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Phenological Dynamics Characterization of Alignment Trees with Sentinel-2 Imagery: A Vegetation Indices Time Series Reconstruction Methodology Adapted to Urban Areas

1
ONERA-Department of Theoretical and Applied Optics, University of Toulouse, FR-31055 Toulouse, France
2
Centre National de Recherches Météorologiques, Meteo-France-CNRS, FR-31057 Toulouse, France
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(4), 639; https://doi.org/10.3390/rs12040639
Received: 18 December 2019 / Revised: 10 February 2020 / Accepted: 11 February 2020 / Published: 14 February 2020
(This article belongs to the Section Urban Remote Sensing)
This article presents a novel methodology for the characterization of tree vegetation phenology, based on vegetation indices time series reconstruction and adapted to urban areas. The methodology is based on a pixel by pixel curve fitting classification, together with a subsequent Savitzky–Golay filtering of raw phenological curves from pixels classified as vegetation. Moreover, the new method is conceived to face specificities of urban environments such as: the high heterogeneity of impervious/natural elements, the 3D structure of the city inducing shadows, the restricted spatial extent of individual tree crowns and the strong biodiversity of urban vegetation. Three vegetation indices have been studied: Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index 1 (NDRE1), which are mainly linked to chlorophyll content and leaf density and Normalized Burn Ratio (NBR) mostly correlated to water content and leaf density. The methodology has been designed to allow the analysis of annual and intra-annual vegetation phenological dynamics. Then, different annual and intra-annual criteria for phenology characterization are proposed and criticized. To show the applicability of the methodology, this article focuses on Sentinel-2 (S-2) imagery covering 2018 and the study of groups of London planes in an alignment structure in the French city of Toulouse. Results showed that the new method allows the ability to 1) describe the heterogeneity of phenologies from London planes exposed to different environmental conditions (urban canyons, proximity with a source of water) and 2) to detect intra-annual phenological dynamics linked to changes in meteorological conditions. View Full-Text
Keywords: urban tree vegetation; phenology; time series reconstruction; Sentinel-2; NDVI; NBR; NDRE1 urban tree vegetation; phenology; time series reconstruction; Sentinel-2; NDVI; NBR; NDRE1
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MDPI and ACS Style

Granero-Belinchon, C.; Adeline, K.; Lemonsu, A.; Briottet, X. Phenological Dynamics Characterization of Alignment Trees with Sentinel-2 Imagery: A Vegetation Indices Time Series Reconstruction Methodology Adapted to Urban Areas. Remote Sens. 2020, 12, 639.

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