Paper
23 January 2001 Mapping and monitoring land use and condition change in the southwest of Western Australia using remote sensing and other data
Peter A. Caccetta, Norm A. Campbell, F. Evans, S. L. Furby, H. T. Kiiveri, Jeremy F. Wallace
Author Affiliations +
Abstract
In the south-west of Western Australia, the clearing of land for agricultural production has lead to rising saline ground water, resulting in the loss of previously productive land to salinity; damage to buildings, roads and other infrastructure; the decline in pockets of remnant vegetation and biodiversity; and the reduction in water quality. The region in question comprises some 24 million hectares of land. This has resulted in a wide variety of stakeholders requesting quantitative information regarding historical, present and future trends in land condition and use. Historically, two methods have been widely used to obtain information: (1) surveys requesting land managers to provide estimates of land use and condition; and (2) human interpretation of aerial photography. Data obtained from the first approach has in the past been incomplete, inaccurate and non-spatial. The second approach is relatively expensive and as a result is incomplete and is not regularly updated.In this paper, we describe an approach to land use/condition monitoring using remotely sensed and other data such as digital elevation models (DEMs). We outline our methodology and give examples of mapping and monitoring change in woody vegetation and salinity.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peter A. Caccetta, Norm A. Campbell, F. Evans, S. L. Furby, H. T. Kiiveri, and Jeremy F. Wallace "Mapping and monitoring land use and condition change in the southwest of Western Australia using remote sensing and other data", Proc. SPIE 4171, Remote Sensing for Agriculture, Ecosystems, and Hydrology II, (23 January 2001); https://doi.org/10.1117/12.413948
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Cited by 8 scholarly publications.
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KEYWORDS
Vegetation

Earth observing sensors

Landsat

Agriculture

Calibration

Associative arrays

Data modeling

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