本文为德国德累斯顿应用技术大学（作者：Anne Reichmuth）的硕士论文，共113页。

巴伐利亚州的主要树种是云杉，由于其在非典型地理范围内的人为影响分布，受到气候变化的强烈影响。由于气候变化、生物和非生物因素如树皮甲虫、真菌、风暴、雪和水分缺乏更频繁地发生，对这些不适宜地点的云杉造成压力。在这些变化的条件下，越来越重要的是检测森林类型作为其自身的特征，特别是包括其他树种和云杉。

本文提出了一种光谱分析法，以落叶和针叶林为森林类型，以欧洲山毛榉、欧洲冷杉和挪威云杉为树种。这项分析是使用高光谱HySpex-VNIR和多光谱Worldwiew-2图像进行的，每幅图像的地面分辨率为2m，来自德国南部的一片异质和分层温带森林。这种类型的森林具有可持续发展的温带森林的特点。从HySpex-VNIR和Worldwiew-2提取了2008年和2009年的参考光谱，并用主成分分析法进行了研究。利用遗传算法从HySpex-VNIR图像中提取了8个不相关的波段，这些波段被优化用于森林类型识别，另外8个波段也被优化用于树种识别。从HySpex-VNIR和Worldwiew-2中提取的8个波段作为线性判别分析输入。HySpex-VNIR对森林类型和树种识别的总准确率分别为94.4%和88.3%。Worldwiew-2对森林类型和树种识别的准确率分别为87.8%和86.7%。成功的基于光谱的森林类型和树种分类方法被转移到相应的图像上，用于其发生的空间描述。本文的研究结果证实了航空高光谱图像在森林类型和物种检测方面的优势。这种方法对于具有光谱信息的星载多光谱图像（与植被相关）的可转移性似乎是可行的。

The main tree species in Bavaria is spruce, which is being strongly affected by the climate change, because of its anthropogenic influenced distribution in non-typical site ranges. Through climate change, biotic and abiotic factors, such as bark beetles, fungi, storm, snow and water stress are occurring more often and are stressing spruce in these unsuitable sites. Due to these changing conditions it is getting more important to detect forest types as a feature of its own, but also other tree species and spruce in particular. This thesis presents a spectral analysis of detecting deciduous and coniferous forest as forest type and independently European beech, European fir and Norway spruce as tree species. The analysis was carried out using hyperspectral HySpex VNIR and multispectral Worldview-2 images, each with 2 m ground resolution from a heterogeneous and stratified temperate forest in southern Germany. This type of forest exhibits characteristics of sustainable prospective temperate forests. A total of 2008 and 2009 reference spectra from HySpex VNIR and Worldview-2 were extracted and analysed with Principal Component Analysis for possible discrimination. A combination of eight uncorrelated bands, that were optimised for forest type discrimination and another eight bands, also optimised for tree species discrimination were extracted from HySpex VNIR imagery, using a Genetic Algorithm. The extracted eight bands from HySpex VNIR and the eight bands from Worldview-2 served as input for Linear Discriminant Analysis. The overall accuracies achieved from HySpex VNIR are 94.4 % for forest type and 88.3 % for tree species discrimination. Worldview-2 achieved an overall accuracy of 87.8 % for forest type and 86.7 % for tree species discrimination. The successful spectral based classification for forest type and tree species were transferred onto the corresponding images for spatial description of their occurrence. The promising results of this thesis confirms the advantage of airborne hyperspectral images for forest type and species detection. The transferability of this approach to spaceborne multispectral images with spectral information, relevant for vegetation purposes seems feasible.

1.       引言与研究目标

2. 研究的地理区域

3. 遥感的基本原理

4. 文献回顾

5. 数据集与预处理

6. 研究方法

7. 研究结果

8. 讨论与展望

9. 结论

10. 总结

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