气候变化领域集成服务门户(CCPortal): Remotely-sensed phenology of Italian forests: Going beyond the species

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DOI	10.1016/j.jag.2018.10.003
	Remotely-sensed phenology of Italian forests: Going beyond the species
	Bajocco S.; Ferrara C.; Alivernini A.; Bascietto M.; Ricotta C.
发表日期	2019
ISSN	15698432
起始页码	314
结束页码	321
卷号	74
英文摘要	Remotely sensed observations of seasonal greenness dynamics represent a valuable tool for studying vegetation phenology at regional and ecosystem-level scales. We investigated the seasonal variability of forests in Italy, examining the different mechanisms of phenological response to biophysical drivers. For each point of the Italian National Forests Inventory, we processed a multitemporal profile of the MODIS Enhanced Vegetation Index. Then we applied a multivariate approach for the purpose of (i) classifying the Italian forests into phenological clusters (i.e. pheno-clusters), (ii) identifying the main phenological characteristics and the forest compositions of each pheno-cluster and (iii) exploring the role of climate and physiographic variables in the phenological timing of each cluster. Results identified four pheno-clusters, following a clear elevation gradient and a distinct separation along the Mediterranean-to-temperate climatic transition of Italy. The “High-elevation coniferous” and the “High elevation deciduous” resulted mainly affected by elevation, with the former characterized by low annual productivity and the latter by high seasonality. To the contrary, the “Low elevation deciduous” showed to be mostly associated to moderate climate conditions and a prolonged growing season. Finally, summer drought was the main driving variable for the “Mediterranean evergreen”, characterized by low seasonality. The discrimination of vegetation phenology types can provide valuable information useful as a baseline framework for further studies on forests ecosystem and for management strategies. © 2018 Elsevier B.V.
英文关键词	Discriminant analysis; MODIS EVI; Pheno-clusters; Time-series; Vegetation phenology
语种	英语
scopus关键词	discriminant analysis; forest inventory; Mediterranean environment; MODIS; phenology; remote sensing; seasonal variation; time series; vegetation index; Italy
来源期刊	International Journal of Applied Earth Observation and Geoinformation
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156566
作者单位	Council for Agricultural Research and Economics, Research Centre for Agriculture and Environment (CREA-AA), Rome, Italy; Council for Agricultural Research and Economics, Research Centre for Forestry and Wood (CREA-FL), Arezzo, Italy; Council for Agricultural Research and Economics, Research Centre for Engineering and Agro-Food Processing (CREA-IT), Monterotondo, Italy; Department of Environmental Biology, University of Rome “La Sapienza”, Rome, Italy
推荐引用方式 GB/T 7714	Bajocco S.,Ferrara C.,Alivernini A.,et al. Remotely-sensed phenology of Italian forests: Going beyond the species[J],2019,74.
APA	Bajocco S.,Ferrara C.,Alivernini A.,Bascietto M.,&Ricotta C..(2019).Remotely-sensed phenology of Italian forests: Going beyond the species.International Journal of Applied Earth Observation and Geoinformation,74.
MLA	Bajocco S.,et al."Remotely-sensed phenology of Italian forests: Going beyond the species".International Journal of Applied Earth Observation and Geoinformation 74(2019).