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December, 2009
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Refereed Papers
Zhang, C. & Fraser, C.S. 2009. An Improved
Approach for DSM Generation from High-Resolution Satellite Imagery. Journal of Spatial Science, Vol. 54, No. 2. 
Salah, M. et al.
2009. Evaluation of the Self-Organizing Map Classifier for Building
Detection from Lidar Data and Multispectral
Aerial Images. Journal of Spatial Science, Vol. 54, No. 2.
Mitchell, D.P. 2009. Land Administration Trends and their
Implications for Australian Natural Resource Management. Journal of Spatial Science, Vol. 54, No. 2.
Coutts, B.J. & Grant, D.B. 2009. The New Zealand Surveyor – the
21st Century. Journal of Spatial Science, Vol. 54, No. 2.
Liao, E. et al. 2009. Developing a Web-Based
e-Research Facility for Socio-Spatial Analysis to Investigate Relationships
between Voting Patterns and Local Population Characteristics. Journal of
Spatial Science, Vol. 54, No. 2.
Cromley, R.G. & Ebenstein,
A.Y. 2009. Estimating Components of Population Change from Census Data for
Incongruent Spatial/Temporal Units and Attributes. Journal of Spatial
Science, Vol. 54, No. 2.
Gaisbauer, C. 2009. Strategies
for Decentralized ad-hoc Trip Planning. Journal of Spatial Science,
Vol. 54, No. 2.
Professional Papers
Harvey, B.R. 2009. Constraint Equations in Cadastral Modelling.
Journal of Spatial Science, Vol. 54, No. 2.
Abstracts
Refereed Papers
An Improved Approach for DSM Generation from
High-Resolution Satellite Imagery
C. Zhang
GIS Center of Excellence
South Dakota
State
University
Brookings,
SD
57007
USA
chunsun.zhang@sdstate.edu
C. S. Fraser
Department of Geomatics
University of
Melbourne
Melbourne, Vic 3010
Australia
c.fraser@unimelb.edu.au
Abstract
This paper
develops an improved approach to digital surface model (DSM) generation from
high-resolution satellite imagery (HRSI). The approach centres upon an
image matching strategy that integrates feature
point, grid point and edge matching algorithms within a coarse-to-fine
hierarchical process. The starting point is a knowledge
of precise sensor orientation, achieved in this case through bias-compensated
rational polynomial coefficients (RPCs), and the
DSM is sequentially constructed through a combination of the matching results
for feature and grid points, and edges at different image pyramid levels. The
approach is designed to produce precise, reliable and very dense DSMs which preserve information on surface
discontinuities. Following a brief introduction to sensor orientation
modelling, the integrated image matching algorithms and DSM generation stages
are described. The proposed approach is then experimentally tested through
the generation of a DSM covering the Hobart area
from a stereo pair of IKONOS Geo images. The accuracy of the resulting
surface model is assessed using both ground checkpoints and a lidar DSM, with the results indicating that for
favourable imagery and land cover, a heighting
accuracy of 2 - 4 pixels can be readily achieved. This result validates the
feasibility of the developed approach for DSM production from HRSI.
Evaluation
of the Self-Organizing Map Classifier for Building Detection from Lidar Data and Multispectral
Aerial Images
M. Salah
J. Trinder
School of
Surveying and
Spatial Information Systems,
The University of
New South
Wales, Sydney
NSW 2052
Australia
m.gomah@unsw.edu.au
j.trinder@unsw.edu.au
A. Shaker
Department of Surveying Engineering,
Shoubra Faculty of
Engineering,
Benha University
Egypt
ahmshaker@link.net
Abstract
Integration of
aerial images and lidar data compensate for the
individual weaknesses of each data set when used alone, thus providing more
accurate classification of terrain cover, such as buildings, roads and green
areas, and advancing the potential for automation of large scale digital
mapping and GIS
database compilation. This paper presents work on the development of
automatic feature extraction from multispectral
aerial images and lidar data. A total of 22 feature
attributes have been generated from the aerial image and the lidar data which contribute to the detection of the
features. The attributes include those derived from the Grey Level
Co-occurrence Matrix (GLCM), Normalized Difference Vegetation Indices (NDVI),
and standard deviation of elevations and slope. A Self-Organizing Map (SOM)
was used for fusing the aerial image, lidar data
and the generated attributes for building detection. The classified images
were then processed through a series of image processing techniques to
separate the detected buildings. Results show that the proposed method can
extract buildings accurately. Compared with a
building reference map, 95.5 percent of the buildings were detected with a
completeness and correctness of 83 percent and 80 percent respectively for
buildings around 100m2 in area; these measures increased to 96
percent and 99 percent respectively for buildings around 1100m2 in
area. Further, the contributions of lidar
and the individual attributes to the quality of the classification results
were evaluated.
Land Administration Trends and
their Implications for Australian Natural Resource Management
D.P. Mitchell
Land Centre
School of Mathematical and Geospatial Sciences
SET Portfolio, RMIT
University
GPO Box 2476V
Melbourne 3001
Australia
d.mitchell@rmit.edu.au
Abstract
Over the last few
decades there has been a dramatic increase in the productive use of natural
resources in Australia, and a
significant deterioration in the condition of natural resources. Recent
approaches to improving natural resource management (NRM) aim to improve land
use through voluntary schemes, economic incentives, and the un-bundling of
rights to land and resources. However, these initiatives are constrained by
limitations in the amount of local and regional land and natural resources
information. This paper argues that as land administration systems (LAS)
further develop they provide improved tools and mechanisms that can assist
the goals of NRM. Benefits will be achieved through better administration of
property rights and restrictions, improved land and natural resources
information, and improved land use management.
The New Zealand Surveyor – the
21st Century
B. J. Coutts
School of
Surveying
University of
Otago
P O Box 56
Dunedin 9016
New Zealand
brian.coutts@otago.ac.nz
D. B. Grant
Surveyor General
Land Information New Zealand
P O Box 5501
Wellington 6501
New Zealand
dgrant@linz.govt.nz
Abstract
This paper charts the
development of the unique nature of the New Zealand Surveyor from navigator
and early explorer to the multi-discipline land development consultant of the
21st Century. The structural changes that have taken place
in government institutions are identified with an explanation of why these
changes were necessary. The consequential effects on the survey
profession are also outlined, together with an assessment of how the
principal surveying professional body has responded.
Developing a Web-Based
e-Research Facility for Socio-Spatial Analysis to Investigate Relationships
between Voting Patterns and Local Population Characteristics
E. Liao
T- K. Shyy
R. J. Stimson
UQ Social Research Centre
Institute for Social Science
Research
The
University of
Queensland
Brisbane,
Queensland 4072
e.liao@uq.edu.au
t.shyy@uq.edu.au
r.stimson@uq.edu.au
Abstract
This paper describes the
development of an e-research facility for socio-spatial analysis. It is
illustrated with the example of a prototype Web-based GIS and statistical
application for the analysis, modelling and visualisation of the
relationships between patterns of voting at the 2007 Australian federal
election and the demographic and socio-economic characteristics of local
populations using 2006 census data. The facility incorporates a web-based GIS which can
generate maps displaying patterns of voting for political parties across
polling booths with overlay data showing the population characteristics
living within the surrounding polling booth catchments. Various
classification approaches including equal interval, quantile,
median-based natural breaks, and location quotients can be used to generate
different map displays. Statistical analysis functionality - such as
regression analysis, cluster analysis and discriminant
analysis - enables researchers to conduct on-line statistical modelling and
the visualisation of outputs. This prototype facility not only gives
researchers and students on-line access to socio-spatial datasets through a
metadata directory, but also enhances the capacity and capability of
researchers and students to undertake spatially integrated social science
research.
Estimating
Components of Population Change from Census Data for Incongruent
Spatial/Temporal Units and Attributes
R. G. Cromley
Department of
Geography
Campus Unit 4148,
215 Glenbrook
Rd.
University of
Connecticut
Storrs,
CT
06269-4148
USA
robert.cromley@uconn.edu
A. Y. Ebenstein
Institute for Quantitative
Social Science
Harvard
University
USA
D. M. Hanink
Department of
Geography
University of
Connecticut
USA
Abstract
When calculating the
components of population change over time, the spatial units of analysis must
remain constant. However, the boundaries of these units often change
from one census to the next. Another limiting factor is the absence of
data values for the time period. Net migration figures might be
available for a five year interval in a census but not for a twenty year
interval. GIS and areal
interpolation are used here to rectify boundary changes that occur from one
census to the next and shift-share analysis is used to estimate the
components of population change from the census data. These
methods are applied to a county level study of population change in China between 1982 and
2000.
Strategies for Decentralized
ad-hoc Trip Planning
C. Gaisbauer
Institute for Geoinformation and Cartography
Vienna
University of Technology
Austria.
gaisbauer@geoinfo.tuwien.ac.at
S. Winter
Department of Geomatics
The
University of
Melbourne
Parkville,
Victoria 3010
Australia.
winter@unimelb.edu.au
Abstract
This paper considers a set
of vehicles, called hosts, forming a transportation network, and a set of
mobile transportation clients such as pedestrians. The paper focuses on the
problem of clients choosing rides with hosts in an ad-hoc manner, i.e.,
without calling a central service. For this purpose, clients and nearby hosts
are enabled to negotiate via short distance radio, making it likely that
clients will not find a complete ride to their destination instantly. Instead,
they take rides to intermediate locations, in expectation of finding
connecting rides from there on. This paper studies the clients’ dilemma to
assess intermediate locations. It proposes a heuristic that outperforms the
strategy of strictly following a predefined route (for example, the geometric
shortest one). Furthermore, the proposed heuristic is expanded to incorporate
a-priori data about the spatially inhomogeneous – yet repetitive – mobility
behaviour of potential hosts as it is typical in urban traffic. It is shown
that the average travel times of clients can be further reduced through the
prediction of host availability at intermediate locations.
Professional Paper
Constraint
Equations in Cadastral Modelling
B. R. Harvey
School of
Surveying and Spatial
Information Systems
University of
New South Wales
UNSW Sydney NSW 2052
Australia
b.harvey@unsw.edu.au
Abstract
Cadastral modelling uses the
cadastral data including bearings and distances of boundary lines to
calculate coordinates of boundary corners and associated marks, and to
evaluate the data. This paper shows that at sites where several boundary
corners are intended to be on a straight line a Least Squares adjustment of
the boundary data may cause the points to move away from one straight
line.
Methods of constraining
boundary corners to stay on straight lines, when that is desired, in a Least
Squares solution of cadastral boundary data are described in this paper. The
LS process and equations are given for constraining points to stay on a
straight line by using fixed 180° angle observations or by using parameter constraint
equations. Also, considered are multiple points on a line, parallel line
constraints and constraints to keep boundary points on a circular arc, where
appropriate. An example is given to demonstrate the application and effect of
the constraints.
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