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首页> 外文期刊>Journal of Vegetation Science >Using hyperspectral satellite imagery for regional inventories: a test with tropical emergent trees in the Amazon Basin
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Using hyperspectral satellite imagery for regional inventories: a test with tropical emergent trees in the Amazon Basin

机译：将高光谱卫星图像用于区域清单：对亚马逊盆地热带新兴树木的测试

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QuestionsUnderstanding distributions of tree species at landscape scales in tropical forests is a difficult task that could benefit from the recent development of satellite imaging spectroscopy. We tested an application of the EO-1 Hyperion satellite sensor to spectrally detect the location of five important tree taxa in the lowland humid tropical forests of southeastern Peru.LocationPeru, Departamento de Madre de Dios.MethodsWe used linear discriminant analysis with a stepwise selection procedure to analyze two Hyperion datasets (July and December 2006) to choose the most informative narrow bands for classifying trees.ResultsOptimal channels selected were different between the two seasons. Classification was 100% successful for the five taxa when using 25 narrow bands and pixels that represented > 40% of tree crowns. We applied the discriminant functions developed separately for the two seasons to the entire study area, and found significantly nonrandom overlap in the anticipated distributions of the five taxa between seasons.ConclusionsDespite known issues, such as signal-to-noise ratio and spatial resolution, Hyperion imaging spectroscopy has potential for developing regional mapping of large-crowned tropical trees.
机译：问题了解热带森林在景观尺度上的树种分布是一项艰巨的任务，可以从卫星成像光谱学的最新发展中受益。我们测试了EO-1 Hyperion卫星传感器在光谱上检测秘鲁东南部低地潮湿热带森林中五种重要树类的位置的方法。方法我们使用线性判别分析和逐步选择程序分析两个Hyperion数据集（2006年7月和2006年12月），以选择信息最丰富的窄带来对树木进行分类。结果两个季节之间选择的最佳渠道不同。当使用25个窄带和代表树冠> 40％的像素时，五个分类单元的分类成功100％。我们将两个季节分别开发的判别函数应用于整个研究区域，发现五个季节之间的五个分类单元的预期分布中存在明显的非随机重叠。结论尽管存在已知问题，例如信噪比和空间分辨率，Hyperion成像光谱学具有发展大型加冕热带树木区域分布图的潜力。

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