Mapping land use in a large agricultural basin : a comparison between classification techniques

Ierodiaconou, D, Leblanc, M, Laurenson, L, Stagnitti, F and Versace, V 2005, Mapping land use in a large agricultural basin : a comparison between classification techniques. In Cheng, A.H-D (ed), River basin management III, WIT Press, Southampton, Eng., pp.535-544.

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Title Mapping land use in a large agricultural basin : a comparison between classification techniques
Author(s) Ierodiaconou, DORCID iD for Ierodiaconou, D
Leblanc, M
Laurenson, LORCID iD for Laurenson, L
Stagnitti, F
Versace, VORCID iD for Versace, V
Title of book River basin management III
Editor(s) Cheng, A.H-D
Publication date 2005
Series WIT transactions on ecology and the environment
Chapter number 51
Total chapters 62
Start page 535
End page 544
Total pages 10
Publisher WIT Press
Place of Publication Southampton, Eng.
Keyword(s) image classification
land use
remote sensing
Summary In order to facilitate the better management of river basin resources, the Glenelg-Hopkins region in south-east Australia required an accurate and up to date land use map. Land use has a major impact on Australia's natural resources including its soil, water, flora and fauna and plays a major role in determining basin health. Inappropriate land use and practices have contributed to extensive dryland salinity and water quality problems. Land use data is often required for environmental models and in most cases the reliability of model outputs is dependent on the spatial detail and accuracy of the land use mapping. This paper examines methods to obtain an up to date land use map and a detailed accuracy assessment using Landsat ETM+ data for a regional basin. A multi-source based approach allowed the collection of 4817 ground truth data points from the field investigation. This enabled researchers to (i) incorporate a full range of information into digital image analysis with significant improvements in accuracy and (ii) hold sufficient independent references for an accurate error assessment. Classification accuracy was significantly improved using a stratification design, in which the region is sub-divided into smaller homogenous areas as opposed to a full scene classification technique. The overall classification accuracy was 84% (KHAT= 0.833) for the stratified approach compared to 76% (KHAT= 0.743) for the full scene classification. Effective assessment, planning and management of basins are dependent on a sound knowledge of the distribution and variability of land use.
ISBN 1845640233
ISSN 1743-3541
Language eng
Field of Research 050205 Environmental Management
Socio Economic Objective 0 Not Applicable
HERDC Research category B1.1 Book chapter
Copyright notice ©2005, WIT Press
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