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Unmanned aerial system multispectral mapping for low and variable solar irradiance conditions: Potential of tensor decomposition / Sheng Wang in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 155 (September 2019) . - pp 58 - 71 Titre : Unmanned aerial system multispectral mapping for low and variable solar irradiance conditions: Potential of tensor decomposition Type de document : Article/Communication Auteurs : Sheng Wang, Auteur ; Andreas Baum, Auteur ; Pablo J. Zarco-Tejada, Auteur ; Carsten Dam-Hansen, Auteur ; Anders Thorseth, Auteur ; Peter Bauer-Gottwein, Auteur ; Filippo Bandini, Auteur ; Monica Garcia, Auteur Année de publication : 2019 Article en page(s) : pp 58 - 71 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] éclairement énergétique [Termes IGN] étalonnage de capteur (imagerie) [Termes IGN] image captée par drone [Termes IGN] image multibande [Termes IGN] nébulosité [Termes IGN] réflectance spectrale [Termes IGN] réflectance végétale [Termes IGN] tenseur Résumé : (Auteur) Unlike satellite earth observation, multispectral images acquired by Unmanned Aerial Systems (UAS) provide great opportunities to monitor land surface conditions also in cloudy or overcast weather conditions. This is especially relevant for high latitudes where overcast and cloudy days are common. However, multispectral imagery acquired by miniaturized UAS sensors under such conditions tend to present low brightness and dynamic ranges, and high noise levels. Additionally, cloud shadows over space (within one image) and time (across images) are frequent in UAS imagery collected under variable irradiance and result in sensor radiance changes unrelated to the biophysical dynamics at the surface. To exploit the potential of UAS for vegetation mapping, this study proposes methods to obtain robust and repeatable reflectance time series under variable and low irradiance conditions. To improve sensor sensitivity to low irradiance, a radiometric pixel-wise calibration was conducted with a six-channel multispectral camera (mini-MCA6, Tetracam) using an integrating sphere simulating the varying low illumination typical of outdoor conditions at 55oN latitude. The sensor sensitivity was increased by using individual settings for independent channels, obtaining higher signal-to-noise ratios compared to the uniform setting for all image channels. To remove cloud shadows, a multivariate statistical procedure, Tucker tensor decomposition, was applied to reconstruct images using a four-way factorization scheme that takes advantage of spatial, spectral and temporal information simultaneously. The comparison between reconstructed (with Tucker) and original images showed an improvement in cloud shadow removal. Outdoor vicarious reflectance validation showed that with these methods, the multispectral imagery can provide reliable reflectance at sunny conditions with root mean square deviations of around 3%. The proposed methods could be useful for operational multispectral mapping with UAS under low and variable irradiance weather conditions as those prevalent in northern latitudes. Numéro de notice : A2019-311 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2019.06.017 Date de publication en ligne : 04/07/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.06.017 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93336 [article]

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Understanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery / Pablo J. Zarco-Tejada in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 137 (March 2018) . - pp 134 - 148 Titre : Understanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery Type de document : Article/Communication Auteurs : Pablo J. Zarco-Tejada, Auteur ; A. Hornero, Auteur ; Rocío Hernández-Clemente, Auteur ; P.S.A. Beck, Auteur Année de publication : 2018 Article en page(s) : pp 134 - 148 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] bande rouge [Termes IGN] défoliation [Termes IGN] données spatiotemporelles [Termes IGN] image hyperspectrale [Termes IGN] image Sentinel-MSI [Termes IGN] modèle de transfert radiatif [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] Pinus (genre) [Termes IGN] santé des forêts [Termes IGN] teneur en chlorophylle des feuilles Résumé : (Auteur) The operational monitoring of forest decline requires the development of remote sensing methods that are sensitive to the spatiotemporal variations of pigment degradation and canopy defoliation. In this context, the red-edge spectral region (RESR) was proposed in the past due to its combined sensitivity to chlorophyll content and leaf area variation. In this study, the temporal dimension of the RESR was evaluated as a function of forest decline using a radiative transfer method with the PROSPECT and 3D FLIGHT models. These models were used to generate synthetic pine stands simulating decline and recovery processes over time and explore the temporal rate of change of the red-edge chlorophyll index (CI) as compared to the trajectories obtained for the structure-related Normalized Difference Vegetation Index (NDVI). The temporal trend method proposed here consisted of using synthetic spectra to calculate the theoretical boundaries of the subspace for healthy and declining pine trees in the temporal domain, defined by CItime=n/CItime=n+1 vs. NDVItime=n/NDVItime=n+1. Within these boundaries, trees undergoing decline and recovery processes showed different trajectories through this subspace. The method was then validated using three high-resolution airborne hyperspectral images acquired at 40 cm resolution and 260 spectral bands of 6.5 nm full-width half-maximum (FWHM) over a forest with widespread tree decline, along with field-based monitoring of chlorosis and defoliation (i.e., ‘decline’ status) in 663 trees between the years 2015 and 2016. The temporal rate of change of chlorophyll vs. structural indices, based on reflectance spectra extracted from the hyperspectral images, was different for trees undergoing decline, and aligned towards the decline baseline established using the radiative transfer models. By contrast, healthy trees over time aligned towards the theoretically obtained healthy baseline. The applicability of this temporal trend method to the red-edge bands of the MultiSpectral Imager (MSI) instrument on board Sentinel-2a for operational forest status monitoring was also explored by comparing the temporal rate of change of the Sentinel-2-derived CI over areas with declining and healthy trees. Results demonstrated that the Sentinel-2a red-edge region was sensitive to the temporal dimension of forest condition, as the relationships obtained for pixels in healthy condition deviated from those of pixels undergoing decline. Numéro de notice : A2018-079 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.017 Date de publication en ligne : 17/02/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89441 [article]

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Deriving Predictive relationships of carotenoid content at the canopy level in a conifer forest using hyperspectral imagery and model simulation / Rocío Hernández-Clemente in IEEE Transactions on geoscience and remote sensing, vol 52 n° 8 Tome 2 (August 2014)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 52 n° 8 Tome 2 (August 2014) . - pp 5206 - 5217 Titre : Deriving Predictive relationships of carotenoid content at the canopy level in a conifer forest using hyperspectral imagery and model simulation Type de document : Article/Communication Auteurs : Rocío Hernández-Clemente, Auteur ; R.M. Navarro Cerrillo, Auteur ; Pablo J. Zarco-Tejada, Auteur Année de publication : 2014 Article en page(s) : pp 5206 - 5217 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] canopée [Termes IGN] chlorophylle [Termes IGN] image hyperspectrale [Termes IGN] indice de végétation [Termes IGN] modélisation [Termes IGN] photosynthèse [Termes IGN] Pinophyta [Termes IGN] réflectance végétale [Termes IGN] surveillance forestière Résumé : (Auteur) Recent studies have demonstrated that the R570/R515 index is highly sensitive to carotenoid (Cx + c) content in conifer forest canopies and is scarcely influenced by structural effects. However, validated methods for the prediction of leaf carotenoid content relationships in forest canopies are still needed to date. This paper focuses on the simultaneous retrieval of chlorophyll (Cα + b) and (Cx + c) pigments, which are critical bioindicators of plant physiological status. Radiative transfer theory and modeling assumptions were applied at both laboratory and field scales to develop methods for their concurrent estimation using high-resolution hyperspectral imagery. The proposed methodology was validated based on the biochemical pigment quantification. Canopy modeling methods based on infinite reflectance formulations and the discrete anisotropic radiative transfer (DART) model were evaluated in relation to the PROSPECT-5 leaf model for the scaling-up procedure. Simpler modeling methods yielded comparable results to more complex 3-D approximations due to the high spatial resolution images acquired, which enabled targeting pure crowns and reducing the effects of canopy architecture. The scaling-up methods based on the PROSPECT-5+DART model yielded a root-mean-square error (RMSE) and a relative RMSE of 1.48 μg/cm2 (17.45%) and 5.03 μg/cm2 (13.25%) for Cx + c and Cα + b, respectively, while the simpler approach based on the PROSPECT-5+Hapke infinite reflectance model yielded 1.37 μg/cm2 (17.46%) and 4.71 μg/cm2 (14.07%) for Cx + c and Cα+b, respectively. These predictive algorithms proved to be useful to estimate Cα + b and Cx + c from high-resolution hyperspectral imagery, providing a methodology for the monitoring of these photosynthetic pigments in conifer forest canopies. Numéro de notice : A2014-433 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2287304 En ligne : https://doi.org/10.1109/TGRS.2013.2287304 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73970 [article]

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Optical indices as bioindicators of forest condition from hyperspectral CASI data / Pablo J. Zarco-Tejada (31/05/1999)

Public contenu dans Remote sensing in the 21st century : economic and environmental applications / José Luis Casanova (2000) Titre : Optical indices as bioindicators of forest condition from hyperspectral CASI data Type de document : Article/Communication Auteurs : Pablo J. Zarco-Tejada, Auteur ; J.R. Miller, Auteur ; G.H. Mohammed, Auteur ; T.L. Noland, Auteur ; P.H. Sampson, Auteur Editeur : Lisse : Balkema (A.A.) Année de publication : 31/05/1999 Conférence : EARSeL 1999, 19th symposium, Remote sensing in the 21st century : economic and environmental applications 31/05/1999 02/06/1999 Valladolid Espagne Importance : pp 517 - 522 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Acer (genre) [Termes IGN] Compact airborne spectrographic imager [Termes IGN] forêt [Termes IGN] image CASI [Termes IGN] image hyperspectrale [Termes IGN] réflectance végétale [Termes IGN] télédétection aérienne Résumé : (Auteur) This paper reports on progress made to link physiologically-based indicators to optical indices scaling-up from leaf level to the canopy through SAIL and Kuusk Canopy Reflectance Models (CR). Hyperspectral CASI data of 2m spatial resolution and 72 channels were collected in 1997 and 1998 deployments over twelve sites of Acer saccharum M. in Ontario (Canada). A field sampling campaign was carried out for biochemical analysis of leaf chlorophyll and carotenoid concentrations, and fluorescence along with leaf reflectance and transmittance. Leaf-level relationships obtained between optical indices and biochemical indicators were scaled-up to canopy level through CR models using input model parameters related to the canopy structure and viewing geometry at the time of data acquisition. The result is an algorithm which predicts leaf-level bioindicators from airborne hyperspectral imagery. A modeling study was carried out to determine the influence of CR on the four types of optical indices used in this study. Numéro de notice : C1999-049 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Communication Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=65815