Persone Dottori di Ricerca2022Giovanni D'Amico

Giovanni D'Amico

PhD

Curriculum: Forest economics, planning and wood science

Supervisor: Gherardo Chirici

Email: giovanni.damico@unifi.it

Office address: via San Bonaventura 13, Firenze

Profile

I am Giovanni D’Amico, I graduated at the University of Florence where I obtained a Bachelor's Degree in Forest and Environmental Sciences and a Master's degree in Forest Systems Sciences and Technologies (110/110 cum laude).

My research focuses on analysis of remote sensing data for the detection and management of forest resources.

My other interest is music, indeed I hold a Diploma in Percussion Instruments at the Conservatory “Maderna” in Cesena. 

Research interests and PhD project

My main research interests focus on forest inventories, remote sensing, and geomatics. Remote sensing applications using multiple sources of information to support sustainable forest management.

Papers

• Chirici G, Giannetti F, Travaglini D, Nocentini S, Francini S, D’Amico G, Calvo E, Fasolini D, Broll M, Maistrelli F, Tonner J, Pietrogiovanna M, Oberlechner K, Andriolo A, Comino R, Faidiga A, Pasutto I, Carraro G, Zen S, Contarin F, Alfonsi L, Wolynski A, Zanin M, Gagliano C, Tonolli S, Zoanetti R, Tonetti R, Cavalli R, Lingua E, Pirotti F, Grigolato S, Bellingeri D, Zini E, Gianelle D, Dalponte M, Pompei E, Stefani A, Motta R, Morresi D, Garbarino M, Alberti G, Valdevit F, Tomelleri E, Torresani M, Tonon G, Marchi M, Corona P, Marchetti M (2019). Stima dei danni della tempesta “Vaia” alle foreste in Italia. Forest@ 16: 3-9. - doi: 10.3832/efor3070-016
• Vangi, E.; D’Amico, G.; Francini, S.; Giannetti, F.; Lasserre, B.; Marchetti, M.; McRoberts, R.E.; Chirici, G. The Effect of Forest Mask Quality in the Wall-to-Wall Estimation of Growing Stock Volume. Remote Sens. 2021, 13, 1038. https://doi.org/10.3390/rs13051038
• Marcelli A., Mattioli W., Puletti N., Chianucci F., Gianelle D., Grotti M., Chirici G., D' Amico G., Francini S., Travaglini D., Fattorini L., Corona P. (2020). Large-scale two-phase estimation of wood production by poplar plantations exploiting Sentinel-2 data as auxiliary information. Silva Fennica vol. 54 no. 2 article id 10247. https://doi.org/10.14214/sf.10247
• Vangi E, D’Amico G, Francini S, Giannetti F, Lasserre B, Marchetti M, McRoberts RE, Chirici G. The Effect of Forest Mask Quality in the Wall-to-Wall Estimation of Growing Stock Volume. Remote Sensing. 2021; 13(5):1038. https://doi.org/10.3390/rs13051038
• Vangi, E.; D’Amico, G.; Francini, S.; Giannetti, F.; Lasserre, B.; Marchetti, M.; Chirici, G. The New Hyperspectral Satellite PRISMA: Imagery for Forest Types Discrimination. Sensors 2021, 21, 1182. https://doi.org/10.3390/s21041182
• D’Amico G, Vangi E, Francini S, Giannetti F, Nicolaci A, Travaglini D, Massai L, Giambastiani Y, Terranova C, Chirici G (2021). Are we ready for a National Forest Information System? State of the art of forest maps and airborne laser scanning data availability in Italy. iForest 14: 144-154. - doi: 10.3832/ifor3648-014
• Francini S, D’Amico G, Mencucci M, Seri G, Gravano E, Chirici G (2021). Telerilevamento e procedure automatiche: validi strumenti di supporto al monitoraggio delle utilizzazioni forestali. Forest@ 18: 27-34. - doi: 10.3832/efor3835-018
• Giannetti, F.; Pecchi, M.; Travaglini, D.; Francini, S.; D’Amico, G.; Vangi, E.; Cocozza, C.; Chirici, G. Estimating VAIA Windstorm Damaged Forest Area in Italy Using Time Series Sentinel-2 Imagery and Continuous Change Detection Algorithms. Forests 2021, 12, 680. https://doi.org/10.3390/f12060680
• Francini S., McRoberts R.E., D’Amico G., Coops N.C., Hermosilla T., White J.C., Wulder M.A., Marchetti M., Scarascia MugnozzaG., Chirici G., (Submitted). An open science-open data approach for statistically robust estimation of forest disturbance area. International Journal of Applied Earth Observation
• D’Amico G., Francini S., Giannetti F., Vangi E., Travaglini D., Chianucci F., Mattioli W., Grotti M., Puletti N., Corona P., Chirici G. (Submitted). A deep learning approach for automatic mapping of poplar plantations using Sentinel-2 imagery. GIScience & Remote Sensing.

Conference talks and seminars

• D'Amico G., Del Perugia B., Chirici G., Giannetti F., Nocentini S., Travaglini D. - “Stima della provvigione delle pinete litoranee di pino domestico della Toscana con dati telerilevati laser scanning -  Spatial estimation of standing volume in Italian stone pine forests along the Tuscan coast with airborne laser scanning data” session n° 9 - Forest monitoring and planning. 4th Italian National Congress of Silviculture, November 5 - 9, 2018, Turin - Italy.
• D’Amico G., Francini S., Giannetti F., Vangi E., Travaglini D., Mattioli W., Chianucci F., Grotti M., Puletti N., Corona P., Azzi N., Chirici G., Use of multitemporal Sentinel-2 imagery for semiautomatic classification of poplar plantations: a deep learning approach. Sessione Parallela 11: Innovazione nel monitoraggio forestale. XII Congresso Nazionale SISEF. Palermo, 12-15 November 2019
• Borghi C., Francini S., Pollastrini M., Bussotti F., Travaglini D., Marchetti M., Munafò M., Scarascia-Mugnozza G., Tonti G., Ottaviano M., Giuliani C., Cavalli A., Vangi E., D'Amico G., Giannetti F., Chirici G., Monitoring thirty-five years of Italian forest disturbance using Landsat time series.
• Giannetti F., Tattoni C., D'Amico G., Francini S., Chirici G., Romano E., Brambilla M., Travaglini D., Vangi E., Chianucci F., Multiscale monitoring of poplar plantations using proximal and remotely-sensed imagery
• D'Amico G., Giannetti F., Vangi E., Borghi C., Francini S., Travaglini D., Chirici G. Multitemporal LiDAR data for forest carbon monitoring in Mediterranean Forest,
• Fanara V., Chirici G., Cocozza C., D'Amico G., Giannetti F., Francini S., Salbitano F., Speak A., Vangi E., Travaglini D., Estimation of Multitemporal Dry Deposition of Air Pollution by Urban Forests at City Scale
• Giannetti F., Giambastiani Y., Fiorentini S., Travaglini D., Francini S., Vangi E., D'Amico G., Chiesi M., Maselli F., Chirici G., The Key Role of Multiscale Remote Sensing Data to Develop Forest Decision Support Systems