云影区机载高光谱图像树种分类

Tree species classification is crucial for forest management.Airborne hyperspectral data provide the image with high spatial and spectral resolution, which has a possibility for forest species classification. The radiance of airborne hyperspectral image was decreased when the cloud exists. The radiance of object in the cloud shadow area is much lower than the non-shaded. And the spectral variance of different objects in the shadow is also lower than that of the non-shaded region. Although the radiance of the image in the cloud shadow is decreased, there is still a certain difference among different objects, which provides the possibility for forest species classification. We used vegetation indices and texture features to recombine a new image.

树种分类对于森林经营管理至关重要。机载高光谱数据（Airborne Hyperspectral Data）可生成兼具高空间分辨率与高光谱分辨率的影像，为森林树种分类提供了可行基础。当存在云层时，机载高光谱影像的辐射亮度会出现衰减：云阴影区域内地物的辐射亮度远低于非阴影区域，且阴影区域内不同地物的光谱变异度也低于非阴影区域。尽管云阴影区域内的影像辐射亮度有所衰减，但不同地物间仍存在一定差异，这依然为森林树种分类提供了可能性。本研究采用植被指数与纹理特征重构得到新影像。

搜集汇总

背景与挑战

背景概述

该数据集聚焦于云影区机载高光谱图像的树种分类研究，利用高分辨率图像在云阴影区域进行森林物种识别，通过结合植被指数和纹理特征来增强分类能力。数据集隶属于'落叶松高效培育技术研究'项目，以文档格式提供，数据量较小（205.19 KB），适用于植物学领域的相关分析。