Methodological considerations of terrestrial laser scanning for vegetation monitoring in the sagebrush steppe
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Terrestrial laser scanning (TLS) provides fast collection of high-definition structural information, making it a valuable field instrument to many monitoring applications. A weakness of TLS collections, especially in vegetation, is the occurrence of unsampled regions in point clouds where the sensor’s line-of-sight is blocked by intervening material. This problem, referred to as occlusion, may be mitigated by scanning target areas from several positions, increasing the chance that any given area will fall within the scanner’s line-of-sight from at least one position. Because TLS collections are often employed in remote regions where the scope of sampling is limited by logistical factors such as time and battery power, it is important to design field protocols which maximize efficiency and support increased quantity and quality of the data collected. This study informs researchers and practitioners seeking to optimize TLS sampling methods for vegetation monitoring in dryland ecosystems through three analyses. First, we quantify the 2D extent of occluded regions based on the range from single scan positions. Second, we measure the efficacy of additional scan positions on the reduction of 2D occluded regions (area) using progressive configurations of scan positions in 1 ha plots. Third, we test the reproducibility of 3D sampling yielded by a 5-scan/ha sampling methodology using redundant sets of scans. Analyses were performed using measurements at analysis scales of 5 to 50 cm across the 1-ha plots, and we considered plots in grass and shrub-dominated communities separately. In grass-dominated plots, a center-scan configuration and 5 cm pixel size sampled at least 90% of the area up to 18 m away from the scanner. In shrub-dominated plots, sampling at least 90% of the area was only achieved within a distance of 12 m. We found that 3 and 5 scans/ha are needed to sample at least ~ 70% of the total area (1 ha) in the grass and shrub-dominated plots, respectively, using 5 cm pixels to measure sampling presence-absence. The reproducibility of 3D sampling provided by a 5 position scan layout across 1-ha plots was 50% (shrub) and 70% (grass) using a 5-cm voxel size, whereas at the 50-cm voxel scale, reproducibility of sampling was nearly 100% for all plot types. Future studies applying TLS in similar dryland environments for vegetation monitoring may use our results as a guide to efficiently achieve sampling coverage and reproducibility in datasets.
KeywordsPoint cloud Survey Lidar Dryland Vegetation monitoring Terrestrial laser scanning
This work was supported by a Joint Fire Science Program grant (Project ID: 11-1-2-30), National Oceanic and Atmospheric Administration’s Earth System Research Laboratory (ESRL, Physical Sciences Division) Award NA10OAR4680240, the National Science Foundation Idaho Experimental Program to Stimulate Competitive Research Program, and the NSF under award number EPS-0814387. We thank Randy Lee at Idaho National Laboratory for the use of the TLS; Dr. Rupesh Shrestha, Dr. Aihua Li, Mr. Peter Olsoy, Mr. Kyle Gochnour, and Mr. Samuel Gould for providing lab and field assistance; and Dr. Steve DeLong for providing a constructive review. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the US Government. This article has been peer reviewed and approved for publication consistent with US Geological Survey Fundamental Science Practices (http://pubs.usgs.gov/circ/1367).
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