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Support of multispectral very high solution remotely sensed imagery for old-growth beech forest detection.

机译:支持多光谱非常高分辨率的遥感影像,用于老山毛榉森林检测。

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摘要

In the Mediterranean basin human activity has modified landscapes for millennia,nevertheless there are few remote forest areas relatively untouched long enough from direct anthropogenic disturbance to develop old-growth attributes. The aim of this note is to assess the potential of QuickBird (QB) satellite multispectral imagery for detecting old-growth forest stands, considering as case study a Mediterranean beech forest in central Italy. The segmentation-based analysis of QB image proved to be a promising tool to detect scaledependent pattern of forest structural heterogeneity. Values of remotely sensed attributes are compared in old-growth and not-old-growth stands: the statistical analysis showed that oldgrowthness is associated to the variability of multispectral reflectance from the image objects (polygons). Green band variability, notably, expressed by Ratio_band_2 has proven to be helpful for predicting old-growthness.
机译:在地中海盆地,人类活动已经改变了几千年的景观,尽管如此,很少有偏远的森林地区由于直接的人为干扰而没有被开发到相对较长的时间,从而形成了老龄化的属性。本文的目的是评估QuickBird(QB)卫星多光谱图像在检测老龄森林林分中的潜力,并作为案例研究在意大利中部的地中海山毛榉林中进行研究。基于分割的QB图像分析被证明是检测森林结构异质性的尺度依赖性模式的有前途的工具。在旧的和未旧的林分中比较了遥感属性的值:统计分析表明,旧度与图像对象(多边形)的多光谱反射率的可变性相关。事实证明,由Ratio_band_2表示的绿带变异性有助于预测陈旧性。

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