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Erratum

Erratum: Stefanidou, A., et al. LiDAR-Based Estimates of Canopy Base Height for a Dense Uneven-Aged Structured Forest. Remote Sensing 2020, 12, 1565

by
Alexandra Stefanidou
1,*,
Ioannis Z. Gitas
1,
Lauri Korhonen
2,
Dimitris Stavrakoudis
1 and
Nikos Georgopoulos
1
1
Laboratory of Forest Management and Remote Sensing, Department of Forestry and Natural Environment, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, P.O. Box 248, 54124 Thessaloniki, Greece
2
School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(19), 3116; https://doi.org/10.3390/rs12193116
Submission received: 3 September 2020 / Accepted: 16 September 2020 / Published: 23 September 2020
The authors would like to correct certain errors inadvertently made in Section 3.1 (”LiDAR Data Preprocessing”) of the published research article [1]. The errors are related to the point density and scan angle rank of the LiDAR point cloud derived by the described preprocessing. Hence, Section 3.1 should read as follows:
“Prior to delivery, the LiDAR data were preprocessed by the contractor, namely GEOSYSTEMS HELLAS S.A. (https://www.geosystems-hellas.gr/en/home/). The wavelengths were initially transformed to discrete returns (maximum of seven returns per transmitted pulse) resulting in point density of approximately 19 points m 2 for each channel (Green and NIR). The point clouds were subsequently georeferenced, atmospherically corrected and the noise was reduced (e.g., multiple-time-around echoes elimination). The final point cloud was produced by merging the data of the two channels (without maintaining the information about the channel each point belongs to), removing any duplicated points and classifying the remaining ones into six classes, namely ground, low, medium, and high vegetation, buildings and low point noise.
The overlap between adjacent strips, which ensured a spatially continuous coverage of the surveyed area, along with the afore-described preprocessing resulted in an average point density of 82.99 points m 2 with a scan angle rank from 32 to 32 and a point spacing of 0.4 m.”
The authors would like to apologize for any inconvenience caused to the readers by these changes. The changes do not affect any scientific result of the paper.

Reference

  1. Stefanidou, A.; Gitas, I.Z.; Korhonen, L.; Stavrakoudis, D.; Georgopoulos, N. LiDAR-Based Estimates of Canopy Base Height for a Dense Uneven-Aged Structured Forest. Remote Sens. 2020, 12, 1565. [Google Scholar] [CrossRef]

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MDPI and ACS Style

Stefanidou, A.; Z. Gitas, I.; Korhonen, L.; Stavrakoudis, D.; Georgopoulos, N. Erratum: Stefanidou, A., et al. LiDAR-Based Estimates of Canopy Base Height for a Dense Uneven-Aged Structured Forest. Remote Sensing 2020, 12, 1565. Remote Sens. 2020, 12, 3116. https://doi.org/10.3390/rs12193116

AMA Style

Stefanidou A, Z. Gitas I, Korhonen L, Stavrakoudis D, Georgopoulos N. Erratum: Stefanidou, A., et al. LiDAR-Based Estimates of Canopy Base Height for a Dense Uneven-Aged Structured Forest. Remote Sensing 2020, 12, 1565. Remote Sensing. 2020; 12(19):3116. https://doi.org/10.3390/rs12193116

Chicago/Turabian Style

Stefanidou, Alexandra, Ioannis Z. Gitas, Lauri Korhonen, Dimitris Stavrakoudis, and Nikos Georgopoulos. 2020. "Erratum: Stefanidou, A., et al. LiDAR-Based Estimates of Canopy Base Height for a Dense Uneven-Aged Structured Forest. Remote Sensing 2020, 12, 1565" Remote Sensing 12, no. 19: 3116. https://doi.org/10.3390/rs12193116

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