Landsat remote sensing approaches for monitoring long-term tree cover dynamics in semi-arid woodlands: Comparison of vegetation indices and spectral mixture analysis
Landsat remote sensing approaches for monitoring long-term tree cover dynamics in semi-arid woodlands: Comparison of vegetation indices and spectral mixture analysis
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DOI：
10.1016/j.rse.2011.12.004
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发表时间：
2012-04
影响因子：
13.5
通讯作者：
Jian Yang;P. Weisberg;N. Bristow
中科院分区：
文献类型：
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作者：
Jian Yang;P. Weisberg;N. Bristow
树冠复盖是旱地生态系统的主要生物物理属性。监测其在大空间范围内的长期变化，对于了解木本植物对气候变异性和全球变化的响应至关重要。然而，利用遥感数据量化树冠覆盖率对于旱地生态系统来说仍然是一个挑战，因为那里的植被稀少，树木、灌木和草往往在精细的空间尺度上共存。在这项研究中，我们开发了一个完整的光谱混合分析(SMA)方法，该方法将光合作用植被(PV)、非光合作用植被(NPV)和SMA的遮荫成分与旱地树木覆盖进行回归，以利用Landsat TM数据监测美国内华达州松柏林地的树木覆盖动态。我们评估了1)这种方法在受干扰(链条和焚烧)和未受干扰的林地斑块中估计树木覆盖率的效果如何，以及2)这种方法对气候变化的混杂影响有多敏感。这项评估是在与其他两种更常用的方法进行比较的基础上进行的，这两种方法将NDVI或PV与树木覆盖进行了回归。我们的结果表明，尽管PV方法比NDVI方法表现得更好，但这两种方法都高估了最近干扰林地斑块中的乔木盖度，其中灌木对绿度指数的混杂效应高于未干扰斑块。完整的SMA有效地量化了除未受干扰的斑块外，链接后斑块内的变化，但高估了燃烧斑块内的树木覆盖率。在测试的三种方法中，只有完整的SMA显示出有希望的能力，以减轻年际气候变化对监测林地恢复过程的混淆影响。我们的结果可推广到其他半干旱景观，包括镶嵌在灌丛草原植被中的小树种。
Tree canopy cover is a major biophysical attribute of dryland ecosystems. Monitoring its long-term changes over large spatial extents is critical for understanding woody vegetation response to climate variability and global change. However, quantifying tree canopy cover with remotely sensed data remains a challenge for dryland ecosystems where vegetation is sparse and trees, shrubs, and grasses often co-exist at fine spatial scales. In this study, we developed a full SMA (spectral mixture analysis) method that regressed photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and shade components of the SMA with dryland tree cover to monitor tree cover dynamics on a pinyon–juniper woodland landscape in Nevada, USA using Landsat TM data. We assessed 1) how well this method could estimate tree cover in both disturbed (chained and burned) and non-disturbed woodland patches and 2) how sensitive this method was to the confounding effects of climatic variations. The assessment was conducted in comparison with two other more commonly used methods that regressed NDVI or PV with tree cover. Our results showed that although PV performed better than NDVI, both methods overestimated tree canopy cover within recently disturbed woodland patches where the confounding effects of shrubs on greenness index were higher than in non-disturbed patches. The full SMA efficiently quantified variations within post-chaining patches in addition to non-disturbed patches, but overestimated tree cover within burned patches. Of the three methods tested, only full SMA showed promising capability for mitigating the confounding effects of interannual climatic variations on monitoring the woodland recovery process. Our results are generalizable to other semi-arid landscapes comprising a mosaic of small-statured trees intermixed with shrub steppe vegetation.