Abstract
Forests provide many services to society but climate change, biotic, and abiotic forest disturbances are altering ecological systems. Among these, Mediterranean pine forests, distinctive environmental elements of the Italian coastal area for both natural and historical reasons, are particularly susceptible. As evidenced by numerous wind damages, drought stress, and more recently Toumeyella parvicornis infestation in central Italy. On the other hand, there is a lack of reliable and spatialized data on the spread of infestations and stress states. In this context, their monitoring using all available sources of information is essential. In this study, we used Sentinel-2 optical data to monitor the health status and damage that occurred to Mediterranean pine forests in Italy in recent years (2018–2022). In terms of damaged area, we identified a growing trend over the years (4.5% of Italian Mediterranean pine forests in 2018, 4.0% in 2019, 6.4% in 2020, and 14.6% in 2021), with an abrupt increase in 2022 (24.2%). While our model was calibrated using reference data available for a Mediterranean pine forest study area of about 1000 ha in central Italy and 80% accuracy was reported, more exhaustive reference data should be used for providing solid estimates. On the other hand, Sentinel-2 data proved to be a relevant source of information, pointing to a very serious situation for Mediterranean pine forests.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Hlásny, T., Zimová, S., Merganičová, K., Štěpánek, P., Modlinger, R., Turčáni, M.: Devastating outbreak of bark beetles in the Czech Republic: drivers, impacts, and management implications. For. Ecol. Manage. 490, 119075 (2021). https://doi.org/10.1016/j.foreco.2021.119075
Seidl, R., Rammer, W.: Climate change amplifies the interactions between wind and bark beetle disturbances in forest landscapes. Landscape Ecol. 32, 1485–1498 (2017). https://doi.org/10.1007/s10980-016-0396-4
McDowell, N.G., Grossiord, C., Adams, H.D., Pinzón-Navarro, S., Mackay, D.S., Breshears, D.D., Allen, C.D., Borrego, I., Dickman, L.T., Collins, A., Gaylord, M., McBranch, N., Pockman, W.T., Vilagrosa, A., Aukema, B., Goodsman, D., Xu, C.: Mechanisms of a coniferous woodland persistence under drought and heat. Environ. Res. Lett. 14(4), 045014 (2019). https://doi.org/10.1088/1748-9326/ab0921
Pollastrini, M., Puletti, N., Selvi, F., Iacopetti, G., Bussotti, F.: Widespread crown defoliation after a drought and heat wave in the forests of Tuscany (central Italy) and their recovery—a case study from summer 2017. Front. Forest. Glob. Change 2, 74 (2019). https://doi.org/10.3389/ffgc.2019.00074
Garonna, A.P., Foscari, A., Russo, E., Jesu, G., Somma, S., Cascone, P., Guerrieri, E.: The spread of the non-native pine tortoise scale Toumeyella parvicornis (Hemiptera: Coccidae) in Europe: a major threat to Pinus pinea in Southern Italy. iForest 11, 628–634 (2018). https://doi.org/10.3832/ifor2864-011
Garonna, A.P., Scarpato, S., Vicinanza, F., Espinosa, B.: First report of Toumeyella parvicornis (Cockerell) in Europe (Hemiptera, Coccidae). Zootaxa 3949(1), 142–146 (2015). https://doi.org/10.11646/zootaxa.3949.1.9
Di Sora, N., Rossini, L., Contarini, M., Chiarot, E., Speranza, S.: Endotherapic treatment to control Toumeyella parvicornis Cockerell infestations on Pinus pinea L. Pest Manag. Sci. 78(6), 2443–2448 (2022). https://doi.org/10.1002/ps.6876
Abdullah, H., Darvishzadeh, R., Skidmore, A.K., Groen, T.A., Heurich, M.: European spruce bark beetle (Ips typographus, L.) green attack affects foliar reflectance and biochemical properties. Int. J. Appl. Earth Obs. Geoinf. 64, 199–209 (2018). https://doi.org/10.1016/j.jag.2017.09.009
El-Ghany, A., Nesreen, M., El-Aziz, A., Shadia, E., Marei, S.S.: A review: application of remote sensing as a promising strategy for insect pests and diseases management. Environ. Sci. Pollut. Res. 27(27), 33503–33515 (2020). https://doi.org/10.1007/s11356-020-09517-2
Huo, L., Persson, H.J., Lindberg, E.: Early detection of forest stress from European spruce bark beetle attack, and a new vegetation index: normalized distance red & SWIR (NDRS). Remote Sens. Environ. 255, 112240 (2021). https://doi.org/10.1016/j.rse.2020.112240
Giannetti, F., Pegna, R., Francini, S., McRoberts, R.E., Travaglini, D., Marchetti, M., Scarascia Mugnozza, G., Chirici, G.: A new method for automated clear-cut disturbance detection in mediterranean coppice forests using landsat time series. Remote Sens. 12(22), 3720 (2020). https://doi.org/10.3390/rs12223720
Francini, S., McRoberts, R.E., Giannetti, F., Marchetti, M., Scarascia Mugnozza, G., Chirici, G.: The Three Indices Three Dimensions (3I3D) algorithm: a new method for forest disturbance mapping and area estimation based on optical remotely sensed imagery. Int. J. Remote Sens. 42(12), 4693–4711 (2021). https://doi.org/10.1080/01431161.2021.1899334
Del Perugia, B., Travaglini, D., Bottalico, F., Nocentini, S., Rossi, P., Salbitano, F., Sanesi, G.: Are Italian stone pine forests (Pinus pinea L.) an endangered coastal landscape? A case study in Tuscany (Central Italy). L’Italia Forestale e Montana 72(2), 103–121 2017. https://doi.org/10.4129/ifm.2017.2.01
Baroni, C., Brunetti, M., Cerrato, R., Coppola, A., Betti, G., & Salvatore, M.C.: A long-term chronology of Pinus pinea L. from Parco della Versiliana (Pietrasanta, Italy) derived from treefall induced by a windstorm on March 4th–5th, 2015. Dendrochronologia 62, 125710 (2020). https://doi.org/10.1016/j.dendro.2020.125710
Francini, S., D’Amico, G., Vangi, E., Borghi, C., Chirici, G.: Integrating GEDI and landsat: spaceborne lidar and four decades of optical imagery for the analysis of forest disturbances and biomass changes in Italy. Sensors 22(5), 2015 (2022a). https://doi.org/10.3390/s22052015
Francini, S., McRoberts, R.E., D’Amico, G., Coops, N.C., Hermosilla, T., White, J.C., Wulder, M.A., Marchetti, M., Mugnozza, G.S., Chirici, G.: An open science and open data approach for the statistically robust estimation of forest disturbance areas. Int. J. Appl. Earth Obs. Geoinf. 106, 102663 (2022). https://doi.org/10.1016/j.jag.2021.102663
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., Moore, R.: Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18–27 (2017). https://doi.org/10.1016/j.rse.2017.06.031
European Enviromental Agency, EEA (2007). Enviromental Statement; Office for Official Publications of the European Communities: Luxembourg. ISBN 978-92-9167-936-2
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. 13, 1038 (2021). https://doi.org/10.3390/rs13051038
Vizzarri, M., Chiavetta, U., Chirici, G., Garfì, V., Bastrup-Birk, A., Marchetti, M.: Comparing multisource harmonized forest types mapping: a case study from central Italy. Iforest-Biogeosci. For. 8, 59–66 (2015). https://doi.org/10.3832/ifor1133-007
D’Amico, G., Vangi, E., Francini, S., Giannetti, F., Nicolaci, A., Travaglini, D., Massai, L., Giambastiani, Y., Terranova, C., Chirici, G.: 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 (2021). https://doi.org/10.3832/ifor3648-014
Baetens, L., Desjardins, C., Hagolle, O.: Validation of copernicus sentinel-2 cloud masks obtained from MAJA, Sen2Cor, and FMask processors using reference cloud masks generated with a supervised active learning procedure. Remote Sens. 11(2019), 433 (2019). https://doi.org/10.3390/rs11040433
Kennedy, R.E., Yang, Z., Gorelick, N., Braaten, J., Cavalcante, L., Cohen, W.B., Healey, S.: Implementation of the LandTrendr algorithm on Google Earth Engine. Remote Sens. 10(2018), 1–10 (2018). https://doi.org/10.3390/rs10050691
Matthews, B. W. (1975). Comparison of the predicted and observed secondary structure of T4 phage lysozyme. Biochim. Biophys. Acta (BBA) 405(2), 442–451. https://doi.org/10.1016/0005-2795(75)90109-9
Francini, S., McRoberts, R.E., Giannetti, F., Mencucci, M., Marchetti, M., Scarascia Mugnozza, G., Chirici, G.: Near-real time forest change detection using PlanetScope imagery. Eur. J. Remote Sens. 53(1), 233–244 (2020). https://doi.org/10.1080/22797254.2020.1806734
D’Amico, G., Francini, S., Giannetti, F., Vangi, E., Travaglini, D., Chianucci, F., Mattioli, W., Grotti, M., Puletti, N., Corona, P., Chirici, G.: A deep learning approach for automatic mapping of poplar plantations using Sentinel-2 imagery. GIScience Remote Sens. 58(8), 1352–1368 (2021). https://doi.org/10.1080/15481603.2021.1988427
Stone, C., Mohammed, C.: Application of remote sensing technologies for assessing planted forests damaged by insect pests and fungal pathogens: a review. Curr. For. Rep. 3(2), 75–92 (2017). https://doi.org/10.1007/s40725-017-0056-1
Zhang, J., Huang, Y., Pu, R., Gonzalez-Moreno, P., Yuan, L., Wu, K., Huang, W.: Monitoring plant diseases and pests through remote sensing technology: a review. Comput. Electron. Agric. 165, 104943 (2019). https://doi.org/10.1016/j.compag.2019.104943
Mazza, G., Manetti, M.C. Growth rate and climate responses of Pinus pinea L. in Italian coastal stands over the last century. Climatic Change 121, 713–725 (2013). https://doi.org/10.1007/s10584-013-0933-y
Acknowledgements
We wish to express our gratitude to the Presidency of the Italian Republic, to Dr. Giulia Bonella and Dr. Daniele Cecca, Direction of the Castelporziano Presidential Estate for the possibility to use needed data to carry out the research.
This study was partially supported by the following projects:
1. MULTIFOR “Multi-scale observations to predict Forest response to pollution and climate change” PRIN 2020 Research Project of National Relevance funded by the Italian Ministry of University and Research (prot. 2020E52THS);
2. SUPERB “Systemic solutions for upscaling of urgent ecosystem restoration for forest related biodiversity and ecosystem services” H2020 project funded by the European Commission, number 101036849 call LC-GD-7-1-2020;
3. EFINET “European Forest Information Network” funded by the European Forest Institute, Network Fund G-01-2021;
4. FORWARDS;
5. PNRR, funded by the Italian Ministry of University and Research, Missione 4 Componente 2, “Dalla ricerca all’impresa”, Investimento 1.4, Project CN00000033.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
D’Amico, G. et al. (2023). Multitemporal Optical Remote Sensing to Support Forest Health Condition Assessment of Mediterranean Pine Forests in Italy. In: Benítez-Andrades, J.A., García-Llamas, P., Taboada, Á., Estévez-Mauriz, L., Baelo, R. (eds) Global Challenges for a Sustainable Society . EURECA-PRO 2022. Springer Proceedings in Earth and Environmental Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-25840-4_15
Download citation
DOI: https://doi.org/10.1007/978-3-031-25840-4_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-25839-8
Online ISBN: 978-3-031-25840-4
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)