remote sensing Article Mapping Mediterranean Forest Plant Associations and Habitats with Functional Principal Component Analysis Using Landsat 8 NDVI Time Series Simone Pesaresi 1 , Adriano Mancini 2 , Giacomo Quattrini 1 and Simona Casavecchia 1,* 1 Department of Agricultural, Food, and Environmental Sciences, D3A, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy;
[email protected] (S.P.);
[email protected] (G.Q.) 2 Department of Information Engineering, DII, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy;
[email protected] * Correspondence:
[email protected]; Tel.: +39-0712204350 Received: 28 February 2020; Accepted: 31 March 2020; Published: 2 April 2020 Abstract: The classification of plant associations and their mapping play a key role in defining habitat biodiversity management, monitoring, and conservation strategies. In this work we present a methodological framework to map Mediterranean forest plant associations and habitats that relies on the application of the Functional Principal Component Analysis (FPCA) to the remotely sensed Normalized Difference Vegetation Index (NDVI) time series. FPCA, considering the chronological order of the data, reduced the NDVI time series data complexity and provided (as FPCA scores) the main seasonal NDVI phenological variations of the forests. We performed a supervised classification of the FPCA scores combined with topographic and lithological features of the study area to map the forest plant associations. The