ABSTRACTS IN ENGLISH - Applied
GIS
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 ;
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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 ;
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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):
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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
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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
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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
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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 ;
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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
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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
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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
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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
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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 ;
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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
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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
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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
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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
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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
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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
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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 ;
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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
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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
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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.
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