Classifying remote sensing imageries to obtain reliable and accurate land use and land cover (LULC) information still remains a challenge that depends on many factors such as complexity of landscape, the remote sensing data selected, image processing and classification methods, etc. The aim of this paper is to extract reliable LULC information from Landsat imageries of the Lower Hunter region of New South Wales, Australia. The classical maximum likelihood classifier (MLC) was first applied to classify Landsat-MSS of 1985 and Landsat-TM of 1995 and 2005. The major LULC identified were Woodland, Pasture/scrubland, Vineyard, Built-up and Water-body. By applying post-classification correction (PCC) using ancillary data and knowledge-based logic rules the overall classification accuracy was improved from about 72% to 91% for 1985 map, 76% to 90% for 1995 map and 79% to 87% for 2005 map. The improved overall Kappa statistics due to PCC were 0.88 for the 1985 map, 0.86 for 1995 and 0.83 for 2005. The PCC maps, assessed by McNemar's test, were found to have much higher accuracy in comparison to their counterpart MLC maps. The overall improvement in classification accuracy of the LULC maps is significant in terms of their potential use for land change modelling of the region.

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Abstract:As soil is the basis of all terrestrial ecosystems, degraded soil means lower fertility, reduced biodiversity and reduced human welfare. Therefore the focus of this paper is on elucidating the influence of land use and land cover (LULC) change on two important soil quality indicators that are fundamental to effective measures for ameliorating soil degradation; namely soil acidity and soil salinity in the Lower Hunter Valley of New South Wales, Australia. First, Analysis of Variance was used to elucidate the effects of LULC categories on soil acidity and salinity. The results indicate that soils under Vineyard have significantly higher pH. In contrast there is no significant effect of LULC or its change on soil salinity. To further elucidate the complex interactions of these soil quality indicators with landscape attributes over 20 years and other terrain attributes, multivariate ordination techniques (correspondence analysis and canonical correspondence analysis) were used. The results show that elevation exerted a more dominant influence on pH than the LULC types and their dynamics. In comparison, salinity of the soil appears to be higher in subsoil layers under woodland than under other LULC categories. The environmental implications of these interactions, as evidenced by this study, provide some insights for future land use planning in the region.

Built-up areas have been expanding throughout the world. Monitoring and prediction of the build-up is not only important for the economic development but also acts as sentinels of environmental decline important for ecologically sustainable development of a region. The aim of this paper is to model the growth of built-up and residential-commercial dwellings over the recent past and thus predict the near future growth for a popular tourist destination of the Lower Hunter of New South Wales, Australia. The land use and land cover change analysis, based on classification of Landsat imageries from 1985 to 2005 at a 5-yearly interval, indicates that built-up areas increased steadily; it was 2.0% of the total landscape in 1985 but increased to 4.2% by the year 2005. If this trend continues, the built-up area will have grown to over 6.5% by 2025-which is equivalent to growth of over 325% from the 1985 base. In order to further evaluate the residential and commercial growth, orthorectified aerial photographs of nearby periods of 1985, 1995 and 2005 were utilized to manually delineate residential/commercial dwellings, and thereby dwelling densities were derived. The results indicate that the mean dwelling