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Tracking Desertification in California Using Remote Sensing: A Sand Dune Encroachment Approach
AbstractMost remote sensing studies in deserts focus solely on vegetation monitoring to assess the extent of desertification. However, the application of sand dune encroachment into such studies would greatly improve the accuracy in the prediction criteria of risk-prone areas. This study applies the latter methodology for tracking desertification using sand dunes in the Kelso Dunes (in Newberry-Baker, CA, USA). The approach involves the comparison of spectral characteristics of the dunes in Landsat Thematic Mapper (TM) images over a 24-year period (1982, 1988, 1994, 2000, and 2006). During this 24-year period, two El Niño events occurred (1983 and 1993); it was concluded that despite the shift in predominant winds, the short-term variation in wind direction did not make a noticeable change in dune formation, but greatly influences vegetation cover. Therefore, relying solely on vegetation monitoring to assess desertification can lead to overestimations in prediction analysis. Results from this study indicate that the Kelso Dunes are experiencing an encroachment rate of approximately 5.9 m3/m/yr over the 24-year period. While quantifying the Kelso Dunes or any natural dynamic system is subject to uncertainties, the encroachment rate approach reflects the highly heterogeneous nature of the sand dunes (in regards to spectral variability in brightness) at Kelso Dunes and serves as an exemplar for future research.
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Lam, D.K.; Remmel, T.K.; Drezner, T.D. Tracking Desertification in California Using Remote Sensing: A Sand Dune Encroachment Approach. Remote Sens. 2011, 3, 1-13.View more citation formats
Lam DK, Remmel TK, Drezner TD. Tracking Desertification in California Using Remote Sensing: A Sand Dune Encroachment Approach. Remote Sensing. 2011; 3(1):1-13.Chicago/Turabian Style
Lam, Doris K.; Remmel, Tarmo K.; Drezner, Taly D. 2011. "Tracking Desertification in California Using Remote Sensing: A Sand Dune Encroachment Approach." Remote Sens. 3, no. 1: 1-13.