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Recent changes in two outlet glaciers in the Antarctic Peninsula using multi-temporal Landsat and Sentinel-1 data / Carolina L. Simões in Geocarto international, vol 35 n° 11 ([01/08/2020])
[article]
Titre : Recent changes in two outlet glaciers in the Antarctic Peninsula using multi-temporal Landsat and Sentinel-1 data Type de document : Article/Communication Auteurs : Carolina L. Simões, Auteur ; Katia K. Rosa, Auteur ; Jefferson C. Simões, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1233 - 1244 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Antarctique
[Termes IGN] changement climatique
[Termes IGN] détection de changement
[Termes IGN] fonte des glaces
[Termes IGN] glacier
[Termes IGN] image Sentinel-SAR
[Termes IGN] pente
[Termes IGN] superficieRésumé : (auteur) This work investigates the dynamics of the ice front retreat of two tidewater glaciers in adjacent valleys, Drummond and Widdowson (66°43'S, 65°46'W), on the western coast of the Antarctic Peninsula over the past six decades. The Widdowson Glacier had a more significant area loss (36.37 km2 or 16.97%) and a higher snow line elevation (200 m above sea level (a.s.l.) in 2016) than the Drummond Glacier (19.11 km2, or 4.33%; snow line at 100 m a.s.l. in 2016). This difference in the retreat of the two glaciers is attributed slopes and accumulation areas values. The glacier with a smaller area, Widdowson, has been shown to be more sensitive to environmental changes Their steeper glacier front may have influenced the calving rate and generated a more efficient basal slip, increasing the ice flow rate and consequently increasing the retreat rate. Numéro de notice : A2020-458 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1576776 Date de publication en ligne : 14/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1576776 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95565
in Geocarto international > vol 35 n° 11 [01/08/2020] . - pp 1233 - 1244[article]Towards a semi-automated mapping of Australia native invasive alien Acacia trees using Sentinel-2 and radiative transfer models in South Africa / Cecilia Masemola in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)
[article]
Titre : Towards a semi-automated mapping of Australia native invasive alien Acacia trees using Sentinel-2 and radiative transfer models in South Africa Type de document : Article/Communication Auteurs : Cecilia Masemola, Auteur ; Moses Azong Cho, Auteur ; Abel Ramoelo, Auteur Année de publication : 2020 Article en page(s) : pp 153 - 168 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Acacia (genre)
[Termes IGN] Afrique du sud (état)
[Termes IGN] canopée
[Termes IGN] cartographie automatique
[Termes IGN] chlorophylle
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] échantillonnage
[Termes IGN] espèce exotique envahissante
[Termes IGN] essence indigène
[Termes IGN] image Sentinel-MSI
[Termes IGN] Leaf Area Index
[Termes IGN] modèle de transfert radiatif
[Termes IGN] réflectance
[Termes IGN] surveillance de la végétationRésumé : (auteur) Invasive alien plants (IAPs) threaten biodiversity and critical ecosystem services worldwide. There is, therefore, an urgent need to develop intervention measures to control the spread of IAPs. Efforts to control and monitor the spread of IAPs would require their current and detailed distribution over a large geographic area. Recently launched multispectral instrument on-board Sentinel-2 provides free data with good spatiotemporal and spectral resolution, compared to Landsat datasets. The Sentinel-2 dataset, therefore, can be a useful source of the IAPs spatial information required for detection and monitoring purposes. We combined Sentinel-2 data with a radiative transfer model to discriminate IAPs (Acacia mearnsii and Acacia dealbata) from surrounding native tree species in Van Reenen, KwaZulu-Natal, South Africa. The forward mode of combined PROSPECT leaf optical properties model and SAIL canopy bidirectional reflectance model, also referred to as PROSAIL was used to simulate reflectance corresponding to bands of Sentinel-MSI, while the PROSAIL model inversion retrieved leaf area index (LAI) and canopy chlorophyll contents (CCC) of the IAPs and native species. Both reflectance and retrieved properties were used to map the distribution of the species within the study area. Our results showed that A. mearnsii and A. dealbata could be accurately discriminated from the surrounding native trees using integrated PROSAIL Sentinel-2 based model. We found that CCC– and LAI-based (% accuracy = 92.8%, 91.4% for CCC and LAI, respectively) modelling produced a higher classification accuracy than field sampling-based modelling (Accuracy = 90.2% (IAP), 82.2% (NAT) and kappa coefficient = 0.84 (IAP), 0.78 (NAT)). Simulated bands corresponding to Sentinel-2 data, on the other hand, produced species maps comparable to field sampling-based maps. Overall, the integrated PROSAIL Sentinel-2 inversion approach proved suitable for detecting and mapping IAPs over a large area. Due to the high spatiotemporal coverage of Sentinel-2, satellite images, the model developed showed the potential to contribute to the IAPs monitoring systems. Numéro de notice : A2020-352 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.04.009 Date de publication en ligne : 13/06/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.04.009 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95235
in ISPRS Journal of photogrammetry and remote sensing > vol 166 (August 2020) . - pp 153 - 168[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020083 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020082 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Cartographie des surfaces pastorales à l’aide des données Sentinel 2 L3A et des données ouvertes : Promesses et réalités / Urcel Kalenga Tshingomba in Revue internationale de géomatique, vol 30 n° 3-4 (juillet - décembre 2020)
[article]
Titre : Cartographie des surfaces pastorales à l’aide des données Sentinel 2 L3A et des données ouvertes : Promesses et réalités Titre original : Mapping of pastoral areas using Sentinel 2 L3A data and open data. Promises and realities Type de document : Article/Communication Auteurs : Urcel Kalenga Tshingomba, Auteur ; Magali Jouven, Auteur ; Lucile Sautot, Auteur ; Imad Shaqura, Auteur ; Maguelonne Teisseire, Auteur Année de publication : 2020 Article en page(s) : pp 245 - 277 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] BD forêt
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données ouvertes
[Termes IGN] image Sentinel-MSI
[Termes IGN] Occitanie (région 2016)
[Termes IGN] parcours
[Termes IGN] Provence-Alpes-Côte d'Azur
[Termes IGN] Registre parcellaire graphiqueRésumé : (auteur) Dans cet article, les auteurs expérimentent une démarche permettant de produire une cartographie cohérente de l’occupation des sols des surfaces des parcours en zones périméditerranéennes françaises représentées par les régions Occitanie et Provence-Alpes-Côte d’Azur. Quatre différentes sources de données sont utilisées : l’occupation des sols millésime OSO (OSO), le Registre parcellaire graphique (RPG), la BD-Forêt V.2.0 et les données satellites Sentinel 2 L3A. Le RPG de 2019 et la BD-Forêt actualisée en 2018 ont été utilisés comme principale source de données de référence pour l’entraînement des modèles en vue de classifier les objets OSO 2019 de faible F-score, après extraction des variables spectrales, et des indices spectraux et texturaux issus des données Sentinel 2 L3A. Trois différentes tailles de données de référence ont été constituées. Ensuite 6 modèles ont été entraînés en utilisant l’algorithme Random Forest (RF) dont 3 modèles à partir des 3 jeux de données, intégrant toutes les variables extraites (98) et 3 modèles en reprenant uniquement les variables importantes (30) définies par le RF. Les résultats montrent des précisions globales stables pour tous les jeux de données utilisés et produisent une meilleure discrimination de 3 classes sur 4 : les pelouses, les cultures pérennes et les forêts. Les landes ne sont pas bien discriminées à cause de leur forte hétérogénéité spatiale. Numéro de notice : A2022-324 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.3166/rig.2021.00112 Date de publication en ligne : 20/04/2022 En ligne : https://doi.org/10.3166/rig.2021.00112 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100479
in Revue internationale de géomatique > vol 30 n° 3-4 (juillet - décembre 2020) . - pp 245 - 277[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 047-2020021 SL Revue Centre de documentation Revues en salle Disponible Complete and accurate data correction for seamless mosaicking of airborne hyperspectral images: A case study at a mining site in Inner Mongolia, China / Kun Tan in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)
[article]
Titre : Complete and accurate data correction for seamless mosaicking of airborne hyperspectral images: A case study at a mining site in Inner Mongolia, China Type de document : Article/Communication Auteurs : Kun Tan, Auteur ; Chao Niu, Auteur ; Xiuping Jia, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1 - 15 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] atténuation
[Termes IGN] correction atmosphérique
[Termes IGN] distorsion du signal
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] image hyperspectrale
[Termes IGN] mine
[Termes IGN] Mongolie intérieure (Chine)
[Termes IGN] mosaïquage d'images
[Termes IGN] radiance
[Termes IGN] rayonnement infrarouge
[Termes IGN] réflectance de surface
[Termes IGN] Short Waves InfraRed
[Termes IGN] spectroradiométrie
[Termes IGN] surveillance écologiqueRésumé : (auteur) Airborne hyperspectral remote sensing is an important application in the ecological monitoring of the environment in mining areas, and accurate preprocessing of the original images is the key to quantitative information retrieval. The original image data need radiation correction to acquire surface reflectance data. Due to the impact of the field angle, incidental radiance, and the bidirectional reflectance distribution function (BRDF), there can be a brightness gradient between adjacent strips, which leads to radiance difference and obvious chromatic aberration of the mosaicked images. We propose a novel data correction method for seamless mosaicking of airborne hyperspectral images. Firstly, visible and near-infrared (VNIR) and shortwave infrared (SWIR) sensors are calibrated in the laboratory, and the radiation calibration model of the sensor is established by an integrating-sphere system. A correction function is then established by combining the BRDF effect and the radiation attenuation coefficients. We also normalize the exposure time, sun altitude angle, and sensor altitude angle according to the flight strip. The results showed that this method is able to eliminate the signal distortion, allowing the seamless mosaicking of 37 strip images which were taken in different date and conditions in the study area. After the atmospheric correction of the imagery was completed, the accuracy of the preprocessing results was evaluated by field-measured ASD spectroradiometer data. The coefficient of determination R2 of the results for the reflectance was greater than 0.9. The experiments show that the proposed method has a good performance in radiation accuracy, and can provide high-quality hyperspectral data for the follow-up application of the ecological monitoring of a mining area. Numéro de notice : A2020-465 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.04.022 Date de publication en ligne : 16/05/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.04.022 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95092
in ISPRS Journal of photogrammetry and remote sensing > vol 165 (July 2020) . - pp 1 - 15[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020071 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020073 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020072 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches / S.M. Hamylton in International journal of applied Earth observation and geoinformation, vol 89 (July 2020)
[article]
Titre : Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches Type de document : Article/Communication Auteurs : S.M. Hamylton, Auteur ; R.H. Morris, Auteur ; R.C. Carvalho, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 102085 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] carte de la végétation
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification pixellaire
[Termes IGN] détection de changement
[Termes IGN] données de terrain
[Termes IGN] image captée par drone
[Termes IGN] Nouvelle-Galles du Sud
[Termes IGN] pesticide
[Termes IGN] réserve naturelle
[Termes IGN] série temporelle
[Termes IGN] surveillance de la végétationRésumé : (auteur) We evaluate three approaches to mapping vegetation using images collected by an unmanned aerial vehicle (UAV) to monitor rehabilitation activities in the Five Islands Nature Reserve, Wollongong (Australia). Between April 2017 and July 2018, four aerial surveys of Big Island were undertaken to map changes to island vegetation following helicopter herbicide sprays to eradicate weeds, including the creeper Coastal Morning Glory (Ipomoea cairica) and Kikuyu Grass (Cenchrus clandestinus). The spraying was followed by a large scale planting campaign to introduce native plants, such as tussocks of Spiny-headed Mat-rush (Lomandra longifolia). Three approaches to mapping vegetation were evaluated, including: (i) a pixel-based image classification algorithm applied to the composite spectral wavebands of the images collected, (ii) manual digitisation of vegetation directly from images based on visual interpretation, and (iii) the application of a machine learning algorithm, LeNet, based on a deep learning convolutional neural network (CNN) for detecting planted Lomandra tussocks. The uncertainty of each approach was assessed via comparison against an independently collected field dataset. Each of the vegetation mapping approaches had a comparable accuracy; for a selected weed management and planting area, the overall accuracies were 82 %, 91 % and 85 % respectively for the pixel based image classification, the visual interpretation / digitisation and the CNN machine learning algorithm. At the scale of the whole island, statistically significant differences in the performance of the three approaches to mapping Lomandra plants were detected via ANOVA. The manual digitisation took a longer time to perform than others. The three approaches resulted in markedly different vegetation maps characterised by different digital data formats, which offered fundamentally different types of information on vegetation character. We draw attention to the need to consider how different digital map products will be used for vegetation management (e.g. monitoring the health individual species or a broader profile of the community). Where individual plants are to be monitored over time, a feature-based approach that represents plants as vector points is appropriate. The CNN approach emerged as a promising technique in this regard as it leveraged spatial information from the UAV images within the architecture of the learning framework by enforcing a local connectivity pattern between neurons of adjacent layers to incorporate the spatial relationships between features that comprised the shape of the Lomandra tussocks detected. Numéro de notice : A2020-716 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2020.102085 Date de publication en ligne : 03/03/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102085 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96287
in International journal of applied Earth observation and geoinformation > vol 89 (July 2020) . - n° 102085[article]Long time-series remote sensing analysis of the periodic cycle evolution of the inlets and ebb-tidal delta of Xincun Lagoon, Hainan Island, China / Huaguo Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)PermalinkMapping the condition of macadamia tree crops using multi-spectral UAV and WorldView-3 imagery / Kasper Johansen in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)PermalinkPath length correction for improving leaf area index measurements over sloping terrains: A deep analysis through computer simulation / Gaofei Yin in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)PermalinkA simple distributed water balance model for an urbanized river basin using remote sensing and GIS techniques / Olutoyin Adeola Fashae in Geocarto international, vol 35 n° 9 ([01/07/2020])PermalinkUsing spectral indices to estimate water content and GPP in sphagnum moss and other peatland vegetation / Kirsten J. Lees in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)PermalinkUsing machine learning to synthesize spatiotemporal data for modelling DBH-height and DBH-height-age relationships in boreal forests / Jiaxin Chen in Forest ecology and management, Vol 466 (15 June 2020)PermalinkAn integrated approach for detection and prediction of greening situation in a typical desert area in China and its human and climatic factors analysis / Lei Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)PermalinkAqueous alteration mapping in Rishabdev ultramafic complex using imaging spectroscopy / Hrishikesh Kumar in International journal of applied Earth observation and geoinformation, vol 88 (June 2020)PermalinkCoastline change modelling induced by climate change using geospatial techniques in Togo (West Africa) / Yawo Konko in Advances in Remote Sensing, vol 9 n° 2 (June 2020)PermalinkCounting of grapevine berries in images via semantic segmentation using convolutional neural networks / Laura Zabawa in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)Permalink