Erratum: A Machine Learning Method for Co-Registration and Individual Tree Matching of Forest Inventory and Airborne Laser Scanning Data. Remote Sens. 2017, 9, 505
References
- Lamprecht, S.; Hill, A.; Stoffels, J.; Udelhoven, H. A Machine Learning Method for Co-Registration and Individual Tree Matching of Forest Inventory and Airborne Laser Scanning Data. Remote Sens. 2017, 9, 505. [Google Scholar] [CrossRef]
- Hansen, J.; Nagel, J. Waldwachstumskundliche Softwaresysteme auf Basis von TreeGrOSS-Anwendung und Theoretische Grundlagen; Niedersächsische Staats-und Universitätsbibliothek: Göttingen, Germany, 2014. [Google Scholar]
- Pretzsch, H. Modellierung des Waldwachstums; Parey: Berlin, Germany, 2001. [Google Scholar]
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Lamprecht, S.; Hill, A.; Stoffels, J.; Udelhoven, T. Erratum: A Machine Learning Method for Co-Registration and Individual Tree Matching of Forest Inventory and Airborne Laser Scanning Data. Remote Sens. 2017, 9, 505. Remote Sens. 2017, 9, 692. https://doi.org/10.3390/rs9070692
Lamprecht S, Hill A, Stoffels J, Udelhoven T. Erratum: A Machine Learning Method for Co-Registration and Individual Tree Matching of Forest Inventory and Airborne Laser Scanning Data. Remote Sens. 2017, 9, 505. Remote Sensing. 2017; 9(7):692. https://doi.org/10.3390/rs9070692
Chicago/Turabian StyleLamprecht, Sebastian, Andreas Hill, Johannes Stoffels, and Thomas Udelhoven. 2017. "Erratum: A Machine Learning Method for Co-Registration and Individual Tree Matching of Forest Inventory and Airborne Laser Scanning Data. Remote Sens. 2017, 9, 505" Remote Sensing 9, no. 7: 692. https://doi.org/10.3390/rs9070692
APA StyleLamprecht, S., Hill, A., Stoffels, J., & Udelhoven, T. (2017). Erratum: A Machine Learning Method for Co-Registration and Individual Tree Matching of Forest Inventory and Airborne Laser Scanning Data. Remote Sens. 2017, 9, 505. Remote Sensing, 9(7), 692. https://doi.org/10.3390/rs9070692