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Can linear trend analyses of NDVI time series data truly detect land degradation? Simulations may provide the answer.

机译:NDVI时间序列数据的线性趋势分析可以真正检测出土地退化吗?模拟可以提供答案。

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There has been a recent proliferation of remote sensing-based trend analysis for monitoring regional desertification. These show contradictory results. All of them claim to have been "validated" through expert interpretation, in the absence of sufficient field data. We suggest that such an approach is not sufficiently rigorous. Therefore, we demonstrate an approach which simulates land degradation so that the intensity, rate and timing of the reduction in NDVI can be controlled, in order to quantitatively evaluate the ability of methods to detect these known changes. The results show that linear trend analysis is rather insensitive to previously observed levels of NDVI reduction due to degradation in the well-studied communal lands in the Lowveld of South Africa. The period of investigation, has a large but rather unpredictable influence on the linear trends. This casts doubts over the ability of linear trend analysis, to detect relatively subtle, slowly-developing degradation in semi-arid rangelands.
机译:近来,用于监测区域荒漠化的基于遥感的趋势分析激增。这些结果矛盾。在缺乏足够的现场数据的情况下,所有这些人都声称已通过专家解释得到“确认”。我们建议这种方法不够严格。因此,我们演示了一种模拟土地退化的方法,以便可以控制NDVI降低的强度,速度和时间,以便定量评估检测这些已知变化的方法的能力。结果表明,线性趋势分析对先前观察到的NDVI降低水平不敏感,这是由于在南非Lowveld进行了深入研究的公共土地退化所致。调查期对线性趋势具有很大但不可预测的影响。这使人们对线性趋势分析的能力产生怀疑,该能力可以检测半干旱牧场中相对细微,发展缓慢的退化。

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