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: Brebbia, C.A., and Antunes do Carmo, J.S., (eds.) River Basin Management III. WIT Transactions on Ecology and the Environment, 83 . WIT Press, UK, pp. 535-544.

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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.

Item ID: 3443
Item Type: Book Chapter (Research - B1)
ISBN: 1-84564-023-3
ISSN: 1743-3541
Keywords: image classification, stratification, land use, remote sensing
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Date Deposited: 13 Jul 2009 06:35
Downloads: Total: 3
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