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Geosciences 2017, 7(1), 7; doi:10.3390/geosciences7010007

Characterizing Degradation Gradients through Land Cover Change Analysis in Rural Eastern Cape, South Africa

1
Department Geography and Environmental Studies, Stellenbosch University, Stellenbosch 7602, South Africa
2
Department of Construction and Surveying, School of Engineering and the Built Environment, Glasgow Caledonian University, Glasgow G4 0BA, UK
3
Institute for Water Research, Rhodes University, Grahamstown 6140, South Africa
4
Agricultural Research Council-Animal Production Institute, Grahamstown 6140, South Africa
*
Author to whom correspondence should be addressed.
Received: 16 November 2016 / Accepted: 3 February 2017 / Published: 10 February 2017
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Abstract

Land cover change analysis was performed for three catchments in the rural Eastern Cape, South Africa, for two time steps (2000 and 2014), to characterize landscape conversion trajectories for sustained landscape health. Land cover maps were derived: (1) from existing data (2000); and (2) through object-based image analysis (2014) of Landsat 8 imagery. Land cover change analysis was facilitated using land cover labels developed to identify landscape change trajectories. Land cover labels assigned to each intersection of the land cover maps at the two time steps provide a thematic representation of the spatial distribution of change. While land use patterns are characterized by high persistence (77%), the expansion of urban areas and agriculture has occurred predominantly at the expense of grassland. The persistence and intensification of natural or invaded wooded areas were identified as a degradation gradient within the landscape, which amounted to almost 10% of the study area. The challenge remains to determine significant signals in the landscape that are not artefacts of error in the underlying input data or scale of analysis. Systematic change analysis and accurate uncertainty reporting can potentially address these issues to produce authentic output for further modelling. View Full-Text
Keywords: land cover change; remote sensing; object-based image analysis; OBIA; Landsat land cover change; remote sensing; object-based image analysis; OBIA; Landsat
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Münch, Z.; Okoye, P.I.; Gibson, L.; Mantel, S.; Palmer, A. Characterizing Degradation Gradients through Land Cover Change Analysis in Rural Eastern Cape, South Africa. Geosciences 2017, 7, 7.

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