期刊
FORESTS
卷 10, 期 3, 页码 -出版社
MDPI
DOI: 10.3390/f10030235
关键词
Robinia pseudoacacia L; reproduction; spreading; short rotation coppice; unmanned aerial system (UAS); object-based image analysis (OBIA); convolutional neural network (CNN)
类别
资金
- University of Applied Science Erfurt (FHE)
- Technical University of Munich (TUM)
- Westfalische Wilhelms University of Munster
- German Research Foundation (DFG)
Varying reproduction strategies are an important trait that tree species need in order both to survive and to spread. Black locust is able to reproduce via seeds, stump shoots, and root suckers. However, little research has been conducted on the reproduction and spreading of black locust in short rotation coppices. This research study focused on seed germination, stump shoot resprout, and spreading by root suckering of black locust in ten short rotation coppices in Germany. Seed experiments and sample plots were analyzed for the study. Spreading was detected and measured with unmanned aerial system (UAS)-based images and classification technology-object-based image analysis (OBIA). Additionally, the classification of single UAS images was tested by applying a convolutional neural network (CNN), a deep learning model. The analyses showed that seed germination increases with increasing warm-cold variety and scarification. Moreover, it was found that the number of shoots per stump decreases as shoot age increases. Furthermore, spreading increases with greater light availability and decreasing tillage. The OBIA and CNN image analysis technologies achieved 97% and 99.5% accuracy for black locust classification in UAS images. All in all, the three reproduction strategies of black locust in short rotation coppices differ with regards to initialization, intensity, and growth performance, but all play a role in the survival and spreading of black locust.
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