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Evaluating leaf chlorophyll content prediction from multispectral remote sensing data within a physically-based modelling framework / H. Croft in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)
[article]
Titre : Evaluating leaf chlorophyll content prediction from multispectral remote sensing data within a physically-based modelling framework Type de document : Article/Communication Auteurs : H. Croft, Auteur ; Jing M. Chen, Auteur ; Y. Zhang, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 85 - 95 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Acer saccharum
[Termes IGN] aiguille
[Termes IGN] image Landsat-TM
[Termes IGN] indice de stress
[Termes IGN] Leaf Area Index
[Termes IGN] modèle de transfert radiatif
[Termes IGN] Picea mariana
[Termes IGN] Pinus banksiana
[Termes IGN] Populus tremuloides
[Termes IGN] réflectance végétale
[Termes IGN] surveillance forestière
[Termes IGN] teneur en chlorophylle des feuillesRésumé : (auteur) Accurate modelling of leaf chlorophyll content over a range of spatial and temporal scales is central to monitoring vegetation stress and physiological condition, and vegetation response to different ecological, climatic and anthropogenic drivers. A process-based modelling approach can account for variation in other factors affecting canopy reflectance, providing a more accurate estimate of chlorophyll content across different vegetation species, time-frames, and broader spatial extents. However, physically-based modelling studies usually use hyperspectral data, neglecting a wealth of data from broadband and multispectral sources. In this study, we assessed the potential for using canopy (4-Scale) and leaf radiative transfer (PROSPECT4/5) models to estimate leaf chlorophyll content using canopy Landsat satellite data and simulated Landsat bands from leaf level hyperspectral reflectance data. Over 600 leaf samples were used to test the performance of PROSPECT for different vegetation species, including black spruce (Picea mariana), sugar maple (Acer saccharum), trembling aspen (Populus tremuloides) and jack pine (Pinus banksiana). At the leaf level, hyperspectral and simulated Landsat bands showed very similar results to laboratory measured chlorophyll (R2 = 0.77 and R2 = 0.75, respectively). Comparisons between PROSPECT4 modelled chlorophyll from simulated Landsat and hyperspectral spectra showed a very close correspondence (R2 = 0.97, root mean square error (RMSE) = 3.01 μg/cm2), as did simulated reflectance bands from other broadband and narrowband sensors (MODIS: R2 = 0.99, RMSE = 1.80 μg/cm2; MERIS: R2 = 0.97, RMSE = 2.50 μg/cm2 and SPOT5 HRG: R2 = 0.96, RMSE = 5.38 μg/cm2). Modelled leaf chlorophyll content from Landsat 5 TM canopy reflectance data, acquired from over 40 ground validation sites, demonstrated a strong relationship with measured leaf chlorophyll content (R2 = 0.78, RMSE = 8.73 μg/cm2, p Numéro de notice : A2015-691 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.01.008 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.01.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78326
in ISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 85 - 95[article]Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)
[article]
Titre : Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery Type de document : Article/Communication Auteurs : Gang Chen, Auteur ; Margaret R. Metz, Auteur ; David M. Rizzo, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 38 - 47 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse en composantes principales
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] délimitation
[Termes IGN] houppier
[Termes IGN] image à ultra haute résolution
[Termes IGN] image aérienne
[Termes IGN] image MASTER
[Termes IGN] impact sur l'environnement
[Termes IGN] incendie de forêt
[Termes IGN] maladie phytosanitaire
[Termes IGN] réflectance végétaleRésumé : (auteur) Forest ecosystems are subject to a variety of disturbances with increasing intensities and frequencies, which may permanently change the trajectories of forest recovery and disrupt the ecosystem services provided by trees. Fire and invasive species, especially exotic disease-causing pathogens and insects, are examples of disturbances that together could pose major threats to forest health. This study examines the impacts of fire and exotic disease (sudden oak death) on forests, with an emphasis on the assessment of post-fire burn severity in a forest where trees have experienced three stages of disease progression pre-fire: early-stage (trees retaining dried foliage and fine twigs), middle-stage (trees losing fine crown fuels), and late-stage (trees falling down). The research was conducted by applying Geographic Object-Based Image Analysis (GEOBIA) to MASTER airborne images that were acquired immediately following the fire for rapid assessment and contained both high-spatial (4 m) and high-spectral (50 bands) resolutions. Although GEOBIA has gradually become a standard tool for analyzing high-spatial resolution imagery, high-spectral resolution data (dozens to hundreds of bands) can dramatically reduce computation efficiency in the process of segmentation and object-based variable extraction, leading to complicated variable selection for succeeding modeling. Hence, we also assessed two widely used band reduction algorithms, PCA (principal component analysis) and MNF (minimum noise fraction), for the delineation of image objects and the subsequent performance of burn severity models using either PCA or MNF derived variables. To increase computation efficiency, only the top 5 PCA and MNF and top 10 PCA and MNF components were evaluated, which accounted for 10% and 20% of the total number of the original 50 spectral bands, respectively. Results show that if no band reduction was applied the models developed for the three stages of disease progression had relatively similar performance, where both spectral responses and texture contributed to burn assessments. However, the application of PCA and MNF introduced much greater variation among models across the three stages. For the early-stage disease progression, neither band reduction algorithms improved or retained the accuracy of burn severity modeling (except for the use of 10 MNF components). Compared to the no-band-reduction scenario, band reduction led to a greater level of overestimation of low-degree burns and underestimation of medium-degree burns, suggesting that the spectral variation removed by PCA and MNF was vital for distinguishing between the spectral reflectance from disease-induced dried crowns (still retaining high structural complexity) and fire ash. For the middle-stage, both algorithms improved the model R2 values by 2–37%, while the late-stage models had comparable or better performance to those using the original 50 spectral bands. This could be explained by the loss of tree crowns enabling better signal penetration, thus leading to reduced spectral variation from canopies. Hence, spectral bands containing a high degree of random noise were correctly removed by the band reduction algorithms. Compared to the middle-stage, the late-stage forest stands were covered by large piles of fallen trees and branches, resulting in higher variability of MASTER imagery. The ability of band reduction to improve the model performance for these late-stage forest stands was reduced, because the valuable spectral variation representing the actual late-stage forest status was partially removed by both algorithms as noise. Our results indicate that PCA and MNF are promising for balancing computation efficiency and the performance of burn severity models in forest stands subject to the middle and late stages of sudden oak death disease progression. Compared to PCA, MNF dramatically reduced image spectral variation, generating larger image objects with less complexity of object shapes. Whereas, PCA-based models delivered superior performance in most evaluated cases suggesting that some key spectral variability contributing to the accuracy of burn severity models in diseased forests may have been removed together with true spectral noise through MNF transformations. Numéro de notice : A2015-475 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.01.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.01.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77183
in ISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 38 - 47[article]Employing ground and satellite-based QuickBird data and Random forest to discriminate five tree species in a Southern African Woodland / Samuel Adelabu in Geocarto international, vol 30 n° 3 - 4 (March - April 2015)
[article]
Titre : Employing ground and satellite-based QuickBird data and Random forest to discriminate five tree species in a Southern African Woodland Type de document : Article/Communication Auteurs : Samuel Adelabu, Auteur ; Timothy Dube, Auteur Année de publication : 2015 Article en page(s) : pp 457 - 471 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Afrique du sud (état)
[Termes IGN] analyse diachronique
[Termes IGN] Botswana
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données de terrain
[Termes IGN] espèce végétale
[Termes IGN] forêt
[Termes IGN] image hyperspectrale
[Termes IGN] image Quickbird
[Termes IGN] rééchantillonnage
[Termes IGN] réflectance végétale
[Termes IGN] savaneRésumé : (Auteur) With the emergence of very high spatial and spectral resolution data set, the resolution gap that existed between remote-sensing data set and aerial photographs has decreased. The decrease in resolution gap has allowed accurate discrimination of different tree species. In this study, discrimination of indigenous tree species (n = 5) was carried out using ground based hyperspectral data resampled to QuickBird bands and the actual QuickBird imagery for the area around Palapye, Botswana. The purpose of the study was to compare the accuracies of resampled hyperspectral data (resampled to QuickBird sensors) with the actual image (QuickBird image) in discriminating between the indigenous tree species. We performed Random Forest (RF) using canopy reflectance taking from ground-based hyperspectral sensor and the reflectance delineated regions of the tree species. The overall accuracies for classifying the five tree species was 79.86 and 88.78% for both the resampled and actual image, respectively. We observed that resampled data set can be upscale to actual image with the same or even greater level of accuracy. We therefore conclude that high spectral and spatial resolution data set has substantial potential for tree species discrimination in savannah environments. Numéro de notice : A2015-306 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2014.885589 Date de publication en ligne : 31/03/2014 En ligne : https://doi.org/10.1080/10106049.2014.885589 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76524
in Geocarto international > vol 30 n° 3 - 4 (March - April 2015) . - pp 457 - 471[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2015021 RAB Revue Centre de documentation En réserve L003 Disponible Spectroscopic analysis of green, desiccated and dead tamarisk canopies / Ran Meng in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 3 (March 2015)
[article]
Titre : Spectroscopic analysis of green, desiccated and dead tamarisk canopies Type de document : Article/Communication Auteurs : Ran Meng, Auteur ; Philip E. Dennison, Auteur Année de publication : 2015 Article en page(s) : pp 199 - 207 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande infrarouge
[Termes IGN] bande rouge
[Termes IGN] bande spectrale
[Termes IGN] insecte nuisible
[Termes IGN] rayonnement proche infrarouge
[Termes IGN] réflectance végétale
[Termes IGN] risque naturel
[Termes IGN] Tamarix (genre)Résumé : (auteur) Defoliation by the northern tamarisk beetle (Diorhabda carinulata) causes changes in the reflectance of tamarisk (Tamarix spp.) canopies. Cross correlogram spectral matching was used to examine spectral separability of green, yellow desiccated, brown desiccated, and dead tamarisk canopy types. Using a feature selection technique (the instability index), four spectral regions were identified as important for canopy type discrimination, including one red (645-693 nm), one near infrared (735-946 nm), and two shortwave infrared regions (1,960-2,090 nm and 2,400-2,478 nm). The random forests decision tree algorithm was used to compare classification performances of full-range and feature-selected hyperspectral spectra as well as simulated WorldView-2 spectra. Classification results indicated that the process of feature selection can reduce data redundancy and computation time while improving accuracy of tamarisk canopy type classification. Numéro de notice : A2015-969 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.81.3.199-207 En ligne : https://doi.org/10.14358/PERS.81.3.199-207 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80027
in Photogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 3 (March 2015) . - pp 199 - 207[article]Retrieving surface variables by integrating ground measurements and earth observation data in forest canopies : a case study in Speuldersbos forest / Kitsiri Weligepolage (2015)
Titre : Retrieving surface variables by integrating ground measurements and earth observation data in forest canopies : a case study in Speuldersbos forest Type de document : Thèse/HDR Auteurs : Kitsiri Weligepolage, Auteur Editeur : Enschede [Pays Bas] : University of Twente Année de publication : 2015 Collection : ITC Dissertation num. 269 Importance : 148 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-90-365-3876-3 Note générale : bibliographie
University of Twente, Faculty of Geo-Information and Earth ObservationLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] aiguille
[Termes IGN] albedo
[Termes IGN] canopée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Fagus (genre)
[Termes IGN] hauteur des arbres
[Termes IGN] image AHS
[Termes IGN] image thermique
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] Pinophyta
[Termes IGN] Pseudotsuga menziesii
[Termes IGN] réflectance végétale
[Termes IGN] rugosité
[Termes IGN] température au solRésumé : (auteur) The main objective of this study is to integrate tower-based measurements with ED data for estimating spatially and temporally distributed surface variables of a forest canopy for improved quantification of surface-atmosphere interactions. This study mainly focuses on three of the most important surface variables for estimating surface fluxes, namely the aerodynamic roughness, land surface albedo and land surface temperature.
In chapter 2, a framework is presented for estimating aerodynamic roughness parameters: the momentum roughness length (z0) and the displacement height (do) of a coniferous forest stand using remote sensing data. The specific objective of the study is to make use of high resolution Terrestrial Laser Scanning (TLS) data together with Airborne Laser Scanning (ALS) data to digitally map the upper canopy surface in order to generate high resolution digital Canopy Height Models (CHMs). The digital CHMs were subsequently used to extract surface geometric parameters of the upper canopy surface. Eventually the surface geometric parameters were used as input variables in the selected morphometric models to estimate aerodynamic roughness parameters. It was observed that the estimated values of zo and do depend very much on the selected model. Comparison of model estimated roughness parameters against the literature values for similar surface types has shown that the technique can be successfully applied to estimate forest surface roughness by tuning some of the model parameters to resemble the forest structure of the study area.
Chapter 3 describes the use of these two aerodynamic methods to estimate momentum roughness length and displacement height of Douglas fir forest using simultaneous micrometeorological and flux measurements. When the flux-gradient method was used to objectively determine zo and do, corrections for roughness sub-layer effects proved to be important. A new iterative method is employed to solve the set of equations when the corrections were made. In the absence of experimentally determined roughness sub-layer height, the corrections of Harman and Finnigan (2007) yielded the best overall estimates of aerodynamic parameters. Comparison with results of over 25 other studies has shown that the results obtained in this work fit the general trend rather well. Two quadratic relationships are proposed to predict do and ha based on the observed mean tree height. These simple relationships can be easily incorporated to large scale land surface models, provided that spatially distributed tree height information is available. The flux-variance technique is shown to be robust even when measurements are made in the roughness sub-layer. However the technique cannot be objectively used to estimate zo and do as no explicit method exists to select the exact value for coefficient C1.
A detailed investigation of stand level surface albedo variability of a patchwork forest is presented in chapter 4. The top of the canopy reflectance in the visible and near-infrared domain retrieved from airborne and satellite imageries were integrated to estimate spatially distributed surface albedo while the tower-based radiation measurements in the solar-reflective region were used to obtain the temporal variation of surface albedo over a needleleaf forest canopy. The diurnal variation of surface albedo is consistent with the previous findings for needleleaf forest canopies. The spatial mean surface albedo values estimated from remote sensing data for needleleaf (pure Douglas fir), broadleaf (pure Beech) and mixed forest classes are 0.09, 0.13 and 0.11 respectively. Both visual characteristics and descriptive statistics indicate that with increased pixel size, the spatial variability of albedo progressively decreases. The semivariogram analysis was more insightful to perceive the nature and causes of albedo spatial variability in different forest classes in relation to sensor spatial resolution.
Finally a theoretical basis for directional LST estimation from top of the atmosphere radiance measurements is presented along with a spatio-temporal analysis of remotely sensed LST and concurrently carried out ground-based radiation together with contact temperature measurements in a Douglas fir forest. For the analysis we used remotely sensed TIR data from Airborne Hyperspectral Scanner to estimate spatially distributed LST of forested area. The AHS sensor, with 10 thermal bands covering the range between 8 and 13pm of the electromagnetic spectrum is an example of the new generation of airborne sensors with multispectral thermal infrared capabilities. The data acquired from the AHS sensors provided the opportunity to retrieve the directional LST of the forest canopy with a very high spatial resolution for both nadir and oblique view angles. Also the concurrent tower-based temperature measurements provided limited ground truth for a spatio-temporal analysis of surface temperature in an area covered with Douglas fir trees. The method adopted here for concurrent determination of LST and LSE is the widely-used TES algorithm together with the MODTRAN4 preprocessor for calculating the required atmospheric contributions. AHS derived average temperature values are generally in good agreement with the tower based component temperature measured at 24 m level whereas the component temperatures (trunk) measured at 17 m are consistently higher. It may be noted that in comparison with off-nadir radiometric temperature the TES method provides average LST with RMSE around 1.9K while the corresponding value with respect to component temperature measured at 24 m is around 1.4 K.Note de contenu : 1- Introduction
2- Estimation of canopy aerodynamic roughness using morphometric methods
3- Effects of sub-layer corrections on the roughness parametrization of a Douglas fir forest
4- Effects of spatial resolution on estimating surface albedo
5- Retrieving directional temperature using multiplatform thermal data
6- Conclusion and recommendationsNuméro de notice : 14944 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse étrangère Note de thèse : PhD : Geo-Information and Earth Observation : University of Twente : 2015 En ligne : https://research.utwente.nl/en/publications/retrieving-surface-variables-by-inte [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77060 Documents numériques
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14944 Retrieving surface variablesAdobe Acrobat PDF Retrieving the stand age from a retrospective detection of multinannual forest changes using Landsat data. Application on the heavily managed maritime pine forest in Southwestern France from a 30-year Landsat time-series (1984–2014) / Dominique Guyon (2015)PermalinkDeriving 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)PermalinkCrop type classification by simultaneous use of satellite images of different resolutions / Mark W. Liu in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)PermalinkLaboratory measurements of plant drying: Implications to estimate moisture content from radiative transfer models in two temperate species / Sara Jurdao in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 5 (May 2014)PermalinkDeriving leaf mass per area (LMA) from foliar reflectance across a variety of plant species using continuous wavelet analysis / Tao Cheng in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)PermalinkUsing hyperspectral reflectance data to assess biocontrol damage of giant salvinia / James H. Everitt in Geocarto international, vol 28 n° 5-6 (August - October 2013)PermalinkBuilding a forward-mode three-dimensional reflectance model for topographic normalization of High-Resolution (1–5 m) imagery: validation phase in a forested environment / Stéphane Couturier in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 1 (July 2013)PermalinkAssessing the impact of hydrocarbon leakages on vegetation using reflectance spectroscopy / I.D. Sanches in ISPRS Journal of photogrammetry and remote sensing, vol 78 (April 2013)PermalinkMaterial reflectance retrieval in urban tree shadows with physics-based empirical atmospheric correction / Karine R.M. Adeline (2013)PermalinkModeling and simulation of polarimetric hyperspectral imaging process / Junping Zhang in IEEE Transactions on geoscience and remote sensing, vol 50 n° 6 (June 2012)Permalink