TY - JOUR
T1 - Examining Forest Structure With Terrestrial Lidar
T2 - Suggestions and Novel Techniques Based on Comparisons Between Scanners and Forest Treatments
AU - Donager, Jonathon J.
AU - Sankey, Temuulen Ts
AU - Sankey, Joel B.
AU - Sanchez Meador, Andrew J.
AU - Springer, Abraham E.
AU - Bailey, John D.
N1 - Funding Information:
We would like to thank Tim Andrews from the USGS Grand Canyon Monitoring and Research Center for lending his knowledge in the process of building the ATLS scanner. Also, thanks to Nicole Donager for all her help in collecting locations of trees at these field sites. This manuscript is submitted for publication with the understanding that the U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. This study was funded by Bureau of Reclamation grant RC13AC80032. Joel Sankey is supported by the USGS Southwest Biological Science Center. Data generated during this study are available from the USGS ScienceBase-Catalog (Donager et al.,).
Funding Information:
We would like to thank Tim Andrews from the USGS Grand Canyon Monitoring and Research Center for lending his knowledge in the process of building the ATLS scanner. Also, thanks to Nicole Donager for all her help in collecting locations of trees at these field sites. This manuscript is submitted for publication with the understanding that the U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. This study was funded by Bureau of Reclamation grant RC13AC80032. Joel Sankey is supported by the USGS Southwest Biological Science Center. Data generated during this study are available from the USGS ScienceBase-Catalog (Donager et al., 2018).
Publisher Copyright:
©2018. The Authors.
PY - 2018/11
Y1 - 2018/11
N2 - Terrestrial laser scanners (TLSs) provide a tool to assess and monitor forest structure across forest landscapes. We present TLS methods, suggestions, and mapped guidelines for planning TLS acquisitions at varying scales and forest densities. We examined rates of point-density decline with distance from two TLS that acquire data at relatively high and low point density and found that the rates were nearly identical between scanners (p value <0.01), suggesting that our findings are applicable to a range of TLS types. Using unique, TLS-adapted processing methods, we determined the relative accuracy of TLS-derived plot-scale estimates of tree height, diameter-at-breast-height, height-to-canopy, tree counts, as well as treatment-scale tree density and patch metrics, using both high point density and low point density TLS among thinned and nonthinned forest treatments. The high-density TLS consistently provides more accurate estimates of plot-level metrics (R2 = 0.46 to 0.87) than the low-density TLS (R2 = −0.14 to 0.53). At treatment scales, tree density estimates are similar among scanners (R2 = 0.95 vs. 0.71), as are canopy cover and patch metrics. We develop and present the normalized density-distance index (NDDI), which can account for up to 59% of the variance in estimate error and can be used to guide TLS-data acquisition plans. This index indicates whether a given location has generally higher point density (higher NDDI) relative to the distance from the scanner and can be used as a proxy for uncertainty. Using NDDI as a guide for fair comparison between scanners, both plot- and treatment-scale estimates improved.
AB - Terrestrial laser scanners (TLSs) provide a tool to assess and monitor forest structure across forest landscapes. We present TLS methods, suggestions, and mapped guidelines for planning TLS acquisitions at varying scales and forest densities. We examined rates of point-density decline with distance from two TLS that acquire data at relatively high and low point density and found that the rates were nearly identical between scanners (p value <0.01), suggesting that our findings are applicable to a range of TLS types. Using unique, TLS-adapted processing methods, we determined the relative accuracy of TLS-derived plot-scale estimates of tree height, diameter-at-breast-height, height-to-canopy, tree counts, as well as treatment-scale tree density and patch metrics, using both high point density and low point density TLS among thinned and nonthinned forest treatments. The high-density TLS consistently provides more accurate estimates of plot-level metrics (R2 = 0.46 to 0.87) than the low-density TLS (R2 = −0.14 to 0.53). At treatment scales, tree density estimates are similar among scanners (R2 = 0.95 vs. 0.71), as are canopy cover and patch metrics. We develop and present the normalized density-distance index (NDDI), which can account for up to 59% of the variance in estimate error and can be used to guide TLS-data acquisition plans. This index indicates whether a given location has generally higher point density (higher NDDI) relative to the distance from the scanner and can be used as a proxy for uncertainty. Using NDDI as a guide for fair comparison between scanners, both plot- and treatment-scale estimates improved.
KW - 3-D models
KW - forest assessment
KW - forest structure
KW - individual tree segmentation
KW - lidar
KW - remote sensing
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U2 - 10.1029/2018EA000417
DO - 10.1029/2018EA000417
M3 - Article
AN - SCOPUS:85056299807
SN - 2333-5084
VL - 5
SP - 753
EP - 776
JO - Earth and Space Science
JF - Earth and Space Science
IS - 11
ER -