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Discrimination of deciduous tree species from time series of unmanned aerial system imagery / Jonathan Lisein in Plos one, vol 10 n° 11 (November 2015)
[article]
Titre : Discrimination of deciduous tree species from time series of unmanned aerial system imagery Type de document : Article/Communication Auteurs : Jonathan Lisein , Auteur ; Adrien Michez, Auteur ; Hugues Claessens, Auteur ; Philippe Lejeune, Auteur Année de publication : 2015 Article en page(s) : n° 0141006 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse discriminante
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] drone
[Termes IGN] houppier
[Termes IGN] image aérienne
[Termes IGN] orthoimage
[Termes IGN] orthophotoplan numérique
[Termes IGN] phénologie
[Termes IGN] variation saisonnièreRésumé : (auteur) Technology advances can revolutionize Precision Forestry by providing accurate and fine forest information at tree level. This paper addresses the question of how and particularly when Unmanned Aerial System (UAS) should be used in order to efficiently discriminate deciduous tree species. The goal of this research is to determine when is the best time window to achieve an optimal species discrimination. A time series of high resolution UAS imagery was collected to cover the growing season from leaf flush to leaf fall. Full benefit was taken of the temporal resolution of UAS acquisition, one of the most promising features of small drones. The disparity in forest tree phenology is at the maximum during early spring and late autumn. But the phenology state that optimized the classification result is the one that minimizes the spectral variation within tree species groups and, at the same time, maximizes the phenologic differences between species. Sunlit tree crowns (5 deciduous species groups) were classified using a Random Forest approach for monotemporal, two-date and three-date combinations. The end of leaf flushing was the most efficient single-date time window. Multitemporal datasets definitely improve the overall classification accuracy. But single-date high resolution orthophotomosaics, acquired on optimal time-windows, result in a very good classification accuracy (overall out of bag error of 16%). Numéro de notice : A2015--031 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1371/journal.pone.0141006 En ligne : http://dx.doi.org/10.1371/journal.pone.0141006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81106
in Plos one > vol 10 n° 11 (November 2015) . - n° 0141006[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]Improving forest aboveground biomass estimation using seasonal Landsat NDVI time-series / Xiaolin Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)
[article]
Titre : Improving forest aboveground biomass estimation using seasonal Landsat NDVI time-series Type de document : Article/Communication Auteurs : Xiaolin Zhu, Auteur ; Desheng Liu, Auteur Année de publication : 2015 Article en page(s) : pp 222 - 231 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] biomasse forestière
[Termes IGN] image Landsat
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] puits de carbone
[Termes IGN] série temporelle
[Termes IGN] variation saisonnièreRésumé : (auteur) Spatially explicit knowledge of aboveground biomass (AGB) in large areas is important for accurate carbon accounting. Landsat data have been widely used to provide efficient and timely estimates of forest AGB because of their long archive and relatively high spatial resolution. Previous studies have explored different empirical modeling approaches to estimate AGB, but most of them only used a single Landsat image in the peak season, which may cause a saturation problem and low accuracy. To improve the accuracy of AGB estimation using Landsat images, this study explored the use of NDVI seasonal time-series derived from Landsat images across different seasons to estimate AGB in southeast Ohio by six empirical modeling approaches. Results clearly show that NDVI in the fall season has a stronger correlation to AGB than in the peak season, and using seasonal NDVI time-series can result in a more accurate AGB estimation and less saturation than using a single NDVI. In comparing these different empirical approaches, it is difficult to decide which one is superior to the other because they have different strengths and their accuracy is generally similar, indicating that modeling methods may not be the key issue for improving the accuracy of AGB estimation from Landsat data. This study suggests that future research should pay more attention to seasonal time-series data, and especially the data from the fall season. Numéro de notice : A2015-695 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.08.014 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.08.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78329
in ISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 222 - 231[article]
Titre : GPS time-variable seasonal signals modeling Type de document : Mémoire Auteurs : Qiang Chen, Auteur Editeur : Stuttgart : University of Stuttgart Année de publication : 2015 Importance : 65 p. Format : 21 x 30 cm Note générale : bibliographie
mémoire de master, Université de StuttgartLangues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] analyse de spectre singulier
[Termes IGN] compensation par moindres carrés
[Termes IGN] données GPS
[Termes IGN] filtrage du bruit
[Termes IGN] filtre de Kalman
[Termes IGN] oscillation
[Termes IGN] série temporelle
[Termes IGN] variation saisonnière
[Vedettes matières IGN] Traitement de données GNSSIndex. décimale : MX Mémoires divers Résumé : (auteur) Seasonal signals (annual plus semi-annual) in GPS time series are of great importance for understanding the evolution of regional mass, i.e. ice and hydrology. Conventionally these signals (annual and semi-annual) are derived by least-squares fitting of harmonic terms with a constant amplitude and phase. In reality, however, such seasonal signals are modulated, i.e. they will have a time-variable amplitude and phase. Recently, Davis et al. (2012) proposed a Kalman filter based approach to capture the stochastic seasonal behavior of geodetic time series. In this study, a non-parametric approach, singular spectrum analysis (SSA) is introduced. It uses time domain data to extract information from short and noisy time series without prior knowledge of the dynamics affecting the time series. A prominent benefit is that obtained trends are not necessarily linear and extracted oscillations can be amplitude and phase modulated. In this work, the capability of SSA for analyzing time-variable seasonal signals from GPS time series is investigated. We also compare SSA-based results to two model-based results, i.e. least-squares analysis and Kalman filtering. Our results show that singular spectrum analysis could be a viable and complementary tool for exploring modulated oscillations from GPS time series. Based on the SSA-derived seasonal signals, we look into the effects of the input noise variances in the framework of Kalman filtering. Two Kalman filtering based approaches with different process noise models are compared over 79 GPS sites. We find that the basic Kalman filtering technique with the input noise model suggested by Davis et al. (2012) turns out to be optimal. Numéro de notice : 17348 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Mémoire masters divers En ligne : http://dx.doi.org/10.18419/opus-8824 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83707 Improved land cover mapping using aerial photographs and satellite images / Katalin Varga in Open geosciences, vol 7 n° 1 (January 2015)
[article]
Titre : Improved land cover mapping using aerial photographs and satellite images Type de document : Article/Communication Auteurs : Katalin Varga, Auteur ; Szilárd Szabó, Auteur ; Gergely Szabó, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 15 - 26 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] couvert végétal
[Termes IGN] image aérienne
[Termes IGN] image Landsat
[Termes IGN] MNS SRTM
[Termes IGN] précision de la classification
[Termes IGN] variation saisonnièreRésumé : (auteur) Manual Land Cover Mapping using aerial photographs provides sufficient level of resolution for detailed vegetation or land cover maps. However, in some cases it is not possible to achieve the desired information over large areas, for example from historical data where the quality and amount of available images is definitely lower than from modern data. The use of automated and semi automated methods offers the means to identify the vegetation cover using remotely sensed data. In this paper automated methods were tested on aerial photographs and satellite images to extract better and more reliable information about vegetation cover. These testswere performed by using automated analysis of LANDSAT7 images (with and without the surface model of the Shuttle Radar Topography Mission (SRTM)) and two temporally similar aerial photographs. The spectral bands were analyzed with supervised (maximum likelihood) methods. In conclusion, the SRTM and the combination of two temporally similar aerial photographs from earlier years were useful in separating the vegetation cover on a floodplain area. In addition the different date of the vegetation season also gave reliable information about the land cover. High quality information about old and present vegetation on a large area is an essential prerequisites ensuring the conservation of ecosystems. Numéro de notice : A2015-435 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1515/geo-2015-0002 En ligne : https://doi.org/10.1515/geo-2015-0002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77035
in Open geosciences > vol 7 n° 1 (January 2015) . - pp 15 - 26[article]Social status-mediated tree-ring responses to climate of Abies alba and Fagus sylvatica shift in importance with increasing stand basal area / François Lebourgeois in Forest ecology and management, Vol 328 (September 2014)PermalinkHyperspectral data dimensionality reduction and the impact of multi-seasonal Hyperion EO-1 imagery on classification accuracies of tropical forest species / Manjit Saini in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 8 (August 2014)PermalinkThe quest for a consistent signal in ground and GRACE gravity time-series / Michel Van Camp in Geophysical journal international, vol 197 n° 1 (April 2014)Permalink3D tree reconstruction from simulated small footprint waveform lidar / Jiaying Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 12 (December 2013)PermalinkSingular spectrum analysis for modeling seasonal signals from GPS time series / Q. Chen in Journal of geodynamics, vol 72 (December 2013)PermalinkSubseasonal GNSS positioning errors / Jim Ray in Geophysical research letters, vol 40 n° 22 (November 2013)PermalinkImpact of seasonal station motions on VLBI UT1 intensives results / Zinovy Malkin in Journal of geodesy, vol 87 n° 6 (June 2013)PermalinkRemote sensing of seasonal variability of fractional vegetation cover and its object-based spatial pattern analysis over mountain areas / Guijun Yang in ISPRS Journal of photogrammetry and remote sensing, vol 77 (March 2013)PermalinkEstimating irrigated agricultural water use through Landsat TM and a simplified surface energy balance modeling in the semi-arid environments of Arizona / S. Kaplan in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 8 (August 2012)PermalinkVariations saisonnière et annuelle de l'indice NDVI en relation avec les herbiers de zosteres (zostera noltii) par images satellites Spot : exemple du Bassin d'Arcachon (France) / J.M. Froidefond in Revue Française de Photogrammétrie et de Télédétection, n° 197 (Juin 2012)Permalink