1. Seidl R., Thom D., Kautz M., Martin-Benito D., Peltoniemi M., Vacchiano G., et al. (2017) - Forest disturbances under climate change. Nat. Clim. Change 7, 395–402. DOI: 10.1038/nclimate3303
2. Pilli R., Alkama R., Cescatti A., Kurz W.A., Grassi G. (2022) - The European forest carbon budget under future climate conditions and current management practices, Biogeosci. 19, 3263–3284. DOI: 10.5194/bg-19-3263-2022
3. Waring RW, Running S.W. (2007) – Forest ecosystems. Analysis at multiple scales, 3rd ed., Elsevier, Berlin.
4. Maselli F., Chiesi M., Moriondo M., Fibbi L., Bindi M., Running, S.W. (2009) - Modelling the forest carbon budget of a Mediterranean region through the integration of ground and satellite data, Ecol. Model. 220, 330 - 342 DOI: 10.1016/j.ecolmodel.2008.10.002
5. Sciarretta A., Marziali L., Squarcini M., Marianelli L., Benassai D., Logli F., Roversi P.F. (2015) - Adaptive management of invasive pests in natural protected areas: the case of Matsucoccus feytaudi in Central Italy, Bulletin Entomol. Res. DOI: 10.1017/S0007485315000851
6. Cambi M., Paffetti D., Vettori C., Picchio R., Venanzi R., Marchi E. (2017) - Assessment of the impact of forest harvesting operations on the physical parameters and microbiological components on a Mediterranean sandy soil in an Italian stone pine stand, Eu. J. Forest Res. 136(2), 205-215. DOI: 10.1007/s10342-016-1020-5
7. Thornton P.E., Running S.W., White M.A. (1997) - Generating surfaces of daily meteorological variables over large regions of complex terrain, J. Hydrol. 190, 214 -251. DOI: 10.1016/S0022-1694(96)03128-9
8. Fibbi L., Maselli F., Pieri M. (2020) - Improved estimation of global solar radiation over rugged terrains by the disaggregation of Satellite Applications Facility on Land Surface Analysis data (LSA SAF), Meteorol. Appl. 27(4), e1940. DOI: 10.1002/met.1940
9. Maselli F., Papale D., Puletti N., Chirici G., Corona P. (2009) - Combining remote sensing and ancillary data to monitor the gross productivity of water-limited forest ecosystems, Remote Sens. Environ. 113, 657-667. DOI: 10.1016/j.rse.2008.11.008
10. Running S.W., Zhao M., (2021) - User’s Guide. Daily GPP and annual NPP (MOD17A2H/A3H) and year-end gap-filled (MOD17A2HGF/A3HGF) products NASA Earth Observing System MODIS Land Algorithm (For collection 6.1). https//modis-land.gsfc.nasa.gov/pdf/MOD17C61UsersGuideV11Mar112021.pdf
11. Golinkoff, J. Biome BGC Version 4.2: Theoretical Framework of Biome-BGC. January 2010. Available online: http://www.ntsg.umt.edu/project/biome-bgc
12. Chirici G., Chiesi M., Fibbi L., Giannetti F., Corona P., Maselli F. (2022) - High spatial resolution modelling of net forest carbon fluxes based on ground and remote sensing data, Agric. For. Meteorol. 316, 108866. DOI: 10.1016/j.agrformet.2022.108866
13. Maselli F., Mari R., Chiesi M. (2013) - Use of LiDAR data to simulate forest net primary production, Int. J. Remote Sens. 34, 2487–2501. DOI: 10.1080/01431161.2012.745019
14. Chiesi M., Fibbi L., Vanucci S., Maselli F. (2024) - Use of remote sensing and biogeochemical modelling to simulate the impact of climatic and anthropogenic factors on forest carbon fluxes, Remote Sens. 16(2), 232. DOI: 10.3390/rs16020232
15. Dietmaier A., McDermid G.J., Rahman M.M., Linke J., Ludwig R. (2019) - Comparison of LiDAR and Digital Aerial Photogrammetry for Characterizing Canopy Openings in the Boreal Forest of Northern Alberta, Remote Sens. 11(16), 1919. DOI: 10.3390/rs11161919

Chapter Information

Bibliographic Information