Research, 2018-01-17

Airborne Laser Scanner to predict forest inventories variables, to map forest structure, and to quantify forest natural and human disturbances

Light detection and ranging (LiDAR) characterizes the 3D structures of trees, thus can provide useful inputs (e.g., tree species, heights, crown sizes, biomass) for ecosystem understanding and for efficient forest management. New techniques are quickly emerging to collect LiDAR with better quality and capabilities. However, there are questions remaining unsolved regarding the successful application of LiDAR data and techniques to complex environments such as mediterrenean and mixed forest. The increased point density of discrete return LiDAR data or even full waveform LiDAR data introduce new challenges as well. Our laboratory is involved in research activity related to: + quantification of forest natruale damages + prediction of forest inventories variables + mapping forest structures

Paper

Gherardo Chirici, Francesca Bottalico, Francesca Giannetti, Barbara Del Perugia, Davide Travaglini, Susanna Nocentini, Erico Kutchartt, Enrico Marchi, Cristiano Foderi, Marco Fioravanti, Lorenzo Fattorini, Lorenzo Bottai, Ronald E. McRoberts, Erik Næsset Piermaria Corona, Bernardo Gozzini (2018). Assessing forest windthrow damage using single-date, post-event airborne laser scanning data. Forestry: An International Journal of Forest Research, 91, 27-37. doi: https://doi.org/10.1093/forestry/cpx029
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 laserscanning data. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, vol. 57, pp. 145-153, ISSN:1872-826X doi: http://dx.doi.org/10.1016/J.JAG.2016.12.013
Mura, Matteo; Mcroberts, Ronald E; Chirici, Gherardo; Marchetti, Marco (2016). Statistical inference for forest structural diversity indices using airborne laser scanning data and the k-Nearest Neighbors technique. REMOTE SENSING OF ENVIRONMENT, vol. 186, pp. 678-686, ISSN:0034-4257 doi : http://dx.doi.org/10.1016/J.RSE.2016.09.010
Chirici, Gherardo; Mcroberts, Ronald E.; Fattorini, Lorenzo; Mura, Matteo; Marchetti, Marco (2016). Comparing echo-based and canopy height model-based metrics for enhancing estimation of forest aboveground biomass in a model-assisted framework. REMOTE SENSING OF ENVIRONMENT, vol. 174, pp. 1-9, ISSN:0034-4257 doi: http://dx.doi.org/10.1016/J.RSE.2015.11.010
Moser, Paolo; Vibrans, Alexander C.; Mcroberts, Ronald E.; Næsset, Erik; Gobakken, Terje; Chirici, Gherardo; Mura, Matteo; Marchetti, Marco (2016). Methods for variable selection in LiDAR-assisted forest inventories. FORESTRY, pp. 112-124, ISSN:0015-752X doi: http://dx.doi.org/10.1093/FORESTRY/CPW041
Mura, Matteo; Mcroberts, Ronald E.; Chirici, Gherardo; Marchetti, Marco (2015). Estimating and mapping forest structural diversity using airborne laser scanning data. REMOTE SENSING OF ENVIRONMENT, vol. 170, pp. 133-142, ISSN:0034-4257 doi: http://dx.doi.org/10.1016/J.RSE.2015.09.016

Master Thesis

D'Amico Giovanni (2017). A spatially-explicit method to assess the growing stock volume in coastal pine forests (Pinus pinea L.) in Tuscany using laser scanning data. Supervisors: Gherardo Chirici, Davide Travaglini English abstract available on-line
Grotti Mirko (2017). Impiego di dati Airborne Laser Scanning per la stima della provvigione legnosa e delle categorie assortimentali: il caso di studio del complesso forestale di Rincine (FI). Supervisors: Gherardo Chirici, Nicola Puletti English abstract available on-line Italian Full text available on-line