首页> 外文期刊>Global and planetary change >Characterizing land condition variability in Ferlo, Senegal (2001-2009) using multi-temporal 1-km Apparent Green Cover (AGC) SPOT Vegetation data
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Characterizing land condition variability in Ferlo, Senegal (2001-2009) using multi-temporal 1-km Apparent Green Cover (AGC) SPOT Vegetation data

机译:使用多时相1公里表观绿色覆盖(AGC)SPOT植被数据表征塞内加尔费洛(2001-2009)的土地条件变化

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摘要

The ecosystem state or 'land condition' can be characterized by a set of attributes, which show variations at different temporal scales. A multi-resolution analysis (MRA) based on the wavelet transform (WT) has been implemented to examine the land condition of a dryland region in Ferlo (Senegal) over the period 2001-2009. This methodology has proven to be useful for smoothing time series while considering those temporal resolutions that incorporate information about the vegetation dynamics. For this purpose, time series of the 1-km Apparent Green Cover (AGC) from the 10-day composites SPOT Vegetation (VGT) data are analyzed. Two relevant outputs from the MRA, A, (de-noised) and the A6 (inter-annual) components have served us for characterizing the annual vegetation production and assess the long-term variation, respectively. In a first stage, the vegetation seasonality (or intra-annual variation) over the area is described by using several metrics related to vegetation phenology derived from the de-noised time series (At). In a second phase, the temporal variability of the inter-annual component series (As) is accomplished to detect potential vegetation changes over the considered period. A Mann-Kendall test has been applied to confirm the significance of the observed inter-annual changes. A higher number of significant pixels (86%) are obtained when considering the inter-annual component in the trend analysis instead of the original time-series (47%). The results confirm a general greening up over the period 2001-2009, not fully explained by precipitation, as well as rather local negative trends. The Rain-Use Efficiency (RUE) ratio computed using the AGC as a proxy of vegetation production has been considered to further analyze the detected changes. Inter-annual changes in RUE provide a potential method of separating vegetation declines due to lack of rainfall from declines associated with degradation. Some spots of negative values in inter-annual RUE changes are found in certain areas for which several evidence of land degradation have been documented.
机译:生态系统状态或“土地状况”可以通过一组属性来表征,这些属性显示出不同时间尺度的变化。已经实施了基于小波变换(WT)的多分辨率分析(MRA),以检查2001-2009年期间塞罗加(Ferlo)(塞内加尔)干旱地区的土地状况。在考虑那些结合了植被动态信息的时间分辨率时,该方法已证明对于平滑时间序列很有用。为此,分析了来自10天复合SPOT植被(VGT)数据的1公里表观绿色覆盖(AGC)的时间序列。 MRA的两个相关输出A(降噪)和A6(年际)组成部分分别为我们表征了年度植被产量和评估长期变化提供了帮助。在第一阶段,通过使用与从降噪时间序列(At)得出的植被物候相关的若干指标来描述该地区的植被季节性(或年内变化)。在第二阶段,完成年际分量系列(As)的时间变化,以检测所考虑时期内潜在的植被变化。进行了Mann-Kendall检验以确认观察到的年际变化的重要性。当考虑趋势分析中的年际分量而不是原始时间序列时,可获得更高数量的有效像素(86%)。结果证实了2001年至2009年期间的总体绿化,但降雨和局部负面趋势并未完全解释。已考虑使用AGC作为植被产量的代表来计算雨水利用效率(RUE)比率,以进一步分析检测到的变化。 RUE的年际变化提供了一种将因降雨不足而导致的植被减少与退化相关的减少区分开的潜在方法。在某些地区发现了年际RUE变化中的一些负值点,这些地方已经记录了一些土地退化的证据。

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  • 来源
    《Global and planetary change》 |2011年第4期|p.152-165|共14页
  • 作者单位

    Departament de Fisica de la Terra i Termodinamica, Universitat de Valencia., Dr. Moiiner, 50, 46100-Burjassot, Spain;

    Departament de Fisica de la Terra i Termodinamica, Universitat de Valencia., Dr. Moiiner, 50, 46100-Burjassot, Spain;

    Departament de Fisica de la Terra i Termodinamica, Universitat de Valencia., Dr. Moiiner, 50, 46100-Burjassot, Spain;

    Centre de Suivi Ecologique (CSE), Dakar, Senegal;

    Departament de Fisica de la Terra i Termodinamica, Universitat de Valencia., Dr. Moiiner, 50, 46100-Burjassot, Spain;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    land condition; apparent green cover (agc) data; wavelet transform; multi-resolution analysis (mra);

    机译:土地状况;明显的绿色覆盖(agc)数据;小波变换多分辨率分析(MRA);

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