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Improved parametrisation of a physically-based forest reflectance model for retrieval of boreal forest structural properties / Eelis Halme in Silva fennica, vol 57 n° 2 (April 2023)  

Public [article]  inSilva fennica > vol 57 n° 2 (April 2023) . - n° 22028 Titre : Improved parametrisation of a physically-based forest reflectance model for retrieval of boreal forest structural properties Type de document : Article/Communication Auteurs : Eelis Halme, Auteur ; Matti Mõttus, Auteur Année de publication : 2023 Article en page(s) : n° 22028 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Betula pendula [Termes IGN] betula pubescens [Termes IGN] densité du peuplement [Termes IGN] diagnostic foliaire [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] image Sentinel-MSI [Termes IGN] modèle de croissance végétale [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] réflectance végétale [Termes IGN] structure d'un peuplement forestier Résumé : (auteur) Physically-based reflectance models offer a robust and transferable method to assess biophysical characteristics of vegetation in remote sensing. Forests exhibit explicit structure at many scales, from shoots and branches to landscape patches, and hence present a specific challenge to vegetation reflectance modellers. To relate forest reflectance with its structure, the complexity must be parametrised leading to an increase in the number of reflectance model inputs. The parametrisations link reflectance simulations to measurable forest variables, but at the same time rely on abstractions (e.g. a geometric surface forming a tree crown) and physically-based simplifications that are difficult to quantify robustly. As high-quality data on basic forest structure (e.g. tree height and stand density) and optical properties (e.g. leaf and forest floor reflectance) are becoming increasingly available, we used the well-validated forest reflectance and transmittance model FRT to investigate the effect of the values of the “uncertain” input parameters on the accuracy of modelled forest reflectance. With the state-of-the-art structural and spectral forest information, and Sentinel-2 Multispectral Instrument imagery, we identified that the input parameters influencing the most the modelled reflectance, given that the basic forestry variables are set to their true values and leaf mass is determined from reliable allometric models, are the regularity of the tree distribution and the amount of woody elements. When these parameters were set to their new adjusted values, the model performance improved considerably, reaching in the near infrared spectral region (740–950 nm) nearly zero bias, a relative RMSE of 13% and a correlation coefficient of 0.81. In the visible part of the spectrum, the model performance was not as consistent indicating room for improvement. Numéro de notice : A2023-228 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14214/sf.22028 Date de publication en ligne : 30/05/2023 En ligne : https://doi.org/10.14214/sf.22028 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103260 [article]

Multi-sensor airborne lidar requires intercalibration for consistent estimation of light attenuation and plant area density / Grégoire Vincent in Remote sensing of environment, vol 286 (March 2023)  

Public [article]  inRemote sensing of environment > vol 286 (March 2023) . - n° 113442 Titre : Multi-sensor airborne lidar requires intercalibration for consistent estimation of light attenuation and plant area density Type de document : Article/Communication Auteurs : Grégoire Vincent, Auteur ; Philippe Verley, Auteur ; Benjamin Brede, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 113442 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] canopée [Termes IGN] densité de la végétation [Termes IGN] données lidar [Termes IGN] forêt tropicale [Termes IGN] Guyane (département français) [Termes IGN] image captée par drone [Termes IGN] plan de vol [Termes IGN] rayonnement lumineux [Termes IGN] réflectance végétale [Termes IGN] semis de points [Termes IGN] zone d'intérêt Résumé : (auteur) Leaf area is a key structural characteristic of forest canopies because of the role of leaves in controlling many biological and physical processes occurring at the biosphere-atmosphere transition. High pulse density Airborne Laser Scanning (ALS) holds promise to provide spatially resolved and accurate estimates of plant area density (PAD) in forested landscapes, a key step in understanding forest functioning: phenology, carbon uptake, transpiration, radiative balance etc. Inconsistencies between different ALS sensors is a barrier to generating globally harmonised PAD estimates. The basic assumption on which PAD estimation is based is that light attenuation is proportional to vegetation area density. This study shows that the recorded extinction strongly depends on target detectability which is influenced by laser characteristics (power, sensitivity, wavelength). Three different airborne laser scanners were flown over a wet tropical forest at the Paracou research station in French Guiana. Different sensors, flight heights and transmitted power levels were compared. Light attenuation was retrieved with an open source ray-tracing code (http://amapvox.org). Direct comparison revealed marked differences (up-to 25% difference in profile-averaged light attenuation rate and 50% difference at particular heights) that could only be explained by differences in scanner characteristics. We show how bias which may occur under various acquisition conditions can generally be mitigated by a sensor intercalibration. Alignment of light weight lidar attenuation profiles to ALS reference attenuation profiles is not always satisfactory and we discuss what are the likely sources of discrepancies. Neglecting the dependency of apparent light attenuation on scanner properties may lead to biases in estimated vegetation density commensurate to those affecting light attenuation estimates. Applying intercalibration procedures supports estimation of plant area density independent of acquisition characteristics. Numéro de notice : A2023-169 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113442 Date de publication en ligne : 06/01/2023 En ligne : https://doi.org/10.1016/j.rse.2022.113442 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102928 [article]

A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band / Xinjie Liu in Remote sensing of environment, vol 284 (January 2023)  

Public [article]  inRemote sensing of environment > vol 284 (January 2023) . - n° 113341 Titre : A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band Type de document : Article/Communication Auteurs : Xinjie Liu, Auteur ; Liangyun Liu, Auteur ; Cédric Bacour, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 113341 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] canopée [Termes IGN] chlorophylle [Termes IGN] fluorescence [Termes IGN] image Sentinel-5P-TROPOMI [Termes IGN] image Terra-MODIS [Termes IGN] production primaire brute [Termes IGN] rayonnement proche infrarouge [Termes IGN] réflectance de surface [Termes IGN] réflectance végétale Résumé : (auteur) Satellite-based data of solar-induced chlorophyll fluorescence (SIF) and the near-infrared radiation reflected by vegetation (NIRvP) are being increasingly used for the estimation of vegetation gross primary product (GPP) at the global scale. Although SIF contains more physiological information than NIRvP, NIRvP can have higher data quality and spatio-temporal resolution. Therefore, the two variables can be considered complementary for GPP monitoring. Here, we propose a simple framework to combine SIF and NIRvP data from different data sources to generate an enhanced SIF product (eSIF). The original SIF data comes from the TROPOMI instrument onboard the Sentinel-5P mission, whereas NIRvP data are derived from MODIS spectral reflectance and ERA5 reanalysis data. The resulting eSIF product has a spatial resolution of 0.05° and a temporal resolution of 8 days, as well as a higher signal-to-noise ratio and a lower angular dependency than the original TROPOMI SIF data. Our results demonstrate that eSIF has similar spatial patterns to the original SIF but is more spatially continuous and less noisy. Comparisons with the FLUXCOM global GPP product show that eSIF has a more universal relationship with GPP than NIRvP for different grass/crop plant functional types (the coefficients of variation are 18.9% for slopes of GPP to eSIF and 27.3% for slopes of GPP to NIRvP), but NIRvP outperforms eSIF for tracking GPP for forest PFTs exclude BoENF. Moreover, eSIF is able to better track the seasonal variations in GPP related to environmental stresses. This study highlights that our methodology based on the combination of SIF and NIRvP is a promising approach for better monitoring of GPP. Numéro de notice : A2023-017 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113341 Date de publication en ligne : 07/11/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113341 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102151 [article]

An advanced bidirectional reflectance factor (BRF) spectral approach for estimating flavonoid content in leaves of Ginkgo plantations / Kai Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 193 (November 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 193 (November 2022) . - pp 1 - 16 Titre : An advanced bidirectional reflectance factor (BRF) spectral approach for estimating flavonoid content in leaves of Ginkgo plantations Type de document : Article/Communication Auteurs : Kai Zhou, Auteur ; Lin Cao, Auteur ; Shiyun Yin, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1 - 16 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] bande spectrale [Termes IGN] coefficient de corrélation [Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF [Termes IGN] feuille (végétation) [Termes IGN] Ginkgo biloba [Termes IGN] image à haute résolution [Termes IGN] indice foliaire [Termes IGN] Kiangsou (Chine) [Termes IGN] réflectance végétale Résumé : (auteur) As a key phenolic pigment concentrated in the surface tissues of leaves, flavonoids (Flav) are the major bioactive ingredients in Ginkgo leaf extracts. Flav are also marked natural antioxidants and significant indicators of biotic and abiotic stresses, critical for determining cultivation quality and enhancing Flav yield. In particular, area-based Flav (Flavarea) is related to the shortwave-blue light interaction within leaves per unit leaf area, whereas mass-based Flav (Flavmass) is useful for the quantitative assessment of Flav yield. In order to accurately estimate the contents of Flavarea and Flavmass in leaves of Ginkgo plantations, in this study, we developed an advanced bidirectional reflectance factor (BRF) spectra-based approach by reducing the effects of specular reflection and enhancing the absorption signals of Flav (in the shortwave-blue region of spectrum), using a suite of new spectral indices (SIs) (i.e., flavonoid index (FI), modified flavonoid index (mFI) and double difference index (DD)) calculated from the leaf clip equipped spectrometers-collected data. The results demonstrated that most of the SIs derived from the developed BRF spectra-based approach obtained relatively high performance for Flav estimation by alleviating adverse effects of specular reflection to different extents (CV-R2 = 0.60–0.76). In specific, DDnir434,421 selected from DD-type indices performed (CV-R2 = 0.76 for Flavarea; CV-R2 = 0.69 for Flavmass) better than other indices. These findings represent marked potentials of the developed BRF spectra-based approach for non-destructively estimating leaf Flav content, as well as improving the understanding of the mechanisms of specular effects on Flav estimations in leaves of Ginkgo plantations. Numéro de notice : A2022-744 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.08.020 Date de publication en ligne : 09/09/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.08.020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101727 [article]

Attributs de texture extraits d'images multispectrales acquises en conditions d'éclairage non contrôlées : application à l'agriculture de précision / Anis Amziane (2022)  

Public Titre : Attributs de texture extraits d'images multispectrales acquises en conditions d'éclairage non contrôlées : application à l'agriculture de précision Type de document : Thèse/HDR Auteurs : Anis Amziane, Auteur ; Ludovic Macaire, Directeur de thèse Editeur : Lille : Université de Lille Année de publication : 2022 Importance : 214 p. Format : 21 x 30 cm Note générale : Bibliographie Thèse pour obtenir le grade de Docteur de l'Université de Lille, spécialité Automatique, Génie Informatique, Traitement du Signal et des Images Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] agriculture de précision [Termes IGN] bande spectrale [Termes IGN] classification dirigée [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection automatique [Termes IGN] éclairage [Termes IGN] exitance spectrale [Termes IGN] extraction de la végétation [Termes IGN] rayonnement proche infrarouge [Termes IGN] reconnaissance d'objets [Termes IGN] réflectance végétale [Termes IGN] signature spectrale Index. décimale : THESE Thèses et HDR Résumé : (auteur) The main objective of this work is to develop an automatic recognition system of crop and weed plants in field conditions. In Chapter 2 we describe the formation of multispectral radiance images under the Lambertian surface assumption and the different devices that can be used to acquire such images. We then provide a detailed description of the multispectral camera used in this study. Because radiance multispectral images are acquired under varying illumination, we propose an original multispectral image formation model that takes the variation of illumination conditions into account. In chapter 3, we estimate the reflectance as an illumination-invariant spectral signature. First, we present state-of-the-art methods that can be used to estimate the reflectance from multispectral images. We then introduce the reference state-of-the-art method for reflectance estimation and de- scribe our proposed method for reflectance estimation under varying illumination. Chapter 4 focuses on estimated reflectance assessment. The quality of reflectance estimated by our method is evaluated against state-of-the-art methods, and its contribution to supervised crop/weed recognition is demonstrated. Chapter 5 addresses the dimension reduction issue. The acquired multispectral images are composed of a high number of spectral channels, whose analysis is memory and time consuming. Moreover, spectral bands associated to these channels may be redundant or contain highly correlated spectral information. Therefore, we select the best spectral bands for crop/weed classification and use them to specify a camera suited for crop/weed recognition.Chapter 6 deals with the problem of spatio-spectral feature extraction from multispectral images. We propose an approach that extracts both spatial and spectral information at reduced computation costs based on a CNN. Its contribution to crop/weed recognition is demonstrated. Note de contenu : 1- Introduction 2- Multispectral imaging 3- Reflectance estimation 4- Reflectance estimation assessment 5- dimension reduction 6- Raw textures features for crop/weed recognition Conclusion Numéro de notice : 24102 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Organisme de stage : Laboratoire Cristal (Lille) DOI : sans En ligne : https://www.theses.fr/2022ULILB020 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102577

Uncertainties in measurements of leaf optical properties are small compared to the biological variation within and between individuals of European beech / Fanny Petibon in Remote sensing of environment, vol 264 (October 2021)  

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Evaluating the performance of hyperspectral leaf reflectance to detect water stress and estimation of photosynthetic capacities / Jingjing Zhou in Remote sensing, vol 13 n° 11 (June-1 2021)  

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Fractional vegetation cover estimation algorithm for FY-3B reflectance data based on random forest regression method / Duanyang Liu in Remote sensing, vol 13 n° 11 (June-1 2021)  

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Apport de la modélisation physique pour la cartographie de la biodiversité végétale en forêts tropicales par télédétection optique / Dav Ebengo Mwampongo (2021)  

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Polarization of light reflected by grass: modeling using visible-sunlit areas / Bin Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 12 (December 2020)  

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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)  

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Individual tree crown segmentation in tropical peat swamp forest using airborne hyperspectral data / Sitinor Atikah Nordin in Geocarto international, vol 34 n° 11 ([15/08/2019])  

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Mapping leaf chlorophyll content from Sentinel-2 and RapidEye data in spruce stands using the invertible forest reflectance model / Roshanak Darvishzadeh in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)  

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Evaluating metrics derived from Landsat 8 OLI imagery to map crop cover / Rei Sonobe in Geocarto international, vol 34 n° 8 ([15/06/2019])  

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ICARE-VEG: A 3D physics-based atmospheric correction method for tree shadows in urban areas / Karine R.M. Adeline in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)  

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