Predicting areas at risk from salinity
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Satellite images
combined with
terrain maps can
be used to predict
areas that are at
risk from salinity |
Farm and catchment planning can be performed more efficiently if
accurate information about which areas are salt-affected, where salinity is spreading or
emerging, and which areas are at risk from salinity in the future is available. Maps which
show changes in salinity through time, and areas which may be at risk from salinity in the
future, can be produced through the use of satellite images and digital elevation models
(DEMs).
Satellite images provide information about past and present vegetation cover and land
condition. When this is combined with other spatial data sets which describe the terrain
and the movement of water through the landscape, it is possible to predict which areas are
at risk from salinity.
At any position in the landscape, salinity risk is related to the amount of water
flowing into that position, and the slope at which the water drains away. Digital
elevation models show a three- dimensional view of an area and can illustrate regional
drainage patterns.
The clearing of land for agriculture affects the amount of water flowing through the
landscape. Information from satellite data and elevation data can be combined to show
which areas have been cleared and the proportion of clearing in upslope areas.
These techniques have been used to map salinity and salinity risk in the Upper Kent
River catchment, located approximately 350km south east of Perth in Western Australia.
Satellite images and other spatial data, such as downhill slope and upslope cleared
area, were used to predict areas affected by salinity in the Upper Kent River catchment in
Western Australia. Landsat MSS and TM images for the years 1977, 1988 and 1994 were used
to produce maps which show different types of land cover.
| The classification map (right) shows ground cover classes in August 1988. Water is
shown in dark blue, remnant vegetation is shown in green and light blue, bare saline areas
are shown in red, bare non-saline areas are shown in yellow and agricultural land in good
condition is shown in grey. A digital elevation model (DEM) was produced from contour
data provided by the Department of Land Administration.
The DEM was produced using spline interpolation, and cross-validation procedures were
employed to determine the optimal parameter settings. |
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The upslope area map (left) shows the degree of water accumulation at any position.
Areas with low water accumulation (eg. hills) are shown in yellow, ranging through green
and blue, with high water accumulation (eg. streams) shown in pink and red. Methods
based on decision trees and expert systems were used to determine areas at risk from
salinity. The salinity and prediction maps were combined to form a salinity change map for
the catchment. The change map (below) shows changes in salinity from 1977 to 1994 and
beyond. |
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Salinity change map: green - saline in 1977; light blue - saline in 1988; blue -
saline in 1994; and pink - predicted to become saline during the next decade |
For more information, see Predicting Salinity in the Upper Kent River Catchment,
A report from the LWRRDC project "Integrating Remotely Sensed Data With Other Spatial
Data Sets to Predict Areas at Risk from Salinity"
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