharad Master
[Abstract ; Full text].
An area in the Magondi
Belt,
Ore grade estimation of a limestone deposit in India
using an Artificial Neural Network by S. Chatterjee, A. Bhattacherjee, B. Samanta & S. K. Pal
[Abstract ; Full text].
This study describes a method used to improve ore grade
estimation in a limestone deposit in
The effect of cell resolution on depressions in Digital
Elevation Models by Paul A. Zandbergen
[Abstract ; Full text].
A proper understanding of the occurrence of depressions is
necessary to understand how they affect the processing of a Digital Elevation
Model (DEM) for hydrological analysis. While the effect of DEM cell resolution
on common terrain derivatives has been well established, this is not well
understood for depressions. The more widespread availability of high resolution
DEMs derived through Light Detection and Ranging (LIDAR) technologies presents
new challenges and opportunities for the characterization of depressions. A
6-meter LIDAR DEM for a study watershed in
Spatial data compression and denoising via wavelet transformation by
Biswajeet Pradhan, Sandeep
Kumar, Shattri Mansor, Abdul Rahman, Ramli
Abdul, Rashid B. & Mohamed Sharif
[Abstract ; Full text].
A new interpolation wavelet filter for TIN data compression
has been applied in two steps, namely splitting and lifting. In the splitting
step, a triangle has been divided into several sub-triangles and the elevation
step has been used to ‘modify' the point values (point coordinates for geometry)
after the splitting. This data set is then compressed at the desired locations
by using second-generation wavelets: scalar wavelets constructed by using a
lifting scheme. Application of the compressed data compares favourably with
results derived using the original (and much larger) TIN data set.
Spatial information for Integrated Coastal Zone
Management (ICZM): An example from the artificial Entrance
Channel of the Gippsland Lakes, Australia by Peter Wheeler
[Abstract ; Full text].
Since 1889, an artificial entrance channel, cut through the
swash aligned Holocene sandy outer barrier system known as the
2005
-
1(3):
Editorial by
Jim Peterson & Ray Wyatt
[Abstract ; Full text].
The first volume of Applied
GIS is now complete. I would like to thank the staff of
Analysis of pre/post flood bathymetric change using a
GIS: A case study from the
[Abstract ; Full text].
In late June 1998, a damaging flood
event occurred at Lakes Entrance (
Land use history of central Luleå: A case study in the use of
historical maps together with modern geographic municipal information by
Christian Lundberg & Lynette Peterson
[Abstract ; Full text].
The modern Luleå
harbour-side dates back to 1649 when the old city was abandoned because its
harbour-side and approaches had become too shallow to be useful. This
shallowing, due to glacio-isostatic
rebound, affects the new town also, but the results have been mitigated by
coastal engineering. As a result of uplift and engineering, former harbour-side
land is now far enough from the present shoreline for any maritime artifacts that might lie beneath
them to be unsuspected.
Spatial data integration for
classification of 3D point clouds from digital photogrammetry by Joshphar Kunapo
[Abstract ; Full text].
Under increased urban settlement density, access to a high
resolution (land-parcel scale) bare-earth Digital Elevation Model (DEM) is a
pre-requisite for much decision support for planning: stormwater assessment,
flood control, 3D visualisation, automatic delineation of flow paths, sub
watersheds and flow networks for hydrological modelling. In these terms, a
range of options face the DEM-building team. Apart from using necessarily expensive
field survey, or use of out-of-date terrain information (usually in the form of
digital contours of less-than-satisfactory interval) the model will be built
from point-clouds. These will have been assembled via digital photogrammetry or acquisition of LiDAR data. In the first
instance, both these data types soon yield a model that is known as a digital
surface model (DSM). It includes any buildings, vehicles, vegetation (canopy
and understory), as well as the “bare ground". To generate the required
'bare-earth' DEM, ground and non-ground features/data points must be
distinguished from each other so that the latter can be eliminated before DEM
building. Existing methods for doing this are based on data filtering routines,
and are known to produce errors of omission and commission. Moreover, their
implementation is complex and time consuming.
Modelling the driving forces of
[Abstract ; Full text].
This paper demonstrates a flexible
implementation of rules to control the simulation of urban development of
Bathymetric evolution at a coastal inlet after
channel-edge groyne emplacement: A case study from the
[Abstract ; Full text].
Digital capture and analyses of
time-series (1941-2005) digital elevation models (DEMs), developed for the
Gippsland Lakes artificial entrance area (situated in Victoria, Australia) from
analogue hydrographic charts, allows the long-term bathymetric results of rubble
training wall (or ‘groyne') emplacement in the Reeves Channel to be examined.
Reeves Channel form has progressively become sinuous, and extensive flood-tide
delta shoaling areas have also developed since ‘groyne field' installation. It
is argued that deviance from original Reeves Channel groyne emplacement design
(proposed by a Royal Commission report in 1927) may have contributed heavily to
the time-series development of Reeves Channel sinuosity and flood-tide delta
accretion.
1(2):
[Abstract ; Full text].
Real-time analysis of data reported by environmental
monitoring networks poses a number of interesting challenges, one of which is
the handling of point measurements of phenomena that display some spatial
continuity. This is the case for many variables, such as atmospheric and
aquatic pollutant levels, background radiation levels, rainfall fields,
temperature and seismic activity, to name but a few.
Introduction to the Spatial Interpolation Comparison
(SIC) 2004 Exercise and Presentation of the Datasets by G.
Dubois & S. Galmarini
[Abstract ; Full text].
The Spatial Interpolation Comparison (SIC) 2004 exercise was
organised during the summer 2004 to assess the current know-how in the field of
“automatic mapping”. The underlying idea was to explore the way algorithms
designed for spatial interpolation can automatically generate maps on the basis
of information collected regularly by monitoring networks. Participants to this
exercise were invited to use some prior information to design their algorithms
and to test them by applying the software code to two given datasets.
Estimation errors were used to assess the relative performances of the
algorithms proposed. Participants were not only invited to minimize estimation
errors but also to design the algorithms so as to render them suitable for
decision-support systems used in emergency situations. The data used in this
exercise were daily mean values of gamma dose rates measured in
Using Ordinary Kriging to Model Radioactive Contamination
Data by Elena Savelieva
[Abstract ; Full text].
This paper deals with an application of ordinary kriging (OK) for spatial
interpolation of data in a completely automatic (“one-click mapping”) manner.
The important set of kriging
parameters (semivariogram
model, search strategy, etc.) were tuned based on the prior characteristics of
the phenomenon considered. The prior information provided as 10 sets of
monitoring observations taken at different days was used to analyse and model
the spatial correlation of the phenomenon. Furthermore, the prior information
was expected to be consistent within a rather long time range and therefore
assumed to reflect the structure of the contamination pattern at any given day.
The approach applied here gave satisfactory results for both routine and
emergency data sets. The benefits and drawbacks of the kriging model were well illustrated in the study.
Ordinary kriging can be
considered as a real candidate for the implementation in a decision support
system.
Mapping Radioactivity from Monitoring Data: Automating
the Classical Geostatistical Approach by Edzer J. Pebesma
[Abstract ; Full text].
In the context of a comparison of spatial prediction
algorithms, we applied the classical geostatistical
approach to see how well it would automate, and how well it performed in case
of an unexpected anomaly. In case of a test without anomaly, the method
performed well. In the anomaly case, automatic variogram modelling was hindered seriously, and in
terms of RMSE best results were obtained by using the variogram from the test data without the anomaly.
Although the 10 days of available training data showed a strong temporally
persistent spatial pattern, cokriging
did not improve predictions.
Automatic Mapping in the Presence of Substitutive Errors:
A Robust Kriging Approach by Baptiste Fournier & Reinhard Furrer
[Abstract ; Full text].
Interpolation of a spatially correlated random process is
used in many scientific domains. The best unbiased linear predictor (BLUP),
often called kriging
predictor in geostatistical
science, is sensitive to outliers. The literature contains a few attempts to robustify the kriging predictor,
however none of them is completely satisfactory. In this article, we present a
new robust linear predictor for a substitutive error model. First, we derive a
BLUP, which is computationally very expensive even for moderate sample sizes. A
forward search type algorithm is used to derive the predictor resulting in a
linear likelihood-weighted mean procedure that is robust with respect to
substitutive errors.
Automatic Mapping of Monitoring Data by
Søren Lophaven, Hans Bruun Nielsen & Jacob Søndergaard
[Abstract ; Full text].
This paper presents an approach, based on universal kriging, for automatic mapping of
monitoring data. The performance of the mapping approach is tested on two
datasets containing daily mean gamma dose rates in
Bayesian Automating Fitting Functions for Spatial
Predictions by Monica Palaseanu-Lovejoy
[Abstract ; Full text].
A Bayesian predictive model for automating mapping of
background radiation has the advantage of fully accounting for all
uncertainties in the inferred data. Ten training datasets of background
radiation were used to set up the model. The model is robust for data
containing only close outliers but fails to accurately predict values when the
input data is contaminated with extreme outliers, which are the result of a
different random underlying process than the background data. For an integrated
decision support system for automating mapping when data contamination is expected,
a two stage approach is required in which background data are modeled with one set of equations
and the contaminated data with a different set of equations.
Fast Spatial Interpolation using Sparse Gaussian
Processes by Ben Ingram, Lehel Csató
& David Evans
[Abstract ; Full text].
The estimation of the natural ambient radioactivity in this
entry to the Spatial Interpolation Comparison 2004 (SIC2004) uses Gaussian
processes (GP's) to predict the underlying dispersal process. GP's enable us to
predict easily levels of radioactivity at previously unseen locations and in
addition they allow us to assess the uncertainty in the predicted value. To
speed up computation time, which is cubic in the number of examples, a
sequential, sparse implementation of the Gaussian process inference (SSGP) was
used together with a Gaussian observational noise assumption. The examination
of the available data led to a covariance function which is a mixture of
exponential and squared-exponential functions. The mixture was chosen so that
it incorporates both the local ambiguity in the data and also at the same time
it captures the larger-scale variation of the observations.
Interpolation of Radioactivity Data Using Regularized
Spline with Tension by Jaroslav Hofierka
[Abstract ; Full text].
Regularized Spline with Tension was used to interpolate two
data sets representing radioactivity measurements at 200 locations. A
cross-validation analysis showed that the size of the training data sets was
too low to find optimal parameters using the cross-validation procedure. The
resulting surfaces were strongly smoothed and less realistic than expected. Therefore
empirical interpolation parameters were used to interpolate the data. Despite
the fact that this empirical selection did not produced interpolation results
with a lower overall predictive error, it preserved better local fluctuations
and anomalies of the phenomenon. The detection of these features is important
in radioactivity monitoring and emergency situations. The poor reliability of
cross-validation was also confirmed by evaluation data set. It was concluded
that the optimization of interpolation parameters cannot rely on
cross-validation when the modeled
phenomenon is not sufficiently sampled. The sampling density should be
sufficient to represent spatial variations of the phenomenon and, at the same
time, allow the optimization of interpolation parameters using automated
procedures.
Automated Mapping using Multilevel B-Splines by
Anatoly A. Saveliev, Andrey V. Romanov & Svetlana
S. Mukharamova
[Abstract ; Full text].
This paper describes application of multilevel B-Splines
approximation (MBA) algorithm to the SIC2004 exercise as a high performance
automatic mapping means in emergency situations. MBA method was compared with kriging, and various flexible MBA
method's tuning “controls”
were proposed and discussed. Outliers automatic detection and delineation
techniques considered could be used to process outliers without the loss in
performance. Prior data were used to adjust method parameters and discover the
pattern of spatial correlation. The interpolation algorithm development did not
assume any information about the phenomena in addition to values given.
Spatial Interpolation of Natural Radiation Levels with
Prior Information using Back-propagation Artificial Neural Networks by
J.P. Rigol-Sanchez
[Abstract ; Full text].
We propose artificial neural networks (ANNs) as a tool for
automatic mapping of daily observations of environmental data. A feed-forward
back-propagation neural network for estimating daily natural radiation
measurements at unsampled
locations using prior information was developed. Feed-forward back-propagation
networks were trained to learn: (a) the relationship between daily measurements
and their spatial coordinates, and (b) the relationship between daily
measurements made at one site and measurements made at the six surrounding
closest sites. Results of the study indicate that ANNs can be used for
automatic mapping of environmental (background) data with moderate success. ANN
models for spatial interpolation can successfully incorporate prior information
into the estimation process. However, the ANN approach to automatic mapping of
environmental data presented here was clearly inappropriate for dealing with
outliers. Results obtained suggest that developing two different models for
estimating background values and extreme values, respectively, might be a
potentially more successful approach to automatic mapping of environmental
data.
Spatial Prediction of Radioactivity using General
Regression Neural Network by Vadim Timonin,
Elena Savelieva
[Abstract ; Full text].
This work describes an application of General Regression
Neural Network (GRNN) to spatial predictions of radioactivity. GRNN belongs to
a class of neural networks widely used for mapping continuous functions. It is
based on a non-parametric (kernel) Parzen-Rosenblatt
density estimator. The kernel size is the only tuning parameter, and it allows
the user to implement a GRNN in an automatic mode. An important advantage of
the GRNN is its very simple and fast training procedure. The most important
drawbacks are high smoothing and dependence on the spatial density of the
monitoring data set. The current case study is performed on the SIC2004 data
sets, and the results obtained here can be compared with those obtained by the
other participants using other approaches.
Investigation of Two Neural Network Methods in an
Automatic Mapping Exercise by Sridhar Dutta, Rajive
Ganguli & Biswajit Samanta
[Abstract ; Full text].
This paper investigates the performance of two neural
network (NN) methods viz. a radial basis function network (RBFN) and a
multilayer feed forward network (MFFN) to predict the radioactivity levels at a
given test site. A comparative evaluation of the two networks is done using
Root mean square error (RMSE), Pearson's r
, Mean error (ME) and Mean Absolute error (MAE). It was found
that the RBFN performed marginally better compared to the other method
Support Vector Regression for Automated Robust Spatial
Mapping of Natural Radioactivity by Alexei Pozdnoukhov
[Abstract ; Full text].
This paper presents an application of Support Vector
Regression method for the prediction of an environmental variable such as the
level of natural radioactivity. The basics of the method are described, and
some practical considerations are presented, including the meaning of the
method's parameters and their influence on the model. The use of the prior data
is discussed. It is shown how to include the information on the variance of the
measurements into the model. The use of cross-validation for tuning the
parameters of the algorithm is presented. Some ideas for detecting the unusual
training samples with SVR are discussed. Generally, the case study illustrates
the usefulness of the considered approach for automated spatial mapping tasks
in the presence of prior data.
1(1):
Editorial
by Jim Peterson
[Abstract ; Full text].
Applied
GIS – another peer-reviewed applied (social and environmental)
science research journal to keep up with? Well, yes. However, Applied GIS meets a
number of urgent needs in an admittedly crowded science-journal market.
Harbour-side land parcel land-use changes: Significance
in re-development planning permit appraisal in
[Abstract ; Full text].
Results are presented of spatial query at the land parcel
level of a (digital) spatial database, referring to the twentieth century
Harbour-side zone of the
Suburban socio-spatial polarisation and house price
change in
[Abstract ; Full text].
This study examines the process and pattern of spatial
polarisation in
Improving spatial decision support systems:
Methodological developments for natural resources and land management by Hedia Chakroun, Goze
Bertin Benie
[Abstract ; Full text].
The use of geographic information
systems (GIS) in the past two decades helped in formulating and solving spatial
decision-making problems. In spite of their huge capacities in the acquisition
and the storage of spatial data, GIS have some limits when it is a matter of
solving semi-structured problems that represent most real-world spatial
decision cases. The improvement of GIS analytic capacities can provide support
required in multiple decision-making phases. We use advanced spatial analysis
techniques applied to raster data representing a set of constraints that may be
encountered in a land management project. Digital maps and a digital elevation
model (DEM) have been used to produce the constraint spatial database for the
case study. Each spatial feature had been subject to an evaluation process and
a utility value was given to represent its tolerance to the management project
according to the constraints identified previously. Results obtained from this
methodology have been compared to conventional cases of suitability mapping
from the original set of constraint maps. Results show that suitability maps for
the management project derived from this study represent multiple scenarios
leading to the improvement of the design and choice phases of decision-making
process.
Towards automation of impervious surface mapping using
high resolution orthophoto by Joshphar Kunapo, Pua
Tai Sim & Shobhit
Chandra
[Abstract ; Full text ].
Information on the amount and pattern of impervious surface
is important for hydrological modelling of urban areas. As cities expand and/or
develop, hydrologic models will become outdated unless information on
impervious surfaces is kept up to date. At the moment, the mapping teams are
faced with choosing from among a range of alternative approaches/tools/software
products to achieve this. We report here, the results of experiments conducted
for a range of mapping approaches applied to high resolution orthophoto imagery covering part
of the residential zone of Monash City, a local government area in Melbourne, Victoria,
Australia. The application of the Expert Classification (EC) or Feature Analyst
(FA) approaches requires initial human involvement to set the knowledge/learner
function, which, then can be applied to any areas of similar spectral patterns.
The Feature Analyst (FA) approach yielded superior results compared these
'pixel-by-pixel' methods. All of these approaches refer to mapping in aid of
distributed and connectivity modelling. In the absence of access to EC or FA
tools, application of the (sampling-based) Precision Method (PM), (after
careful consideration of sampling stratification) will offer total impervious
surface data-input estimates for lumped hydrological modelling.