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Tree Crown Detection on Multispectral VHR Satellite Imagery

机译:多光谱VHR卫星影像的树冠检测

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摘要

A new method called Arbor Crown Enumerator (ACE) was developed for tree crown detection from multispectral Very High-resolution (VHR) satellite imagery. ACE uses a combination of the Red band and Normalized Difference Vegetation Index (NDVl) thresholding, and the Laplacian of the Gaussian (LOG) blob detection method. This method minimizes the detection shortcomings of its individual components and provides a more accurate estimation of the number of tree crowns captured in an image sample. The ACE was applied successfully to sample images taken from a four-band QuickBird (0.7m X 0.7m) scene of Keritis watershed, in the Island of Crete. The method performs very well for different tree types, sizes and densities that may include non vegetation features such as roads and houses. Statistical analysis on the tree crown detection results from the sample images supports the agreement between the measurements and the simulations. The new method reduces considerably the effort of manual tree counting and can be used for environmental applications of fruit orchard, plantation and open forest population monitoring.
机译:开发了一种称为Arbor Crown Enumerator(ACE)的新方法,用于从多光谱超高分辨率(VHR)卫星图像中检测树冠。 ACE使用红色带和归一化差异植被指数(NDV1)阈值化以及高斯(LOG)斑点的拉普拉斯算子的组合。该方法最大程度地减少了其各个组件的检测缺点,并提供了对图像样本中捕获的树冠数量的更准确估计。 ACE已成功应用于从克里特岛Keritis分水岭的四波段QuickBird(0.7m X 0.7m)场景中拍摄的图像样本。该方法对于可能包括非植被特征(例如道路和房屋)的不同树类型,大小和密度的性能非常好。对样本图像中树冠检测结果的统计分析支持了测量与模拟之间的一致性。这种新方法大大减少了手工计算树木的工作量,可用于果园,人工林和开阔森林人口监测的环境应用。

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