Automated tree crown detection and delineation in high-resolution digital camera imagery of coniferous forest regeneration

By D. Pouliot, D. King, F. W. Bell, Doug Pitt. 2002

429 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/7ffd68162021e8288a0983e692780e6cb0dd46b4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Lianjun Zhang
2. Zhen Zhen
3. Haohuan Fu
4. Weijia Li
5. Le Yu
6. Arthur Philip Cracknell
7. Lindi J. Quackenbush
8. J. V. van Aardt

In Environmental Engineering

1. Lianjun Zhang
2. Zhen Zhen
3. Haohuan Fu
4. Weijia Li
5. Le Yu
6. Arthur Philip Cracknell
7. Lindi J. Quackenbush
8. J. V. van Aardt

In Nature and Landscape Conservation

1. Zhen Zhen
2. Lianjun Zhang
3. Haohuan Fu
4. Weijia Li
5. Arthur Philip Cracknell
6. Le Yu
7. Lindi J. Quackenbush
8. Fethi B. Ahmed

Citations in the corpus

• Remote sensing and machine learning for tree detection and classification in forestry applications (2019, methodology): “Moreover, it was shown that detection accuracy using imagery is more or less comparable with detection accuracy using LiDAR data only if imagery resolution is high (around 5-15 cm) and for lower resolution imagery (less than 30 cm) detection accuracy is significantly lower.(20) There is another appr”
• Trends in Automatic Individual Tree Crown Detection and Delineation - Evolution of LiDAR Data (2016, methodology): “Individual tree level Treetop detection (point accuracy) Precision recall curve that includes precision and recall [64]; Accuracy index, commission/omission error [105]; RMSE for a positioning error vector, N-accuracy base on commission point, unique hit or multiple hit [106]; Site specific measurem”
• Deep Learning Based Oil Palm Tree Detection and Counting for High-Resolution Remote Sensing Images (2016, methodology): “on the local maximum filter and the analysis of local transects extending outward from a potential tree apex [9].”
• A review of methods for automatic individual tree-crown detection and delineation from passive remote sensing (2011, methodology): “Application examples for tree detection and crown delineation are summarized in tables 1 and 2, respectively.”
• Individual tree detection based on variable and fixed window size local maxima filtering applied to IKONOS imagery for even-aged Eucalyptus plantation forests (2011, methodology): “Finally, local maxima filtering (Wulder et al. 2000, Pouliot et al. 2002, Wang et al. 2004, Wulder and White 2004, Korpela 75 et al. 2006), where the maximum pixel brightness value is assumed to represent the tree peak, applies a moving window of a specified window size.”