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    Quantifying savanna woody cover in the field and on historical imagery: a methodological analysis

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    Date
    2014
    Author
    Sinthumule, Ndidzulafhi Innocent
    Munyati, Christopher
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    Abstract
    The proliferation of woody vegetation on open grass savannas constitutes degradation in rangeland quality. Historical high spatial resolution satellite imagery in archive provides possibilities for assessing increase in woody vegetation cover on the rangelands. This paper examines the quantification of woody vegetation in the field and on historical high spatial resolution imagery, using the southern granites research supersite in the Kruger National Park (KNP) as test case. The recently established research supersites represent the key characteristics of the vegetation zones in the KNP. Field quantification of woody cover was undertaken in June and September 2013 by employing a detailed procedure that quantified the area covered by individual woody (tree, shrub) canopies at twelve one hectare sample plots. The area covered by the woody individuals at the respective plots was then totalled in order to yield the fraction (%) of cover per hectare. The woody cover data were then related to test recent historical imagery in order to assess woody cover estimation procedures on historical imagery. Digital high spatial resolution aerial photographs (dated 2010) and dry period (spring/autumn) SPOT multispectral images (September 2001, April 2012) were used; the dry period dates selected so as to eliminate herbaceous vegetation from the analysis. For the newest (2012) image, sub-pixel classification correctly assigned woody cover at the field sample plots to their 2013 field-derived cover fractions. The results indicate that sub-pixel classification, validated by detailed field quantification of woody cover, can accurately map woody encroachment on savanna rangelands using historical high spatial resolution imagery.
    URI
    http://hdl.handle.net/10394/18763
    http://dx.doi.org/10.4314/sajg.v3i2.1
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    • Faculty of Economic and Management Sciences [1428]

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