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The impact of dryland salinity on Ross River virus in south-western Australia : an ecosystem health perspectiveJardine, Andrew January 2007 (has links)
[Truncated abstract] A functional ecosystem is increasingly being recognised as a requirement for health and well being of resident human populations. Clearing of native vegetation for agriculture has left 1.047 million hectares of south-west Western Australia affected by a severe form of environmental degradation, dryland salinity, characterised by secondary soil salinisation and waterlogging. This area may expand by a further 1.7-3.4 million hectares if current trends continue. Ecosystems in saline affected regions display many of the classic characteristics of Ecosystem Distress Syndrome (EDS). One outcome of EDS that has not yet been investigated in relation to dryland salinity is adverse human health implications. This thesis focuses on one such potential adverse health outcome: increased incidence of Ross River virus (RRV), the most common mosquito-borne disease in Australia. Spatial analysis of RRV notifications did not reveal a significant association with dryland salinity. To overcome inherent limitations with notification data, serological RRV antibody prevalence was also investigated, and again no significant association with dryland salinity was detected. However, the spatial scale imposed limited the sensitivity of both studies. ... This thesis represents the first attempt to prospectively investigate the influence of secondary soil salinity on mosquito-borne disease by combining entomological, environmental and epidemiological data. The evidence collected indicates that RRV disease incidence is not currently a significant population health priority in areas affected by dryland salinity despite the dominant presence of Ae. camptorhynchus. Potential limiting factors include; local climatic impact on the seasonal mosquito population dynamics; vertebrate host distribution and feeding behaviour of Ae. camptorhynchus; and the scarce and uneven human population distribution across the region. However, the potential for increased disease risk in dryland salinity affected areas to become apparent in the future cannot be discounted, particularly in light of the increasing extent predicted to develop over coming decades before any benefits of amelioration strategies are observed. Finally, it is important to note that both dryland salinity and salinity induced by irrigation are important forms of environmental degradation in arid and semi-arid worldwide, with a total population of over 400 million people. Potential health risks will of course vary widely across different regions depending on a range of factors specific to the local region and the complex interactions between them. It is therefore not possible to make broad generalisations. The need is highlighted for similar research in other regions and it is contended that an ecosystem health framework provides the necessary basis for such investigations.
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Mapping potential soil salinization using rule based object-oriented image analysisStals, Jacobus Petrus 12 1900 (has links)
Thesis (MSc (Geography and Environmental Studies))--University of Stellenbosch, 2007. / Soil salinization is a world wide environmental problem affecting plant growth and
agricultural yields. Remote sensing has been used as a tool to detect and/or manage soil
salinity. Object-oriented image analysis is a relatively new image analysis technique
which allows analysis at different hierarchical scales, the use of relationships between
objects and contextual information in the classification process, and the ability to create a
rule based classification procedure. The Lower Orange River in South Africa is a region
of successful irrigation farming along the river floodplain but also with the potential risk
of soil salinization. This research attempted to detect and map areas of potential high soil
salinity using digital aerial photography and digital elevation models.
Image orthorectification was conducted on the digital aerial photographs. The radiometric
variances between photographs made radiometric calibration of the photographs
necessary. Radiometric calibration on the photographs was conducted using Landsat 7
satellite images as radiometric correction values, and image segmentation as the
correction units for the photographs.
After radiometric calibration, object-oriented analysis could be conducted on one analysis
region and the developed rule bases applied to the other regions without the need for
adjusting parameters. A rule based hierarchical classification was developed to detect
vegetation stress from the photographs as well as salinity potential terrain features from
the digital elevation models. These rule bases were applied to all analysis blocks.
The detected potential high salinity indicators were analyzed spatially with field collected
soil data in order to assess the capability of the classifications to detect actual salinization,
as well as to assess which indicators were the best indicators of salinity potential.
Vegetation stress was not a good indicator of salinity as many other indicators could also
cause vegetation stress. Terrain indicators such as depressions in the landscape at a micro
scale were the best indicators of potential soil salinization.
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