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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Mapping lichen in a caribou habitat of Northern Quebec, Canada, using an enhancement-classification method and spectral mixture analysis
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Mapping lichen in a caribou habitat of Northern Quebec, Canada, using an enhancement-classification method and spectral mixture analysis

机译：使用增强分类方法和光谱混合分析绘制加拿大北魁北克驯鹿栖息地的地衣

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Studies of caribou herds in northern regions are important to better understand population dynamics and define wildlife management strategies. Lichen is a primary food source for caribou and is a good indicator of caribou herd activity because of its sensitivity to overgrazing and overtrampling, its widespread distribution over northern areas, and its influence on herd demography. In this paper, we used Landsat TM imagery for mapping lichen in the summer range of the George River caribou herd in northern Quebec, Canada. Results from the enhancement-classification method (ECM) and from spectral mixture analysis (SMA) were evaluated for their suitability to characterize lichen land cover and for their potential to be applied over large territories,. ECM and SMA are assessed individually and also for potential synergistic use. ECM is based on guided unsupervised classification of enhanced satellite images. Validation based on 3536 pixels from a relatively smaller number of field sites (20) showed an overall accuracy of 74.5% (kappa=0.70) for 10 classes and good discrimination between lichen and nonlichen classes, although we interpret these results with caution due to spatial autocorrelation and nonrandom sampling within field sites. However, discrimination amongst different lichen classes using ECM was more problematic, SMA derives the proportion of individual scene components at subpixel scales. This method provided good results in characterizing variations in lichen abundance validated against field observations and provided additional and new information not provided by ECM which is important since the abundance of lichen as a primary food source is a key indicator of migration and demographic patterns essential for effective wildlife management. We concluded that the ECM and SMA methods are appropriate for different aspects of lichen mapping. ECM provided good discrimination between lichen and nonlichen classes, whereas SMA provided additional lichen information not available by classification yet critical to the environmental application, which is also appropriate for application over much larger areas and in spatiotemporal studies. A synergistic use of SMA and ECM is therefore recommended for future research.
机译：北部地区对北美驯鹿群的研究对于更好地了解种群动态和确定野生动植物管理策略非常重要。地衣是北美驯鹿的主要食物来源，并且是北美驯鹿种群活动的良好指标，因为它对过度放牧和过度踩踏的敏感度，在北部地区的广泛分布以及对种群人口的影响。在本文中，我们使用Landsat TM影像绘制了加拿大魁北克北部乔治河驯鹿群夏季范围内的地衣。评估了增强分类法（ECM）和光谱混合分析（SMA）得出的结果，这些结果可用于表征地衣覆盖度，并具有在大范围内应用的潜力。分别评估ECM和SMA以及潜在的协同作用。 ECM基于增强型卫星图像的引导式无监督分类。基于来自相对较少数量的现场站点（20）的3536个像素进行的验证显示，对于10个类别，整体准确性为74.5％（kappa = 0.70），并且在地衣和非地衣类别之间有很好的区分，尽管由于空间原因我们谨慎解释了这些结果自相关和现场现场的非随机采样。但是，使用ECM在不同的地衣类别之间进行区分的问题更加棘手，SMA可以得出亚像素尺度下单个场景成分的比例。该方法在表征经过实地观察验证的地衣丰度变化方面提供了良好的结果，并提供了ECM未提供的其他新信息，这很重要，因为丰富的地衣作为主要食物来源是迁移和人口分布模式的关键指标，对有效地迁移至关重要野生动物管理。我们得出的结论是，ECM和SMA方法适用于地衣测绘的不同方面。 ECM在地衣和非地衣类别之间提供了很好的区分，而SMA提供了无法通过分类获得但对环境应用至关重要的附加地衣信息，这也适用于更大范围的区域和时空研究。因此，建议在未来的研究中协同使用SMA和ECM。

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