Improving the estimation of canopy cover from UAV-LiDAR data using a pit-free CHM-based method

Accurate and rapid estimation of canopy cover (CC) is crucial for many ecological and environmental models and for forest management. Unmanned aerial vehicle-light detecting and ranging (UAV-LiDAR) systems represent a promising tool for CC estimation due to their high mobility, low cost, and high po...

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Published inInternational journal of digital earth Vol. 14; no. 10; pp. 1477 - 1492
Main Authors Cai, Shangshu, Zhang, Wuming, Jin, Shuangna, Shao, Jie, Li, Linyuan, Yu, Sisi, Yan, Guangjian
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis 03.10.2021
Taylor & Francis Ltd
Taylor & Francis Group
Subjects
Accuracy
Canopies
Canopy
Canopy cover
data collection
ecological models
Environment models
Environmental modeling
environmental models
Forest management
Lidar
light detecting and ranging
pit-free CHM
Plant cover
testing
unmanned aerial vehicle
Unmanned aerial vehicles
within-crown gaps
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Abstract Accurate and rapid estimation of canopy cover (CC) is crucial for many ecological and environmental models and for forest management. Unmanned aerial vehicle-light detecting and ranging (UAV-LiDAR) systems represent a promising tool for CC estimation due to their high mobility, low cost, and high point density. However, the CC values from UAV-LiDAR point clouds may be underestimated due to the presence of large quantities of within-crown gaps. To alleviate the negative effects of within-crown gaps, we proposed a pit-free CHM-based method for estimating CC, in which a cloth simulation method was used to fill the within-crown gaps. To evaluate the effect of CC values and within-crown gap proportions on the proposed method, the performance of the proposed method was tested on 18 samples with different CC values (40−70%) and 6 samples with different within-crown gap proportions (10−60%). The results showed that the CC accuracy of the proposed method was higher than that of the method without filling within-crown gaps (R 2  = 0.99 vs 0.98; RMSE = 1.49% vs 2.2%). The proposed method was insensitive to within-crown gap proportions, although the CC accuracy decreased slightly with the increase in within-crown gap proportions.
AbstractList Accurate and rapid estimation of canopy cover (CC) is crucial for many ecological and environmental models and for forest management. Unmanned aerial vehicle-light detecting and ranging (UAV-LiDAR) systems represent a promising tool for CC estimation due to their high mobility, low cost, and high point density. However, the CC values from UAV-LiDAR point clouds may be underestimated due to the presence of large quantities of within-crown gaps. To alleviate the negative effects of within-crown gaps, we proposed a pit-free CHM-based method for estimating CC, in which a cloth simulation method was used to fill the within-crown gaps. To evaluate the effect of CC values and within-crown gap proportions on the proposed method, the performance of the proposed method was tested on 18 samples with different CC values (40−70%) and 6 samples with different within-crown gap proportions (10−60%). The results showed that the CC accuracy of the proposed method was higher than that of the method without filling within-crown gaps (R ² = 0.99 vs 0.98; RMSE = 1.49% vs 2.2%). The proposed method was insensitive to within-crown gap proportions, although the CC accuracy decreased slightly with the increase in within-crown gap proportions.
Accurate and rapid estimation of canopy cover (CC) is crucial for many ecological and environmental models and for forest management. Unmanned aerial vehicle-light detecting and ranging (UAV-LiDAR) systems represent a promising tool for CC estimation due to their high mobility, low cost, and high point density. However, the CC values from UAV-LiDAR point clouds may be underestimated due to the presence of large quantities of within-crown gaps. To alleviate the negative effects of within-crown gaps, we proposed a pit-free CHM-based method for estimating CC, in which a cloth simulation method was used to fill the within-crown gaps. To evaluate the effect of CC values and within-crown gap proportions on the proposed method, the performance of the proposed method was tested on 18 samples with different CC values (40−70%) and 6 samples with different within-crown gap proportions (10−60%). The results showed that the CC accuracy of the proposed method was higher than that of the method without filling within-crown gaps (R2 = 0.99 vs 0.98; RMSE = 1.49% vs 2.2%). The proposed method was insensitive to within-crown gap proportions, although the CC accuracy decreased slightly with the increase in within-crown gap proportions.
Accurate and rapid estimation of canopy cover (CC) is crucial for many ecological and environmental models and for forest management. Unmanned aerial vehicle-light detecting and ranging (UAV-LiDAR) systems represent a promising tool for CC estimation due to their high mobility, low cost, and high point density. However, the CC values from UAV-LiDAR point clouds may be underestimated due to the presence of large quantities of within-crown gaps. To alleviate the negative effects of within-crown gaps, we proposed a pit-free CHM-based method for estimating CC, in which a cloth simulation method was used to fill the within-crown gaps. To evaluate the effect of CC values and within-crown gap proportions on the proposed method, the performance of the proposed method was tested on 18 samples with different CC values (40−70%) and 6 samples with different within-crown gap proportions (10−60%). The results showed that the CC accuracy of the proposed method was higher than that of the method without filling within-crown gaps (R 2  = 0.99 vs 0.98; RMSE = 1.49% vs 2.2%). The proposed method was insensitive to within-crown gap proportions, although the CC accuracy decreased slightly with the increase in within-crown gap proportions.
Author Shao, Jie
Li, Linyuan
Cai, Shangshu
Jin, Shuangna
Yan, Guangjian
Zhang, Wuming
Yu, Sisi
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  organization: Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University
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Cites_doi 10.1093/forestry/72.1.59
10.1016/j.agrformet.2018.08.026
10.1186/s40663-019-0212-0
10.3390/rs12020298
10.5589/m09-038
10.5589/m07-029
10.1016/j.rse.2003.08.006
10.14214/sf.402
10.1016/j.rse.2012.02.001
10.1016/j.isprsjprs.2010.08.002
10.1109/JSTARS.2019.2918572
10.1109/LGRS.2010.2079913
10.1016/j.foreco.2005.10.056
10.1016/j.measurement.2017.03.007
10.1080/01431160701736489
10.1080/01431161.2013.779398
10.14214/sf.315
10.1016/j.isprsjprs.2016.01.006
10.1016/j.agrformet.2018.07.028
10.1016/j.jag.2015.04.020
10.3390/rs4061519
10.1186/s40663-019-0173-3
10.3390/rs8060501
10.3390/rs11020211
10.1093/forestscience/55.2.132
10.1016/j.rse.2018.06.022
10.1080/01431160802082155
10.5589/m03-030
10.1016/j.isprsjprs.2018.11.001
10.1016/j.agrformet.2019.01.024
10.1080/01431161.2011.577830
10.3390/rs11080908
10.1016/j.rse.2017.03.021
10.1016/j.isprsjprs.2013.04.001
10.14214/sf.463
10.1126/science.1244693
10.1016/j.ufug.2016.08.011
10.1016/j.isprsjprs.2020.03.008
10.1080/01431161.2013.833361
10.3390/rs1041298
10.3390/rs70810017
10.1016/j.rse.2010.12.011
10.1109/JSTARS.2017.2711482
10.1016/j.foreco.2012.06.020
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  doi: 10.1093/forestry/72.1.59
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  doi: 10.1016/j.agrformet.2018.08.026
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  doi: 10.1186/s40663-019-0212-0
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SubjectTerms Accuracy
Canopies
Canopy
Canopy cover
data collection
ecological models
Environment models
Environmental modeling
environmental models
Forest management
Lidar
light detecting and ranging
pit-free CHM
Plant cover
testing
unmanned aerial vehicle
Unmanned aerial vehicles
within-crown gaps
Title Improving the estimation of canopy cover from UAV-LiDAR data using a pit-free CHM-based method
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