Dataset papers

Dataset of tree inventory and canopy structure in poplar plantations in Northern Italy


The dataset reports data collected in 38 square (50 x 50m) 0.25 ha plots representative of poplar plantations in Lombardy Region (Northern Italy), which were used to calibrate optical information derived from unmanned aerial vehicle (UAV) and satellite (Sentinel-2) sensors.

In each plot, the diameter at breast height was measured using a caliper; height, stem and crown volume of each tree were then derived from diameter using allometric equations developed in an independent study. Additional canopy attributes (foliage and crown cover, crown porosity, leaf area index) were derived in each plot from 12-20 optical images collected using digital cover photography (DCP).

The collected data allows characterizing the assessment of structure of these plantations, along with their variation over the rotation time. Canopy and crown data also enable the evaluation of optimal rotation and tree spacing, as well as the relationship between stand and canopy structure.

The raw datasets consist of 2,591 records (trees) associated with inventory measurements and 616 records (images) associated with optical canopy measurements. An R code was also provided to calculate plot-level attributes from raw data.

Dataset and associated metadata are freely available at


leaf area index; hybrid I-214 poplar; precision forestry; crown volume; stem volume

Full Text:




Chianucci F. 2020a - Dataset of tree inventory and canopy structure in poplar plantations in Northern Italy. Mendely data, v.1 [Dataset], [Online] Available:

Chianucci F. 2020b - An overview of in situ digital canopy photography in forestry. Canadian Journal of Forest Research 50 (3): 227-242. doi: 10.1139/cjfr-2019-0055.

Chianucci F., Disperati L., Guzzi D., Bianchini D., Nardino V., Lastri C., Rindinella A., Corona P. 2016 - Estimation of canopy attributes in beech forests using true colour digital images from a small fixed-wing UAV. International Journal of Applied Earth Observation and Geoinformation 47: 60-68.

Chianucci F., Puletti N., Grotti M., Ferrara C., Giorcelli A., Coaloa D. and Tattoni C. 2020 - Nondestructive Tree Stem and Crown Volume Allometry in Hybrid Poplar Plantations Derived from Terrestrial Laser Scanning. Forest Science

Chianucci F., Puletti N., Grotti M., Bisaglia C., Giannetti F., Romano E., Brambilla M., Mattioli W., Cabassi G., Bajocco S., Li L., Chirici G., Corona P., Tattoni C. 2021 - Influence of image resolution on canopy cover estimation in poplar plantations from field, aerial and satellite optical imagery. Annals of Silvicultural Research 46:8-13.

Coffin D. 2011 - DCRAW: Decoding raw digital photos in Linux.

Corona P., Chianucci F., Marcelli A., Gianelle D., Fattorini L., Grotti M., Puletti N., Mattioli W. 2020 - Probabilistic sampling and estimation for large-scale assessment of poplar plantations in Northern Italy. European Journal of Forest Research 10.1007/s10342-020-01300-9

Macfarlane C. 2011 - Classification method of mixed pixels does not affect canopy metrics from digital images of forest overstorey. Agricultural and Forest Meteorology 151: 833-840.

Macfarlane C., Hoffman M., Eamus D., Kerp N., Higginson S., McMurtrie R., Adams M.A. 2007 - Estimation of leaf area index in eucalypt forest using digital photography. Agricultural and Forestry Meteorology 143: 176–188.

Macfarlane C., Ryu Y., Ogden G.N., Sonnentag O. 2014 - Digital canopy photography: Exposed and in the raw. Agricultural and Forest Meteorology 197: 244-253.

Marcelli A., Mattioli W., Puletti N., Chianucci F., Gianelle D., Grotti M., Chirici G., D’Amico G., Francini S., Travaglini D., Fattorini L. 2020 - Large-scale two-phase estimation of wood production by poplar plantations exploiting Sentinel-2 data as auxiliary information. Silva Fennica 54 (2): 10247

Copyright (c) 2021 Francesco Chianucci, Luca Marchino, Claudio Bidini, Achille Giorcelli, Domenco Coaloa, Piermario Chiarabaglio, Francesca Giannetti, Gherardo Chirici, Clara Tattoni

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License

All texts reported in and all materials directly downloadable from this page are licensed under a Creative Commons Attribution 4.0 International License.