Sensitivity Analysis of Sentinel-2 Imagery to Assess Urban Tree Functional Traits: A Physical Approach Based on Local Climate Zones

Urban trees contribute to urban well-being but face challenging environments that can reduce their lifespan and increase young tree mortality. Although many studies have used remote sensing data to monitor the functional status of trees in rural areas, few have done so in urban areas to assess the h...

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Main Authors: Théo Le Saint, Jean Nabucet, Sidonie Lefebvre, Jean-Philippe Gastellu-Etchegorry, Laurence Hubert-Moy, Karine Adeline
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Remote Sensing
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Online Access:https://www.mdpi.com/2072-4292/16/23/4402
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author Théo Le Saint
Jean Nabucet
Sidonie Lefebvre
Jean-Philippe Gastellu-Etchegorry
Laurence Hubert-Moy
Karine Adeline
author_facet Théo Le Saint
Jean Nabucet
Sidonie Lefebvre
Jean-Philippe Gastellu-Etchegorry
Laurence Hubert-Moy
Karine Adeline
author_sort Théo Le Saint
collection DOAJ
description Urban trees contribute to urban well-being but face challenging environments that can reduce their lifespan and increase young tree mortality. Although many studies have used remote sensing data to monitor the functional status of trees in rural areas, few have done so in urban areas to assess the health or estimate the biomass of large green areas. This study assessed the suitability of using Sentinel-2 images to characterize two urban tree functional traits—leaf chlorophyll content (Cab) and leaf area density (LAD)—in isolated trees and tree rows. Simulated Sentinel-2 images were generated using the DART radiative transfer model, considering 16 tree-endogenous and 14 tree-exogenous parameters, with 15 vegetation indices (VIs) analyzed. Sensitivity analysis was performed in four contrasting urban environments using local climate zone taxonomy. The accuracy of the simulated images was validated with real Sentinel-2 images, field measurements, and ancillary data collected for four tree species in Rennes, France. The results showed that the tree parameters significantly influenced Sentinel-2 spectral bands, with NGBDI and OSAVI VIs being most sensitive to Cab and LAD. The model showed high accuracy, with a mean RMSE of 0.016 for key spectral bands. The results also highlighted the importance of considering ancillary data to capture specific urban characteristics.
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spelling doaj-art-6d756e3c07474b3f94cf6a2b0736675a2024-12-13T16:30:43ZengMDPI AGRemote Sensing2072-42922024-11-011623440210.3390/rs16234402Sensitivity Analysis of Sentinel-2 Imagery to Assess Urban Tree Functional Traits: A Physical Approach Based on Local Climate ZonesThéo Le Saint0Jean Nabucet1Sidonie Lefebvre2Jean-Philippe Gastellu-Etchegorry3Laurence Hubert-Moy4Karine Adeline5UMR 6554 CNRS, LETG, University of Rennes, Place du Recteur Henri Le Moal, 35000 Rennes, FranceUMR 6554 CNRS, LETG, University of Rennes, Place du Recteur Henri Le Moal, 35000 Rennes, FranceDOTA, ONERA, Université Paris Saclay, 31055 Palaiseau, FranceCentre d’Etudes Spatiales de la BIOsphère—UPS, CNES, CNRS, IRD, University of Toulouse, 31055 Toulouse, FranceUMR 6554 CNRS, LETG, University of Rennes, Place du Recteur Henri Le Moal, 35000 Rennes, FranceDOTA, ONERA, Université de Toulouse, 31055 Toulouse, FranceUrban trees contribute to urban well-being but face challenging environments that can reduce their lifespan and increase young tree mortality. Although many studies have used remote sensing data to monitor the functional status of trees in rural areas, few have done so in urban areas to assess the health or estimate the biomass of large green areas. This study assessed the suitability of using Sentinel-2 images to characterize two urban tree functional traits—leaf chlorophyll content (Cab) and leaf area density (LAD)—in isolated trees and tree rows. Simulated Sentinel-2 images were generated using the DART radiative transfer model, considering 16 tree-endogenous and 14 tree-exogenous parameters, with 15 vegetation indices (VIs) analyzed. Sensitivity analysis was performed in four contrasting urban environments using local climate zone taxonomy. The accuracy of the simulated images was validated with real Sentinel-2 images, field measurements, and ancillary data collected for four tree species in Rennes, France. The results showed that the tree parameters significantly influenced Sentinel-2 spectral bands, with NGBDI and OSAVI VIs being most sensitive to Cab and LAD. The model showed high accuracy, with a mean RMSE of 0.016 for key spectral bands. The results also highlighted the importance of considering ancillary data to capture specific urban characteristics.https://www.mdpi.com/2072-4292/16/23/4402remote sensingradiative transfer modellingDARTvegetation indices3D modelling
spellingShingle Théo Le Saint
Jean Nabucet
Sidonie Lefebvre
Jean-Philippe Gastellu-Etchegorry
Laurence Hubert-Moy
Karine Adeline
Sensitivity Analysis of Sentinel-2 Imagery to Assess Urban Tree Functional Traits: A Physical Approach Based on Local Climate Zones
Remote Sensing
remote sensing
radiative transfer modelling
DART
vegetation indices
3D modelling
title Sensitivity Analysis of Sentinel-2 Imagery to Assess Urban Tree Functional Traits: A Physical Approach Based on Local Climate Zones
title_full Sensitivity Analysis of Sentinel-2 Imagery to Assess Urban Tree Functional Traits: A Physical Approach Based on Local Climate Zones
title_fullStr Sensitivity Analysis of Sentinel-2 Imagery to Assess Urban Tree Functional Traits: A Physical Approach Based on Local Climate Zones
title_full_unstemmed Sensitivity Analysis of Sentinel-2 Imagery to Assess Urban Tree Functional Traits: A Physical Approach Based on Local Climate Zones
title_short Sensitivity Analysis of Sentinel-2 Imagery to Assess Urban Tree Functional Traits: A Physical Approach Based on Local Climate Zones
title_sort sensitivity analysis of sentinel 2 imagery to assess urban tree functional traits a physical approach based on local climate zones
topic remote sensing
radiative transfer modelling
DART
vegetation indices
3D modelling
url https://www.mdpi.com/2072-4292/16/23/4402
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