Assessing the accuracy of remote sensing techniques in vegetation fractions estimation
This study aimed at exploring different remote sensing (RS) techniques for quantitatively measuring vegetation and bare soil fractions in dune ecosystems along the Kenyan coast. The accurate measurements of field samples are required by Kenya Wildlife for environmental monitoring. The current methodology for measuring fractions (ecological surveys) is biased, expert dependent and subjective, and for this reason, remote sensing techniques have been explored to find a better cost- effective alternative.
Three methods were carried out to estimate different vegetation coverages in field samples and to analyze their performance: classification of photography’s taken by hand-held camera, unmixing of aerial photographs, unmixing of Crop scan and Field spec spectral measurements. For these purposes 32 plots of 1x1square meters distributed in 4 transects were selected and measured in the dune ecosystem.
According to the field spectral measurements, different targets (lichens, vascular plants, mosses, and bare soil) showed a large spectral variation and overlapping between their spectral signatures. Therefore, classification methods and unmixing techniques led to poor results since they are based upon the spectral signature of the targets.
The hand held camera method proved more accurate than Field Spec, Aerial photograph and Crop Scan. Therefore, from the remote sensing methods, this is the best method when considering accuracy. The performance of this method could be improved by adding an extra band (Infrared for instance). This extra band would allow operators to identify and classify better different kind of vegetation in the image.
Keywords: Unmixing, Remote sensing techniques, spectral measurements
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