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    Author(s): Francesca Bottalico; Gherardo Chirici; Raffaello Giannini; Salvatore Mele; Matteo Mura; Michele Puxeddu; Ronald E. McRoberts; Ruben Valbuena; Davide Travaglini
    Date: 2017
    Source: International Journal of Applied Earth Observation and Geoinformation
    Publication Series: Scientific Journal (JRNL)
    Station: Northern Research Station
    PDF: Download Publication  (1.0 MB)


    The conservation of biological diversity is recognized as a fundamental component of sustainable devel-opment, and forests contribute greatly to its preservation. Structural complexity increases the potentialbiological diversity of a forest by creating multiple niches that can host a wide variety of species. To facilitate greater understanding of the contributions of forest structure to forest biological diversity, we modeled relationships between 14 forest structure variables and airborne laser scanning (ALS) data for two Italian study areas representing two common Mediterranean forests, conifer plantations and coppice oaks subjected to irregular intervals of unplanned and non-standard silvicultural interventions. The objectives were twofold: (i) to compare model prediction accuracies when using two types of ALS metrics, echo-based metrics and canopy height model (CHM)-based metrics, and (ii) to construct inferences in the form of confidence intervals for large area structural complexity parameters. Our results showed that the effects of the two study areas on accuracies were greater than the effects of the two types of ALS metrics. In particular, accuracies were less for the more complex study area interms of species composition and forest structure. However, accuracies achieved using the echo-based metrics were only slightly greater than when using the CHM-based metrics, thus demonstrating that both options yield reliable and comparable results. Accuracies were greatest for dominant height (Hd) (R2= 0.91; RMSE% = 8.2%) and mean height weighted by basal area (R2= 0.83; RMSE% = 10.5%) when using the echo-based metrics, 99th percentile of the echo height distribution and interquantile distance. For the forested area, the generalized regression (GREG) estimate of mean Hd was similar to the simple random sampling (SRS) estimate, 15.5 m for GREG and 16.2 m SRS. Further, the GREG estimator with standard error of 0.10 m was considerable more precise than the SRS estimator with standard error of 0.69 m.

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    Bottalico, Francesca; Chirici, Gherardo; Giannini, Raffaello; Mele, Salvatore; Mura, Matteo; Puxeddu, Michele; McRoberts, Ronald E.; Valbuena, Ruben; Travaglini, Davide. 2017. Modeling Mediterranean forest structure using airborne laser scanning data. International Journal of Applied Earth Observation and Geoinformation. 57: 145-153.


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    Forest biodiversity, Forest inventory, Forest monitoring, Structural complexity indicators, Airborne laser scanning, LiDAR

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