利用超光谱WorldView-3与高光谱影像进行土地利用和土地覆盖分类的比较

2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) Pub Date : 2016-08-01 DOI:10.1109/WHISPERS.2016.8071721

Jan Koenig, L. Gueguen

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引用次数: 3

摘要

在发布具有近红外和SWIR波段的WorldView-3 (WV-3)数据集之前，本研究对基于高光谱和WV-3影像的16波段、8波段和4波段的土地利用/土地覆盖(LULC)分类进行了基线比较。我们在意大利帕维亚的市中心选择了一个经过充分研究的地区。结果表明，从WV-3的SWIR波段中添加的光谱信息有助于弥合多光谱VNIR与高光谱VNIR图像获得的精度/召回分数之间的差距。

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A comparison of land use land cover classification using superspectral WorldView-3 vs hyperspectral imagery

In advance of releasing a WorldView-3 (WV-3) dataset with both VNIR and SWIR bands for research purposes, this study was conducted to provide a baseline comparison of land use/land cover (LULC) classification based on hyperspectral and 16-, 8-, and 4-bands of WV-3 imagery. We chose a well-researched area over the city center of Pavia, Italy. Results suggest that the addition of spectral information from WV-3's SWIR bands helps bridge the gap between precision/recall scores obtained with multispectral VNIR vs. hyperspectral VNIR imagery.

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2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)

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