利用高光谱图像识别植被土地覆盖

J. Cipar, T. Cooley, R. Lockwood
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引用次数: 6

摘要

我们使用在弗吉尼亚州A. P. Hill堡收集的AVIRIS数据来评估航空高光谱图像用于区分植被土地覆盖的效果。a . P. Hill堡位于弗吉尼亚州中东部,森林茂密,既有大西洋中部地区的落叶物种,也有针叶物种。森林物种的位置和范围记录在由堡垒为规划和资源保护目的编制的土地覆盖数据库中。AVIRIS数据集包括1999年11月和2001年9月两个日期的几条低空(3.7米GSD)航线。我们的目标是利用数学和生物物理指标来描述植被土地覆盖的自然变异性,并评估土地覆盖之间的差异以进行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distinguishing vegetation land covers using hyperspectral imagery
We use AVIRIS data collected at Fort A. P. Hill, Virginia, to evaluate how well airborne hyperspectral imagery can be used to distinguish vegetation land covers. Fort A. P. Hill is located in east-central Virginia and is heavily forested with a mix of deciduous and coniferous species native to the mid-Atlantic region. The location and extent of the forest species is documented in a land cover database compiled by the Fort for planning and resource protection purposes. The AVIRIS data set consists of several low-altitude (3.7-m GSD) flight lines on two dates: November 1999 and September 2001. Our goal is to characterize the both the natural variability of vegetation land covers using mathematical and biophysical metrics and to assess differences between land covers for classification purposes.
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