December, 2006

Refereed Papers
Featherstone, W. E. (2006) Yet More Evidence for A North-South Slope in the Australian Height Datum, Journal of Spatial Science, Vol. 51, No. 2.

Wijaya, A. (2006) Comparison of Soft Classification Techniques for Forest Cover Mapping. Journal of Spatial Science, Vol. 51, No. 2.

Hayles, K. (2006) The use of GIS and cluster analysis to enhance property valuation modelling in rural Victoria. Journal of Spatial Science, Vol. 51, No. 2.

Zhang, C. & Li, W. (2006) Towards Rationalizing Protected-Area Designation in China Using a Web-Based Spatial Decision Support System, Journal of Spatial Science, Vol. 51, No. 2.

Special Feature – Hypersepctral Remote Sensing

Hill, M. J., Asner, G. P. & Held, A. A. (2006) The Bio-geophysical Approach to Remote Sensing of Vegetation in Coupled Human-Environment Systems – Societal Benefits and Global Context. Journal of Spatial Science, Vol. 51, No. 2.

Guo, J & Trotter, C. M. (2006) Assessing Light-Dependent Down-Regulation Of Photosynthesis Using the Photochemical Reflectance Index (PRI). Journal of Spatial Science, Vol. 51, No. 2.

Pfitzner, K., Bollhöfer, A. & Carr, G. (2006) A Standard Design for Collecting Vegetation Reference Spectra: Implementation And Implications for Data Sharing. Journal of Spatial Science, Vol. 51, No. 2.

Hueni, A & Tuohy, M. (2006) Spectroradiometer Data Structuring, Pre-Processing and Analysis – an IT Based Approach. Journal of Spatial Science, Vol. 51, No. 2.

Ferwerda, J., Skidmore, A. K., Van Wieren, S. & Prins, H. H. T. (2006) Soil N and P Affected Reflectance Signatures of Individual Colophospermum Mopane Leaves. Journal of Spatial Science, Vol. 51, No. 2.

Day, M. B., Taylor, G. R., Roff, A. M. & Mitchell, A. L. (2006) Hyperspectral Discrimination of Halophytic Vegetation as an Indicator of Stressed Arable Land. Journal of Spatial Science, Vol. 51, No. 2.

Huang, J-F. & Apan, A. (2006) Detection of Sclerotinia Rot Disease on Celery Using Hyperspectral Data and Partial Least Squares Regression. Journal of Spatial Science, Vol. 51, No. 2.

Dutkiewicz, A. & Lewis, M. (2006) Hyperspectral Discrimination of Sea Barley Grass and the Implications for Mapping Salinised Land. Journal of Spatial Science, Vol. 51, No. 2.

Robson, A. J., Wright. G. & Phinn, S. (2006) Using Field Spectroscopy and Quickbird Imagery for the Assessment of Peanut Crop Maturity and Aflatoxin Risk. Journal of Spatial Science, Vol. 51, No. 2.

Pfitzner, K. & Clifton, R. (2006) Integration of Airborne Casi and Gamma Ray Data for Mine Site Characterisation. Journal of Spatial Science, Vol. 51, No. 2.

Abstracts

Refereed Papers

Yet More Evidence for A North-South Slope in the Australian Height Datum

W E Featherstone

Western Australian Centre for Geodesy

Curtin University of Technology

GPO Box U1987, Perth, WA 6845

Australia

W.Featherstone@curtin.edu.au

Abstract

The results here add significantly to the body of evidence for a systematic north-south error in the Australian Height Datum (AHD). Previous studies based solely on Global Positioning System (GPS) and a gravimetric geoid model have suffered from the ‘inseparability problem’, where it is not possible to discriminate between errors in the AHD and geoid. Instead, this study compares horizontal gradients of the AUSGeoid98 regional gravimetric geoid model with totally independent astrogeodetically observed vertical deflections at 741 Laplace stations across Australia. These comparisons do not show any significant latitude-dependent residuals, thus significantly reducing the likelihood of a north-south slope in AUSGeoid98. Subsequently using GPS and AUSGeoid98, now that the inseparability problem has been addressed, there is very compelling evidence for a real north-south slope of ~1.5m in the AHD.

Comparison of Soft Classification Techniques for Forest Cover Mapping

A. Wijaya

Department of Natural Resource Management

International Institute for Geo-Information Science and Earth Observation (ITC)

Hengelosesstraat 99, 7500 AA Enschede

The Netherlands

wijaya06689@alumni.itc.nl

Abstract

Forest cover mapping is necessary to support sustainable forest management. One of the most important factors that cause deforestation comes from illegal logging. This study applied two soft classification techniques, i.e. fuzzy c-means and neural network, to classify forest cover for detecting illegal logging in the form of single tree felling. The classification results were compared to the conventional maximum likelihood classification using a confusion matrix. This study found the neural network resulted in a more accurate detection of single tree felling, followed by the maximum likelihood. The fuzzy c-means gave less satisfactory results due to a strong overlap between single tree felling and high density forest training classes.

The use of GIS and cluster analysis to enhance property valuation modelling in rural Victoria.

K. Hayles

School of Mathematical and Geospatial Science

RMIT University

GPO Box 2476V, Melbourne Victoria 3001

Australia

kelly.hayles@dse.vic.gov.au

Abstract

Rural property valuation is typically performed using manual techniques in Victoria, Australia. Regression analysis is a semi-automated approach to statistically define numerical models for property valuation, however there can be some bias in regression models developed without the determination of sub-markets (Watkins, 1998). Cluster analysis is a data driven technique to create sub-market groups that may help overcome this bias.

This paper reports on research which seeks to ascertain if a higher level of price estimation can be obtained using property segmented using cluster analysis compared to sub-markets created using geographical ‘a-priori’ techniques; in this research the Local Government Area to which each property belongs. The research has shown that an increase has occurred for one of the sets of models which used cluster analysis, however it is envisioned that automated techniques to model rural property values would at this stage not be used as the sole valuation technique even if the accuracy of the models were to be improved dramatically.

Towards Rationalizing Protected-Area Designation in China Using

a Web-Based Spatial Decision Support System

C. Zhang

W. Li

Department of Geography

Kent State University

P.O. Box 5190, Kent, OH 44242-0001

USA

zhangc@uww.edu

weidong6616@yahoo.com

M. J. Day

Department of Geography

University of Wisconsin – Milwaukee

USA

mickday@uwm.edu

Abstract

Designation of protected areas in populous areas of China has often been constrained by lack of public involvement and by failure to consider a comprehensive range of interrelated biophysical and social-economic factors. While recognizing the importance of designation of protected areas, most studies focus on management and administrative problems, yet offer little in the way of effective solutions to these limitations. This paper outlines user-friendly tools and techniques that can allow local governments to resolve these issues by using a Web-based Spatial Decision Support System. The development of a prototype in a case study demonstrates the feasibility of the approach.

Special Feature – Hypersepctral Remote Sensing

The Bio-geophysical Approach to Remote Sensing of Vegetation in Coupled Human-Environment Systems – Societal Benefits and Global Context

M. J. Hill

Department of Earth Systems Science and Policy

University of North Dakota, Grand Forks, ND, 58202-9007

USA

hillmjdr@hotmail.com

G. P. Asner

Department of Global Ecology

Carnegie Institution, 260 Panama Street, Stanford, CA 9430

USA

gasner@globalecology.stanford.edu

A. A. Held

CSIRO Office of Space Science and Applications

CSIRO Marine and Atmospheric Research, GPO Box 3023, Canberra, ACT, 2601

Australia

alex.held@csiro.au

Abstract

Hyperspectral remote sensing has promised a new era in quantitative measurement of key properties of terrestrial systems. The high information content, mechanistic relationships between reflectance spectra and canopy, leaf and molecular properties, and combination of computing power, algorithm maturity and highly quantitative methodology provides the basis for delivery of key information into new international research and observation frameworks seeking to provide societal benefits. This paper describes current capacity of global biophysical remote sensing and defines products that could be delivered by a new sensor. New products could be particularly useful in description of ecosystem services.

Assessing Light-Dependent Down-Regulation Of Photosynthesis Using the Photochemical Reflectance Index (PRI)

J. Guo

C. M. Trotter

Landcare Research

Private Bag 11052, Palmerston North

New Zealand

guoj@landcareresearch.co.nz

Abstract

Exposure to high light caused a down-regulation of photosynthesis and net photo-oxidative damage in three shade-acclimated species (‘Alectryon excelsus’, ‘Corynocarpus laevigatus’ and ‘Coprosma repens’). Analysis of the relationships between the photochemical reflectance index (PRI), an optical measure of excess light dissipation mediated by xanthophyll cycle, and photosynthetic parameters revealed that although PRI remains a measure of down-regulation of photosynthesis when photodamage occurs, the relationship can be expected to vary with changes in growth habitat. Pigment analysis indicates that this is likely due to changes in the xanthophyll cycle pool and carotenoids/chlorophyll ratio. This result may have important implications for the interpretation of PRI measured under different growth light conditions.

A Standard Design for Collecting Vegetation Reference Spectra: Implementation And Implications for Data Sharing

K. Pfitzner

A. Bollhöfer

G. Carr

Environmental Research Institute of the Supervising Scientist

Supervising Scientist Division

Department of the Environment and Heritage

GPO Box 461 Darwin 0801 NT

Australia

kirrilly.pfitzner@deh.gov.au

Abstract

Spectral signatures represent complex physical and biophysical relationships. Consideration and documentation of potential variables affecting these signatures are essential in obtaining meaningful spectra. A lack of standardised procedures and metadata collection has limited the transfer of spectra from one application to another. Here we describe the design and implementation of a standard method for the collection of spectral data and associated metadata. A specific application for revegetation assessment and monitoring is described. The concept of collecting consistent and accurate spectral data while minimising the influence of potential extraneous variation is relevant to field spectrometry in all environments and is particularly important for ecological applications.

Spectroradiometer Data Structuring, Pre-Processing and Analysis – an IT Based Approach

A. Hueni

M. Tuohy

Institute of Natural Resources

Massey University, Private Bag, Palmerston North 5301

New Zealand

a.hueni@massey.ac.nz

m.tuohy@massey.ac.nz

Abstract

Hyperspectral data collection results in huge datasets that need pre-processing prior to analysis. A review of the pre-processing techniques identified repetitive procedures with consequently a high potential for automation. Data from different hyperspectral field studies were collected and subsequently used as test sets for the described system. A relational database was utilized to store hyperspectral data in a structured way. Software was written to provide a graphical user interface to the database, pre-processing and analysis functionality. The resulting system provides excellent services in terms of organised data storage, easy data retrieval and efficient pre-processing. It is suggested that the use of such a system can improve the productivity of researchers significantly.

Soil N and P Affected Reflectance Signatures of Individual Colophospermum Mopane Leaves

J. Ferwerda

School of Mathematical and Geospatial Sciences

RMIT University; GPO Box 2476V; Melbourne

Australia and

ITC

P.O. Box 6, 7500 AA Enschede

The Netherlands

Jelle.ferwerda@rmit.edu.au

A. K. Skidmore

ITC

P.O. Box 6, 7500 AA Enschede

The Netherlands and

Wageningen University

Bornsesteeg 69, 6708 PD Wageningen

The Netherlands

S. Van Wieren

H. H. T. Prins

Wageningen University

Bornsesteeg 69, 6708 PD Wageningen

The Netherlands

Abstract

Reflectance and derivative spectra of greenhouse-grown mopane (Colophospermum mopane) were analyzed to investigate whether the interactive effect of soil phosphorus and nitrogen treatments on plant-chemical composition can be detected using non-destructive techniques. Reflectance spectra were affected by changes in soil nitrogen. Derivative spectra showed significant differences as a result of nitrogen and phosphorus treatment. Several spectral bands that showed different spectral signatures between soil treatments also showed significant correlation to condensed tannin, phosphorus and nitrogen concentration in mopane leaves. This shows the potential to detect the effect of soil properties on the plant’s physiology with hyperspectral remote sensing.

Hyperspectral Discrimination of Halophytic Vegetation as an Indicator of Stressed Arable Land

M. B. Day

G. R. Taylor

A. M. Roff

A. L. Mitchell

CRC for Spatial Information, School of Biological Earth and Environmental Sciences

University of New South Wales, Sydney, 2052, NSW

Australia

m.day@student.unsw.edu.au

g.taylor@unsw.edu.au

adam.roff@unsw.edu.au

a.mitchell@unsw.edu.au

Abstract

The spectral properties of eleven Australian halophytic grass species were analysed for key spectral characteristics to assist in hyperspectral image interpretation and mapping. Six halophyte species were successfully mapped using hyperspectral imagery over an area suffering from dry-land salinity in central west NSW. The resultant class map of halophytes was statistically compared to interpolated electrical conductivity data via a confusion matrix. Variations in the spatial abundance of different halophyte species are shown to significantly reflect the level of landscape stress in terms of salt scalding and electrical conductivity. This illustrates the ability of such technology to map environmental stress as indicated by halophyte populations.

Detection of Sclerotinia Rot Disease on Celery Using Hyperspectral Data and Partial Least Squares Regression

J-F. Huang

Institute of Agricultural Remote Sensing & Information Application

Huajiachi Campus

Zhejiang University, Hangzhou, 310029, Zhejiang

China and

Faculty of Engineering and Surveying & Australian Centre for Sustainable Catchments

University of Southern Queensland, Toowoomba 4350 QLD

Australia

hjf@zju.edu.cn

A. Apan

Faculty of Engineering and Surveying & Australian Centre for Sustainable Catchments

University of Southern Queensland, Toowoomba 4350 QLD

Australia

apana@usq.edu.au

Abstract

There is a need to detect and assess the incidence of Sclerotinia rot disease in celery (Apium graveolens). In this study, we examined the potential of hyperspectral sensing to detect the symptoms of this disease in celery crop. Using a portable spectrometer, sample measurements of diseased and healthy leaves were collected from celery leaves in the field. Both raw and transformed spectral data were used in the development of Partial Least Squares regression models. The cross-validated results showed that the incidence of disease on celery could be predicted using the raw spectra and the first and second derivative data, with prediction errors ranging from 11.08 to 13.62 percent. The visible and near-infrared wavelengths (400-1300nm) produced similar detection ability with that of the full range wavelengths (400-2500nm).

Hyperspectral Discrimination of Sea Barley Grass and the Implications for Mapping Salinised Land

A. Dutkiewicz

M. Lewis

School of Earth and Environmental Sciences

The University of Adelaide

PMB1 Glen Osmond, SA 5064

Australia

anna.dutkiewicz@adelaide.edu.au

Abstract

Sea barley grass (Hordeum marinum) is considered an important early indicator of emerging soil salinity. Saline areas that have good cover of salt tolerant plants are difficult to map with broadband satellite imagery. Hyperspectral imagery may provide a more reliable salinity mapping method because of its potential to discriminate halophytic plant cover from non-halophytes.

In this paper we statistically compare the reflectance spectra of sea barley grass to other annual plant species, to determine whether the sea barley grass has the potential to be discriminated and mapped with hyperspectral imagery. Plant spectra were collected during spring senescence in an attempt to capture the spectral differences between the late senescing sea barley grass and other annual grasses. Multiple reflectance spectra of each species were collected with an ASD Fieldspec Pro spectrometer. The plant spectra were collected at plot scale in the field, and at plant and foliage scale in the laboratory under controlled conditions.

Two-group t-tests comparing reflectance of pairs of species at each wavelength showed broad spectral regions where sea barley grass differed significantly from other species for both field and laboratory spectra. The existence of these broad regions of spectral difference suggests that it should be possible to discriminate and map sea barley grass during spring senescence with hyperspectral imagery.

Using Field Spectroscopy and Quickbird Imagery for the Assessment of Peanut Crop Maturity and Aflatoxin Risk

A. J.Robson

G. Wright

Queensland Department of Primary Industries

J. Bjelke Petersen Research Station

PO Box 23, Kingaroy, Qld 4610

Australia

andrew.robson@dpi.qld.gov.au

graeme.wright@dpi.qld.gov.au

Stuart Phinn

University of Queensland

School of Geography, Planning and Architecture

Brisbane, Qld 4072

Australia

S.phinn@uq.edu.au

Abstract

Hyperspectral reflectance (350nm - 2500nm) measurements of growing peanut leaves were used to predict the kernel maturation stage as well as the incidence of aflatoxin within peanut pods. For the prediction of harvest date, explanations of variance of > 95 percent were obtained while explanations of variance of > 81 percent were achieved when differentiating plants with pods contaminated with aflatoxin from those with uncontaminated pods. An explanation of variance of 85 percent was also identified in the prediction of actual aflatoxin concentration within the pod via the spectral properties of a growing leaf. Multispectral satellite imagery also proved accurate in identifying maturity variations across a peanut crop as well as regions of high aflatoxin risk.

Integration of Airborne Casi and Gamma Ray Data for Mine Site Characterisation

K. Pfitzner

Environmental Research Institute of the Supervising Scientist

Supervising Scientist Division

Department of Environment and Heritage

GPO Box 461 DARWIN NT 0812

Australia

Kirrilly.Pfitzner@deh.gov.au

R. Clifton

Northern Territory Geological Survey

GPO Box 3000 DARWIN NT 0801

Australia

Roger.Clifton@nt.gov.au

Abstract

Current airborne remotely sensed data can contribute to the characterisation of mine sites for monitoring and rehabilitation assessment. The spatial and spectral resolution required from airborne data depends on the issues to be addressed. For this paper we combine Compact Airborne Spectrographic Imager data with ground-based reflectance measurements and gamma ray survey data to characterise both minerals indicative of acid mine drainage processes and the radiological nature of a rehabilitated uranium mine site.