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A Bayesian network-based method to alleviate the ill-posed inverse problem: A case study on leaf area index and canopy water content retrieval / Xingwen Quan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)
[article]
Titre : A Bayesian network-based method to alleviate the ill-posed inverse problem: A case study on leaf area index and canopy water content retrieval Type de document : Article/Communication Auteurs : Xingwen Quan, Auteur ; Binbin He, Auteur ; Xing Li, Auteur Année de publication : 2015 Article en page(s) : pp 6507 - 6517 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] appariement d'images
[Termes IGN] image Landsat-8
[Termes IGN] Leaf Area Index
[Termes IGN] probabilité
[Termes IGN] problème inverse
[Termes IGN] réseau bayesien
[Termes IGN] teneur en eau de la végétationRésumé : (auteur) Retrieval of vegetation parameters from remotely sensed data using a radiative transfer model is generally hampered by the ill-posed inverse problem, which dramatically decreases the precision level of retrieved parameters. The purpose of this study was to use a Bayesian network-based method to allow the alleviation of the ill-posed inverse problem. This was achieved by introducing the correlations between the model free parameters into their prior joint probability distribution (PJPD), allowing the reduction of the probabilities of unrealistic combinations. Three sampling strategies intended to design three types of PJPDs that considered different correlations (represented by a correlation matrix) were presented. They were multivariate uniform distribution composed by independent free parameters, multivariate uniform distribution based on a simple correlation matrix, and multivariate Gaussian distribution based on a complicated correlation matrix, respectively. A case study of the presented method to retrieve leaf area index (LAI) and canopy water content (CWC) using the PROSAIL_5B (PROSPECT-5 + 4SAIL) model from Landsat 8 products was implemented. Results indicate that the presented method greatly improves the precision level of target parameters, with the coefficient of determination R2 of 0.69, 0.77, and 0.82 and root-mean-square error (RMSE) of 0.55, 0.51, and 0.44 m2 · m-2 for LAI and R2 = 0.68, 0.78, and 0.84 and RMSE = 230, 198, and 166 g · m-2 for CWC, respectively. Hence, the ill-posed inverse problem can be alleviated by the presented method, which can be widely applied for vegetation parameters retrieval. Numéro de notice : A2015-838 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2442999 Date de publication en ligne : 30/06/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2442999 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79172
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 12 (December 2015) . - pp 6507 - 6517[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2015121 SL Revue Centre de documentation Revues en salle Disponible A moving weighted harmonic analysis method for reconstructing high-quality SPOT VEGETATION NDVI time-series data / Gang Yang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 11 (November 2015)
[article]
Titre : A moving weighted harmonic analysis method for reconstructing high-quality SPOT VEGETATION NDVI time-series data Type de document : Article/Communication Auteurs : Gang Yang, Auteur ; Huanfeng Shen, Auteur ; Liangpei Zhang, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 6008 - 6021 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] analyse harmonique
[Termes IGN] Chine
[Termes IGN] filtrage numérique d'image
[Termes IGN] image SPOT-Végétation
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] occupation du sol
[Termes IGN] série temporelle
[Termes IGN] surveillance de la végétationRésumé : (Auteur) Global or regional environmental change is of wide concern. Extensive studies have indicated that long-term vegetation cover change is one of the most important factors reflecting environmental change, and normalized difference vegetation index (NDVI) time-series data sets have been widely used in vegetation dynamic change monitoring. However, the significant residual effects and noise levels impede the application of NDVI time-series data in environmental change research. This study develops a novel and robust filter method, i.e., the moving weighted harmonic analysis (MWHA) method, which incorporates a moving support domain to assign the weights for all the points, making the determination of the frequency number much easier. Additionally, a four-step process flow is designed to make the data approach the upper NDVI envelope, so that the actual change in the vegetation can be detected. A total of 487 test pixels selected from SPOT VEGETATION 10-day MVC NDVI time-series data from January 1999 to December 2001 were used to illustrate the effectiveness of the new method by comparing the MWHA results with the results of another four existing methods. Finally, the long-term SPOT VEGETATION 10-day maximum-value compositing (MVC) NDVI time series for China from April 1998 to May 2014 was reconstructed by the use of the proposed method, and a test region in China was utilized to validate the effectiveness of the proposed MWHA method. All the results indicate that the reconstructed high-quality NDVI time series fits the actual growth profile of the vegetation and is suitable for use in further remote sensing applications. Numéro de notice : A2015-771 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2431315 Date de publication en ligne : 02/06/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2431315 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78827
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 11 (November 2015) . - pp 6008 - 6021[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2015111 SL Revue Centre de documentation Revues en salle Disponible Monitoring forest cover loss using multiple data streams, a case study of a tropical dry forest in Bolivia / Loïc Paul Dutrieux in ISPRS Journal of photogrammetry and remote sensing, vol 107 (September 2015)
[article]
Titre : Monitoring forest cover loss using multiple data streams, a case study of a tropical dry forest in Bolivia Type de document : Article/Communication Auteurs : Loïc Paul Dutrieux, Auteur ; Jan Verbesselt, Auteur ; Lammert Kooistra, Auteur ; Martin Herold, Auteur Année de publication : 2015 Article en page(s) : pp 112 - 125 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Bolivie
[Termes IGN] déboisement
[Termes IGN] détection de changement
[Termes IGN] forêt tropicale
[Termes IGN] image Terra-MODIS
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] sécheresse
[Termes IGN] série temporelle
[Termes IGN] variabilitéRésumé : (auteur) Automatically detecting forest disturbances as they occur can be extremely challenging for certain types of environments, particularly those presenting strong natural variations. Here, we use a generic structural break detection framework (BFAST) to improve the monitoring of forest cover loss by combining multiple data streams. Forest change monitoring is performed using Landsat data in combination with MODIS or rainfall data to further improve the modelling and monitoring. We tested the use of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) with varying spatial aggregation window sizes as well as a rainfall derived index as external regressors. The method was evaluated on a dry tropical forest area in lowland Bolivia where forest cover loss is known to occur, and we validated the results against a set of ground truth samples manually interpreted using the TimeSync environment. We found that the addition of an external regressor allows to take advantage of the difference in spatial extent between human induced and naturally induced variations and only detect the processes of interest. Of all configurations, we found the 13 by 13 km MODIS NDVI window to be the most successful, with an overall accuracy of 87%. Compared with a single pixel approach, the proposed method produced better time-series model fits resulting in increases of overall accuracy (from 82% to 87%), and decrease in omission and commission errors (from 33% to 24% and from 3% to 0% respectively). The presented approach seems particularly relevant for areas with high inter-annual natural variability, such as forests regularly experiencing exceptional drought events. Numéro de notice : A2015-726 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.03.015 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.03.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78378
in ISPRS Journal of photogrammetry and remote sensing > vol 107 (September 2015) . - pp 112 - 125[article]BRDF-corrected vegetation indices confirm seasonal pattern in greening of French Guiana's forests / Emil A. Cherrington in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)
[article]
Titre : BRDF-corrected vegetation indices confirm seasonal pattern in greening of French Guiana's forests Type de document : Article/Communication Auteurs : Emil A. Cherrington, Auteur ; Grégoire Vincent, Auteur ; Daniel Sabatier, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 3 - 9 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] forêt tropicale
[Termes IGN] Guyane (département français)
[Termes IGN] image SPOT-Végétation
[Termes IGN] image Terra-MODIS
[Termes IGN] indice de végétation
[Termes IGN] phénologie
[Termes IGN] surveillance forestière
[Termes IGN] variation saisonnièreRésumé : (auteur) Remote sensing is a useful tool set for monitoring changes in forest ecosystems, particularly remote and otherwise inaccessible tracts of tropical forest. To revisit findings of earlier satellite-based studies of phenological variation in Amazonian forests, the current study focused on the variation of vegetation indices (Vis) of French Guiana. Specifically, 12 years of VI data which had been treated for bi-directional effects were extracted from the archives of 2 particular satellite sensors: the SPOT VEGETATION instrument, and MODIS (the MODerate resolution Imaging Spectroradiometer). At the scale of the entire territory of French Guiana, as well as at 4 sites across the territory, VI data displayed strong seasonal patterns, with the dry season months having significantly higher VI estimates than the wet season months. As Vls are considered proxies for photosynthetic activity, those seasonal variations would seem to indicate leaf-Flushing across French Guiana's forests during the dry season months of September to October. Numéro de notice : A2015-900 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.52638/rfpt.2015.536 Date de publication en ligne : 30/12/2020 En ligne : https://doi.org/10.52638/rfpt.2015.536 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79555
in Revue Française de Photogrammétrie et de Télédétection > n° 211 - 212 (juillet - décembre 2015) . - pp 3 - 9[article]In situ calibration of light sensors for long-term monitoring of vegetation / Hongxiao Jin in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)
[article]
Titre : In situ calibration of light sensors for long-term monitoring of vegetation Type de document : Article/Communication Auteurs : Hongxiao Jin, Auteur ; Lars Eklundh, Auteur Année de publication : 2015 Article en page(s) : pp 3405 - 3416 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] capteur terrestre
[Termes IGN] étalonnage de capteur (imagerie)
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] photosynthèse
[Termes IGN] propagation d'erreur
[Termes IGN] surveillance forestièreRésumé : (Auteur) Light sensors are increasingly used to monitor vegetation growing status by measuring reflectance or transmittance in multispectral or photosynthetically active radiation (PAR) bands. The measurements are then used to estimate vegetation indices or the fraction of absorbed PAR (FPAR) in a continuous and long-term manner and to serve as inputs to environmental monitoring and calibration/validation data for satellite remote sensing. However, light-sensor calibration is often overlooked or not properly attended to, which leads to difficulties when comparing the measurement results across sites and through time. In this paper, we investigate a practical and accurate user-level in situ calibration method in daylight. The calibration of a sensor pair is made for measuring either bihemispherical reflectance or hemispherical-conical reflectance, which are the two most common ground-based spectral measurements. Procedures and considerations are suggested for user calibration. We also provide a method for calibrating and measuring a single-sensor reflectance-derived Normalized Difference Vegetation Index (NDVI) from red and near-infrared bands. The calibration error propagation is analyzed, and the induced uncertainties in vegetation reflectance and in the NDVI are evaluated. The analysis and field measurements show that the NDVI estimated from a user calibration factor can be as accurate as, or even more accurate than, the manufacturer's calibration. The in situ calibration described here remedies the situation where reflectance for large field-of-view sensors cannot be always estimated from the manufacturer's calibration. The method developed in this paper may help improve the reliability of long-term field spectral measurements and contributes to the near-surface remote sensing of vegetation. Numéro de notice : A2015-275 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2375381 Date de publication en ligne : 18/12/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2375381 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76388
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 6 (June 2015) . - pp 3405 - 3416[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2015061 SL Revue Centre de documentation Revues en salle Disponible Utilisation des données des capteurs MODIS et SPOT-VGT pour l'analyse de la dynamique des feux dans deux territoires (réserve protégée et unités pastorales) au Ferlo (Sénégal) / Mamadou Adama Sarr in Photo interprétation, European journal of applied remote sensing, vol 51 n° 2 (juin 2015)PermalinkValidation of canopy height profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment / Karolina D. Fieber in ISPRS Journal of photogrammetry and remote sensing, vol 104 (June 2015)PermalinkAn improved species distribution model for Scots pine and downy oak under future climate change in the NW Italian Alps / Giorgio Vacchiano in Annals of Forest Science, vol 72 n° 3 (May 2015)PermalinkDo competition-density rule and self-thinning rule agree? / Sonja Vospernik in Annals of Forest Science, vol 72 n° 3 (May 2015)PermalinkMultispectral sensor spectral resolution simulations for generation of hyperspectral vegetation indices from Hyperion data / Prabir Das in Geocarto international, vol 30 n° 5 - 6 (May - July 2015)PermalinkEvaluating 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)PermalinkImproving forest aboveground biomass estimation using seasonal Landsat NDVI time-series / Xiaolin Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)PermalinkLidar with multi-temporal MODIS provide a means to upscale predictions of forest biomass / Le Li in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)PermalinkEvaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)PermalinkMODIS-based vegetation index has sufficient sensitivity to indicate stand-level intra-seasonal climatic stress in oak and beech forests / Tomáš Hlásny in Annals of Forest Science, vol 72 n° 1 (January 2015)Permalink