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

机译:通过南非东开普省农村土地覆盖变化分析表征退化梯度

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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.
机译:对南非东开普省农村的三个集水区进行了土地覆盖变化分析,分两个时间步长(2000年和2014年),以表征景观转化轨迹,以维持景观健康。土地覆盖图是根据以下数据得出的:(1)来自现有数据(2000); (2)通过Landsat 8影像的基于对象的影像分析(2014年)。土地覆盖变化分析通过开发用来识别景观变化轨迹的土地覆盖标签而得到促进。在两个时间步骤分配给土地覆盖图每个交叉点的土地覆盖标签提供了变化的空间分布的主题表示。虽然土地利用方式的特点是持久性高(77%),但城市地区和农业的扩张主要是以草地为代价的。自然或入侵林区的持续性和集约化被确定为景观中的退化梯度,占研究面积的近10%。确定景观中的重要信号仍然是难题,这些信号不是底层输入数据或分析规模中的误差。系统的变更分析和准确的不确定性报告可以潜在地解决这些问题,以产生可靠的输出以进行进一步的建模。

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