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Calhoun CZO - LiDAR - LiDAR features for the Calhoun CZO forest plots (2015)

LiDAR features for the Calhoun CZO forest plots

Variables:  latitude ('lat'), longitude ('long'), 'elevation', 'lat(Y)_NAD83 UTM 17N', 'long(X)_NAD83 UTM 17N', minimum return height('min_h'), maximum return height ('max_h'), average return height ('avg_h'), standard deviation of all returns ('std_h'), LiDAR return height percentiles ('p05' to'p90'), canopy cover ('cov', see details below), canopy density ('dns', see details below), (FIC', see details below ), minimum scan angle ('min_scan'), maximum scan angle ('max_scan'), average scan angle ('avg_scan_angle'), number of returns ('N_returns'), number of returns from vegetatation ('Nveg', see detail below), and number of return from ground ('Nground').

Standard Variables:  Lidar|Canopy Closure|Elevation|Latitude|Longitude

Date Range:  (2015-2015)

Dataset Creators/Authors:  Majasalmi, Titta

Contact:  Titta Majasalmi, Department of Forest Sciences, University of Helsinki, P.O. Box 27, Helsinki, Finland,

Field Area:   Calhoun Experimental Forest and Eco-hydrology Experiments | Calhoun Long-Term Soil-Ecosystem Plots and Reference Areas

Keywords & XML
  • Description

    Dataset includes LiDAR features for 35 forest plots located at the Calhoun CZO. Both LiDAR data acquisition and field measurements using LAI-2000 (LI-COR, 1992) were performed during summer 2014. LAI-2000 is an optical device used to estimate Leaf Area Index (LAI, hemisurface area of foliage per unit horizontal ground surface area) and canopy gap fraction at five zenith angles. The LiDAR data were processed to match with the LAI-2000 measurements, and thus LiDAR returns arriving at angles more than 15 degrees were excluded before any calculations were performed.

    Processing chain of LiDAR data included: 1) merging .las files which have forest plots near the edges, 2) calculating the ground surface, 3) removing noise, 4) removing duplicates, 5) extracting returns for the forest plots using a 15-m circle, 6) excluding returns arriving at an angle bigger than ±15 degrees, 7) calculation of return heights, 8) classifying returns to ground and vegetation based on return heights (limit set to 1.37-m), 9) calculation of LiDAR features for all forest plots.

    The LiDAR features provided in this dataset are updated version of those presented earlier by Majasalmi et al. (2015).


    Majasalmi, T., Palmroth, S., Cook, W., Brecheisen, Z., Richter, D. (2015): Estimation of LAI, fPAR and AGB based on data from Landsat 8 and LiDAR at the Calhoun CZO. Calhoun CZO 2015 Summer Science Meeting.

    LI-COR, 1992. LAI-2000 Plant Canopy Analyzer, Instruction manual.
    Definitions: cov = The canopy cover is computed as the number of first returns above the height cutoff divided by the number of all first returns and output as a percentage. dns = canopy density is computed as the number of points above the height cutoff divided by the number of all returns. For more details see Korhonen and Morsdorf, 2013: FCI = First echo cover index: FCI=((∑〖Single〗_Canopy+∑〖First〗_Canopy))⁄((∑〖Single〗_All+∑〖First〗_All)) VCC1 and VCC2 = Vertical canopy cover indices: VCC1=FCI-0.6233*θ_Scan VCC2=FCI-0.0253*θ_Scan*F_Max SCI = near-vertical canopy closure or “Solberg's cover index”: SCI=∑〖Single〗_Canopy+0.5 ((∑〖First〗_Canopy+∑〖Last〗_Canopy ))⁄(∑〖Single〗_All )+0.5(∑〖First〗_All+∑〖Last〗_All ) ACI = “All echo cover index”, similar to FCI, but take into account all echo types above the height threshold: ACI=(∑〖All〗_Canopy)⁄(∑All) Korhonen, L., Morsdorf, F. 2013. Estimation of canopy cover, gap fraction and leaf area index with airborne laser scanning, chapter 20 in Forestry applications of airborne laser scanning concepts and case studies, pp.397-413, Springer.
  • Keywords

    High density LiDAR, forest canopy structure, feature extraction

    XML Metadata

    XML is in ISO-19115 geographic metadata format, compatible with ESRI Geoportal Server.

  • Citation for This Webpage

    Majasalmi, Titta (2015). "CZO Dataset: Calhoun CZO - LiDAR (2015) - LiDAR features for the Calhoun CZO forest plots." Retrieved 29 Jan 2020, from

  • Publications

    Primary Publications


    Estimation of LAI, fPAR and AGB based on data from Landsat 8 and LiDAR at the Calhoun CZO. Majasalmi, T., Palmroth, S., Cook, W., Brecheisen, Z., Richter, D. (2015): Calhoun CZO 2015 Summer Science Meeting


Calhoun Experimental Forest - Remote sensing of vegetation

(.csv)   Data Level 4

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