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Generating 2m fine-scale urban tree cover product over 34 metropolises in China based on deep context-aware sub-pixel mapping network / Da He in International journal of applied Earth observation and geoinformation, vol 106 (February 2022)
[article]
Titre : Generating 2m fine-scale urban tree cover product over 34 metropolises in China based on deep context-aware sub-pixel mapping network Type de document : Article/Communication Auteurs : Da He, Auteur ; Qian Shi, Auteur ; Xiaoping Liu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102667 Note générale : bibliography Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse infrapixellaire
[Termes IGN] apprentissage profond
[Termes IGN] arbre hors forêt
[Termes IGN] arbre urbain
[Termes IGN] base de données localisées
[Termes IGN] Chine
[Termes IGN] image Sentinel-MSI
[Termes IGN] métropole
[Termes IGN] Pékin (Chine)
[Termes IGN] prise en compte du contexte
[Termes IGN] Wuhan (Chine)Résumé : (auteur) Contrast to the global forest, few trees live in cities but contribute significantly to urban environment and human health. However, the classical satellite-derived land cover/forest cover products with limited resolution are not fine enough for the identification of urban tree, which is usually appeared in small size and intersected with infrastructure. To relieve the dilemma, this study developed an urban tree specific sub-pixel mapping (SPM) architecture with deep learning approach, which aimed to generate 2m fine-scale urban tree cover product from 10 m Sentinel-2 images for large-scale area of 34 metropolises in China. The proposed approach has remarkable reconstruction ability for delineating the contextual characteristic of the urban tree patterns, and reliable generalization ability to large-scale area. In addition, this study creates a large-volume urban tree cover dataset (UTCD) with 0.13 billion urban tree samples at 2 m resolution, which fills the deficiency of standard dataset in urban tree cover research field. Quantitative analysis of our products was conducted on two typical study sites of Beijing and Wuhan. The results show that our products recover averagely more than 58.72% of urban tree covers that have been underestimated in the existing land cover/forest cover products, and outperforms the state-of-the-art approach both visually and quantitatively, by averagely 11.31% improvement in overall accuracy. From our annual products during 2016–2020, we found an evolution characteristic of urban tree cover: it is more stable in developed cities like Beijing, while more fluctuated in developing cities like Wuhan, and the alteration are usually concentrated at the outer-ring of downtown, which may be caused by the municipal planning and the land development of real estate industry. Numéro de notice : A2022-073 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2021.102667 En ligne : https://doi.org/10.1016/j.jag.2021.102667 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99438
in International journal of applied Earth observation and geoinformation > vol 106 (February 2022) . - n° 102667[article]Landsat-based monitoring of southern pine beetle infestation severity and severity change in a temperate mixed forest / Ran Meng in Remote sensing of environment, vol 269 (February 2022)
[article]
Titre : Landsat-based monitoring of southern pine beetle infestation severity and severity change in a temperate mixed forest Type de document : Article/Communication Auteurs : Ran Meng, Auteur ; Renjie Gao, Auteur ; Feng Zhao, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 112847 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse spatiale
[Termes IGN] dépérissement
[Termes IGN] forêt tempérée
[Termes IGN] image Landsat-8
[Termes IGN] insecte nuisible
[Termes IGN] mortalité
[Termes IGN] peuplement mélangé
[Termes IGN] Scolytinae
[Termes IGN] signature spectrale
[Termes IGN] surveillance forestière
[Termes IGN] xylophageRésumé : (auteur) The recent northward expansion of Southern Pine Beetle (SPB) outbreaks associated with warming winters has caused extensive tree mortality in temperate pine forests, significantly affecting forest dynamics, structure, and functioning. Spatially-explicit early warning and detection of SPB-induced tree mortality is critical for timely and sustainable forest management practices. The unique contributions of remote sensing technologies to mapping the location, extent, and severity of beetle outbreaks, as well as assisting in analyzing the potential drivers for outbreak predictions, have been well recognized. However, little is known about the performance of moderate resolution satellite multispectral imagery for early warning and detection of SPB-induced tree mortality. Thus, we conducted this study, as the first attempt, to capture the spatial-temporal patterns of SPB infestation severity at the regional scale and to understand the underlying environmental drivers in a spatially-explicit manner. First, we explored the spectral signatures of SPB-killed trees based on 30-m plot measurements and Landsat-8 imagery. Then, to improve detection accuracy for areas with low-moderate SPB infestation severity, we added spectral-temporal anomaly information in the form of a linear trend of the spectral index trajectory to a previously developed approach. The best overall accuracy increased from 84.7% to 90.1% and the best Macro F1 value increased from 0.832 to 0.900. Next, we compared the performances of spectral indices in mapping SPB infestation severity (i.e., % red stage within the 30-m grid cell). The results showed that the combination of Normalized Difference Moisture Index and Tasseled Cap Greenness had the best performance for mapping SPB infestation severity (2016: R2 = 0.754; RSME = 15.7; 2017: R2 = 0.787; RSME = 12.4). Finally, we found that climatic and landscape variables can explain the detected patterns of SPB infestation from 2014 to 2017 in our study area (R2 = 0.751; RSME = 9.67), providing valuable insights on possible predictors for early warning of SPB infestation. Specifically, in our study area, winter dew point temperature was found to be one of the most important predictors, followed by SPB infestation locations in the previous year, canopy cover of host species, elevation, and slope. In the context of continued global warming, our study not only provides a novel framework for efficient, spatially-explicit, and quantitative measurements of forest damage induced by SPB infestation over large scales, but also uncovers opportunities to predict future SPB outbreaks and take precautions against it. Numéro de notice : A2022-096 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112847 Date de publication en ligne : 15/12/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112847 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99538
in Remote sensing of environment > vol 269 (February 2022) . - n° 112847[article]Mapping burn severity in the western Italian Alps through phenologically coherent reflectance composites derived from Sentinel-2 imagery / Donato Morresi in Remote sensing of environment, vol 269 (February 2022)
[article]
Titre : Mapping burn severity in the western Italian Alps through phenologically coherent reflectance composites derived from Sentinel-2 imagery Type de document : Article/Communication Auteurs : Donato Morresi, Auteur ; Raffaella Marzano, Auteur ; Emanuele Lingua, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 112800 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte de la végétation
[Termes IGN] cartographie des risques
[Termes IGN] détection de changement
[Termes IGN] forêt alpestre
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] incendie de forêt
[Termes IGN] phénologie
[Termes IGN] Piémont (Italie)
[Termes IGN] réflectance spectrale
[Termes IGN] risque naturel
[Termes IGN] variation saisonnière
[Termes IGN] zone sinistréeRésumé : (auteur) Deriving burn severity from multispectral satellite data is a widely adopted approach to infer the degree of environmental change caused by fire. Burn severity maps obtained by thresholding bi-temporal indices based on pre- and post-fire Normalized Burn Ratio (NBR) can vary substantially depending on temporal constraints such as matched acquisition and optimal seasonal timing. Satisfying temporal requirements is crucial to effectively disentangle fire and non-fire induced spectral changes and can be particularly challenging when only a few cloud-free images are available. Our study focuses on 10 wildfires that occurred in mountainous areas of the Piedmont Region (Italy) during autumn 2017 following a severe and prolonged drought period. Our objectives were to: (i) generate reflectance composites using Sentinel-2 imagery that were optimised for seasonal timing by embedding spatial patterns of long-term land surface phenology (LSP); (ii) produce and validate burn severity maps based on the modelled relationship between bi-temporal indices and field data; (iii) compare burn severity maps obtained using either a pair of cloud-free Sentinel-2 images, i.e. paired images, or reflectance composites. We proposed a pixel-based compositing algorithm coupling the weighted geometric median and thematic spatial information, e.g. long-term LSP metrics derived from the MODIS Collection 6 Land Cover Dynamics Product, to rank all the clear observations available in the growing season. Composite Burn Index data and bi-temporal indices exhibited a strong nonlinear relationship (R2 > 0.85) using paired images or reflectance composites. Burn severity maps attained overall classification accuracy ranging from 76.9% to 83.7% (Kappa between 0.61 and 0.72) and the Relative differenced NBR (RdNBR) achieved the best results compared to other bi-temporal indices (differenced NBR and Relativized Burn Ratio). Improvements in overall classification accuracy offered by the calibration of bi-temporal indices with the dNBR offset were limited to burn severity maps derived from paired images. Reflectance composites provided the highest overall classification accuracy and differences with paired images were significant using uncalibrated bi-temporal indices (4.4% to 5.2%) while they decreased (2.8% to 3.2%) when we calibrated bi-temporal indices derived from paired images. The extent of the high severity category increased by ~19% in burn severity maps derived from reflectance composites (uncalibrated RdNBR) compared to those from paired images (calibrated RdNBR). The reduced contrast between healthy and burnt conditions associated with suboptimal seasonal timing caused an underestimation of burnt areas. By embedding spatial patterns of long-term LSP metrics, our approach provided consistent reflectance composites targeted at a specific phenological stage and minimising non-fire induced inter-annual changes. Being independent from the multispectral dataset employed, the proposed pixel-based compositing approach offers new opportunities for operational change detection applications in geographic areas characterised by persistent cloud cover. Numéro de notice : A2022-095 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112800 Date de publication en ligne : 22/11/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112800 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99534
in Remote sensing of environment > vol 269 (February 2022) . - n° 112800[article]Mapping global flying aircraft activities using Landsat 8 and cloud computing / Fen Zhao in ISPRS Journal of photogrammetry and remote sensing, vol 184 (February 2022)
[article]
Titre : Mapping global flying aircraft activities using Landsat 8 and cloud computing Type de document : Article/Communication Auteurs : Fen Zhao, Auteur ; Lang Xia, Auteur ; Arve Kylling, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 19 - 30 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aéronef
[Termes IGN] analyse spatio-temporelle
[Termes IGN] aviation civile
[Termes IGN] carte thématique
[Termes IGN] climat
[Termes IGN] détection d'objet
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-OLI
[Termes IGN] informatique en nuage
[Termes IGN] navigation aérienne
[Termes IGN] trafic aérienRésumé : (auteur) Satellite-based remote sensing might provide a potential way for monitoring the global flight activities and their environment impacts, while the remote sensing community pays less attention on it. In this study, we presented a flying aircraft detection algorithm which effectively handles the noise on Landsat 8 OLI cirrus band caused by energetic particles in the South Atlantic Anomaly region, and a new framework based on cloud infrastructure was proposed to map global flying aircraft activities from 2013 to 2020 using Landsat 8 Operational Land Imager (OLI) data. Validation was performed for 254 scenes recorded for various cloudy and surface conditions and vapor contents. The overall percentages of false alarms and omissions for these validation images were 5.37% and 7.80%, respectively. Limited to the resolution of Landsat data, cloud, the size and flight altitude of the aircraft, 42.99% flying aircraft were undetected compared with the FlightRadar24. Instead of using the Google Earth Engine, we employed more flexible cloud computing techniques, Google Cloud Storage and Google Calculation Engine, to construct our framework for the larger volume data. A total of 1.94 million Landsat images were analyzed to obtain the activities maps, and the results showed that globally flying aircraft increased by 25.85% from 2014 to 2019 (the year 2013 was excluded for the low coverage of Landsat scenes), with an annual rate of 4.31%. In 2020, flying aircraft were reduced by 40% compared with 2019 due to the influence of COVID-19 and traveling restrictions, and Europe was the most severely affected by COVID-19, with an 84.59% decline of flying aircraft in April 2020. This study provides a unique long-term supplement to monitor aviation activities and their climate impact. Numéro de notice : A2022-090 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.12.003 Date de publication en ligne : 15/12/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.12.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99506
in ISPRS Journal of photogrammetry and remote sensing > vol 184 (February 2022) . - pp 19 - 30[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2022021 SL Revue Centre de documentation Revues en salle Disponible 081-2022023 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2022022 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Multi-method monitoring of rockfall activity along the classic route up Mont Blanc (4809 m a.s.l.) to encourage adaptation by mountaineers / Jacques Mourey in Natural Hazards and Earth System Sciences, vol 22 n° 2 (February 2022)
[article]
Titre : Multi-method monitoring of rockfall activity along the classic route up Mont Blanc (4809 m a.s.l.) to encourage adaptation by mountaineers Type de document : Article/Communication Auteurs : Jacques Mourey, Auteur ; Pascal Lacroix, Auteur ; Pierre-Allain Duvillard, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 445 - 460 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] capteur actif
[Termes IGN] capteur non-imageur
[Termes IGN] carte thématique
[Termes IGN] détection de changement
[Termes IGN] éboulement
[Termes IGN] modèle numérique de terrain
[Termes IGN] Mont-Blanc, massif du
[Termes IGN] onde sismique
[Termes IGN] pergélisol
[Termes IGN] prévention des risques
[Termes IGN] risque naturel
[Termes IGN] saison
[Termes IGN] sismologie
[Termes IGN] surveillance géologique
[Termes IGN] température de l'airRésumé : (auteur) There are on average 35 fatal mountaineering accidents per summer in France. On average, since 1990, 3.7 of them have occurred every summer in the Grand Couloir du Goûter, on the classic route up Mont Blanc (4809 m a.s.l.). Rockfall is one of the main factors that explain this high accident rate and contribute to making it one of the most accident-prone areas in the Alps for mountaineers. In this particular context, the objective of this study is to document the rockfall activity and its triggering factors in the Grand Couloir du Goûter in order to disseminate the results to mountaineers and favour their adaptation to the local rockfall hazard. Using a multi-method monitoring system (five seismic sensors, an automatic digital camera, three rock subsurface temperature sensors, a traffic sensor, a high-resolution topographical survey, two weather stations and a rain gauge), we acquired a continuous database on rockfalls during a period of 68 d in 2019 and some of their potential triggering factors (precipitation, ground and air temperatures, snow cover, frequentation by climbers). At the seasonal scale, our results confirm previous studies showing that rockfalls are most frequent during the snowmelt period in permafrost-affected rockwalls. Furthermore, the unprecedented time precision and completeness of our rockfall database at high elevation thanks to seismic sensors allowed us to investigate the factors triggering rockfalls. We found a clear correlation between rockfall frequency and air temperature, with a 2 h delay between peak air temperature and peak rockfall activity. A small number of rockfalls seem to be triggered by mountaineers. Our data set shows that climbers are not aware of the variations in rockfall frequency and/or cannot/will not adapt their behaviour to this hazard. These results should help to define an adaptation strategy for climbers. Therefore, we disseminated our results within the mountaineering community thanks to the full integration of our results into the management of the route by local actors. Knowledge built during this experiment has already been used for the definition and implementation of management measures for the attendance in summer 2020. Numéro de notice : A2022-181 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article DOI : 10.5194/nhess-22-445-2022 En ligne : https://doi.org/10.5194/nhess-22-445-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99859
in Natural Hazards and Earth System Sciences > vol 22 n° 2 (February 2022) . - pp 445 - 460[article]Automatic extraction of damaged houses by earthquake based on improved YOLOv5: A case study in Yangbi / Yafei Jing in Remote sensing, vol 14 n° 2 (January-2 2022)PermalinkMulti-temporal remote sensing data to monitor terrestrial ecosystem responses to climate variations in Ghana / Ram Avtar in Geocarto international, vol 37 n° 2 ([15/01/2022])PermalinkSoil erosion estimation of Bhandara region of Maharashtra, India, by integrated use of RUSLE, remote sensing, and GIS / Sumedh R. Kashiwar in Natural Hazards, vol 110 n° 2 (January 2022)PermalinkUse of remotely sensed data to estimate tree species diversity as an indicator of biodiversity in Blouberg Nature Reserve, South Africa / Mangana Rampheri in Geocarto international, vol 37 n° 2 ([15/01/2022])PermalinkVariations of urban NO2 pollution during the COVID-19 outbreak and post-epidemic era in China: A synthesis of remote sensing and In situ measurements / Chunhui Zhao in Remote sensing, vol 14 n° 2 (January-2 2022)PermalinkAdaptation of the standardized vegetation optical depth index for satellite-based soil moisture / Juliette Raabe (2022)PermalinkAn assessment of forest loss and its drivers in protected areas on the Copperbelt province of Zambia: 1972–2016 / Darius Phiri in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkApport de la télédétection et des variables auxiliaires dans l'étude de l'évolution des périodes de sécheresse / Nesrine Farhani (2022)PermalinkCartographie dynamique de la topographie de l'océan de surface par assimilation de données altimétriques / Florian Le Guillou (2022)PermalinkCharacteristics of taiga and tundra snowpack in development and validation of remote sensing of snow / Henna-Reetta Hannula (2022)PermalinkPermalinkDetection and biomass estimation of phaeocystis globosa blooms off Southern China from UAV-based hyperspectral measurements / Xue Li in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)PermalinkDétection des prairies de fauche et estimation des périodes de fauche par télédétection / Emma Seneschal (2022)PermalinkEstimating aboveground biomass in dense Hyrcanian forests by the use of Sentinel-2 data / Fardin Moradi in Forests, vol 13 n° 1 (January 2022)PermalinkÉvolution rétrospective et prospective d’un massif dunaire par imagerie multispectrale et LiDAR / Iris Jeuffrard (2022)PermalinkGlobal and climate challenges, graph-based data analysis for multisource information extraction / Morgane Batelier (2022)PermalinkGlobal glacier mass change by spatiotemporal analysis of digital elevation models / Romain Hugonnet (2022)PermalinkHigh-resolution canopy height map in the Landes forest (France) based on GEDI, Sentinel-1, and Sentinel-2 data with a deep learning approach / Martin Schwartz (2022)PermalinkHistorical shoreline analysis and field monitoring at Ennore coastal stretch along the Southeast coast of India / M. Dhananjayan in Marine geodesy, vol 45 n° 1 (January 2022)PermalinkInvestigating the role of wind disturbance in tropical forests through a forest dynamics model and satellite observations / E-Ping Rau (2022)PermalinkLatent heat flux variability and response to drought stress of black poplar: A multi-platform multi-sensor remote and proximal sensing approach to relieve the data scarcity bottleneck / Flavia Tauro in Remote sensing of environment, vol 268 (January 2022)PermalinkMapping burned areas and land-uses in Kangaroo Island using an object-based image classification framework and Landsat 8 Imagery from Google Earth Engine / Jiyu Liu in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkModélisation du lien entre éruptions et glissements de flancs au Piton de la Fournaise / Quentin Dumont (2022)PermalinkMonitoring forest-savanna dynamics in the Guineo-Congolian transition area of the centre region of Cameroon / Le Bienfaiteur Sagang Takougoum (2022)PermalinkMonitoring grassland dynamics by exploiting multi-modal satellite image time series / Anatol Garioud (2022)PermalinkPotentialité de la télédétection thermique pour la modélisation climatique en milieu viticole / Gwenaël Morin (2022)PermalinkPreparation of the VENµS satellite data over Israel for the input into the GRASP data treatment algorithm / Maeve Blarel (2022)PermalinkPermalinkPermalinkPermalinkSimulation of the meltwater under different climate change scenarios in a poorly gauged snow and glacier-fed Chitral River catchment (Hindukush region) / Huma Hayat in Geocarto international, vol 37 n° 1 ([01/01/2022])PermalinkPermalinkPermalinkPermalinkPermalinkEarly detection of spruce vitality loss with hyperspectral data: Results of an experimental study in Bavaria, Germany / Kathrin Einzmann in Remote sensing of environment, vol 266 (December 2021)PermalinkMulti-model estimation of forest canopy closure by using red edge bands based on Sentinel-2 images / Yiying Hua in Forests, vol 12 n° 12 (December 2021)PermalinkNational scale mapping of larch plantations for Wales using the Sentinel-2 data archive / Suvarna M. Punalekar in Forest ecology and management, vol 501 (December-1 2021)PermalinkSnow cover change assessment in the upper Bhagirathi basin using an enhanced cloud removal algorithm / Mritunjay Kumar Singh in Geocarto international, vol 36 n° 20 ([01/12/2021])PermalinkSpatial variability of suspended sediments in San Francisco Bay, California / Niky C. Taylor in Remote sensing, vol 13 n° 22 (November-2 2021)PermalinkThe spatiotemporal implications of urbanization for urban heat islands in Beijing: A predictive approach based on CA–Markov modeling (2004–2050) / Muhammad Amir Siddique in Remote sensing, vol 13 n° 22 (November-2 2021)PermalinkAbove-ground biomass change estimation using national forest inventory data with Sentinel-2 and Landsat / Stefano Puliti in Remote sensing of environment, vol 265 (November 2021)PermalinkEfficient measurement of large-scale decadal shoreline change with increased accuracy in tide-dominated coastal environments with Google Earth Engine / Yongjing Mao in ISPRS Journal of photogrammetry and remote sensing, Vol 181 (November 2021)PermalinkLand subsidence in Beijing’s sub-administrative center and its relationship with urban expansion inferred from Sentinel-1/2 observations / Jin Cao in Canadian journal of remote sensing, vol 47 n° 6 ([01/11/2021])PermalinkA novel cotton mapping index combining Sentinel-1 SAR and Sentinel-2 multispectral imagery / Lan Xun in ISPRS Journal of photogrammetry and remote sensing, Vol 181 (November 2021)PermalinkSeven decades of coastal change at Barter Island, Alaska: Exploring the importance of waves and temperature on erosion of coastal permafrost bluffs / Ann E. Gibbs in Remote sensing, vol 13 n° 21 (November-1 2021)PermalinkTidal flood area mapping in the face of climate change scenarios: case study in a tropical estuary in the Brazilian semi-arid region / Paulo Victor N. Araújo in Natural Hazards and Earth System Sciences, vol 21 n° 11 (November 2021)PermalinkDétection des forêts dégradées en Guinée à partir des images satellites Sentinel-2 : évaluation de l'apport potentiel des nouveaux capteurs satellitaires optiques et radars / An Vo Quang in Blog de la RFPT, sans n° ([11/10/2021])PermalinkBi- and three-dimensional urban change detection using sentinel-1 SAR temporal series / Meiqin Che in Geoinformatica, vol 25 n° 4 (October 2021)PermalinkDeep-learning-based burned area mapping using the synergy of Sentinel-1&2 data / Qi Zhang in Remote sensing of environment, vol 264 (October 2021)PermalinkDisaster intensity-based selection of training samples for remote sensing building damage classification / Luis Moya in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)PermalinkEarly detection of pine wilt disease using deep learning algorithms and UAV-based multispectral imagery / Run Yu in Forest ecology and management, vol 497 (October-1 2021)PermalinkField scale wheat LAI retrieval from multispectral Sentinel 2A-MSI and LandSat 8-OLI imagery: effect of atmospheric correction, image resolutions and inversion techniques / Rajkumar Dhakar in Geocarto international, vol 36 n° 18 ([01/10/2021])PermalinkImproving the accuracy of spring phenology detection by optimally smoothing satellite vegetation index time series based on local cloud frequency / Jiaqi Tian in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)PermalinkPhenology-based delineation of irrigated and rain-fed paddy fields with Sentinel-2 imagery in Google Earth Engine / Daniel Marc G. dela Torre in Geo-spatial Information Science, vol 24 n° 4 (October 2021)PermalinkRecognition of crevasses with high-resolution digital elevation models: Application of geomorphometric modeling and texture analysis / Olga T. Ishalina in Transactions in GIS, vol 25 n° 5 (October 2021)PermalinkUncertainties 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)PermalinkRecurrent-based regression of Sentinel time series for continuous vegetation monitoring / Anatol Garioud in Remote sensing of environment, vol 263 (15 September 2021)PermalinkDetection of aspen in conifer-dominated boreal forests with seasonal multispectral drone image point clouds / Alwin A. Hardenbol in Silva fennica, vol 55 n° 4 (September 2021)PermalinkEstimating regional soil moisture with synergistic use of AMSR2 and MODIS images / Majid Rahimzadegan in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)PermalinkGeoglam, l'agriculture par satellite / Laurent Polidori in Géomètre, n° 2194 (septembre 2021)PermalinkThe real potential of current passive satellite data to map aboveground biomass in tropical forests / Nidhi Jha in Remote sensing in ecology and conservation, vol 7 n° 3 (September 2021)PermalinkUsing electrical resistivity tomography to detect wetwood and estimate moisture content in silver fir (Abies alba Mill.) / Ludovic Martin in Annals of Forest Science, vol 78 n° 3 (September 2021)PermalinkMonitoring forest disturbance using time-series MODIS NDVI in Michoacán, Mexico / Yao Gao in Geocarto international, vol 36 n° 15 ([15/08/2021])PermalinkAutomated tree-crown and height detection in a young forest plantation using mask region-based convolutional neural network (Mask R-CNN) / Zhenbang Hao in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)PermalinkImproving urban land cover classification with combined use of Sentinel-2 and Sentinel-1 imagery / Bin Hu in ISPRS International journal of geo-information, vol 10 n° 8 (August 2021)PermalinkMapping essential urban land use categories with open big data: Results for five metropolitan areas in the United States of America / Bin Chen in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)PermalinkRandom forests with bagging and genetic algorithms coupled with least trimmed squares regression for soil moisture deficit using SMOS satellite soil moisture / Pashrant K. Srivastava in ISPRS International journal of geo-information, vol 10 n° 8 (August 2021)PermalinkRemote sensing method for extracting topographic information on tidal flats using spatial distribution features / Yang Lijun in Marine geodesy, vol 44 n° 5 (September 2021)PermalinkSpatiotemporal analysis of urban heat island intensification in the city of Minneapolis-St. Paul and Chicago metropolitan areas using Landsat data from 1984 to 2016 / Mbongowo J. Mbuh in Geocarto international, vol 36 n° 14 ([01/08/2021])PermalinkAn integrated methodology for surface soil moisture estimating using remote sensing data approach / Rida Khellouk in Geocarto international, vol 36 n° 13 ([15/07/2021])PermalinkComparison of classification methods for urban green space extraction using very high resolution worldview-3 imagery / S. Vigneshwaran in Geocarto international, vol 36 n° 13 ([15/07/2021])PermalinkAnomalous variations of air temperature prior to earthquakes / Irfan Mahmood in Geocarto international, vol 36 n° 12 ([01/07/2021])PermalinkDetecting high-temperature anomalies from Sentinel-2 MSI images / Yongxue Liu in ISPRS Journal of photogrammetry and remote sensing, vol 177 (July 2021)PermalinkEvaluation of sum-NDVI values to estimate wheat grain yields using multi-temporal Landsat OLI data / Asadollah Mirasi in Geocarto international, vol 36 n° 12 ([01/07/2021])PermalinkFeux de forêts et technologies spatiales / Laurent Polidori in Géomètre, n° 2193 (juillet-août 2021)PermalinkFlood depth mapping in street photos with image processing and deep neural networks / Bahareh Alizadeh Kharazi in Computers, Environment and Urban Systems, vol 88 (July 2021)PermalinkFluvial gravel bar mapping with spectral signal mixture analysis / Liza Stančič in European journal of remote sensing, vol 54 sup 1 (2021)PermalinkMapping sandy land using the new sand differential emissivity index from thermal infrared emissivity data / Shanshan Chen in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)PermalinkMulti-scale coal fire detection based on an improved active contour model from Landsat-8 satellite and UAV images / Yanyan Gao in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)PermalinkSemantic unsupervised change detection of natural land cover with multitemporal object-based analysis on SAR images / Donato Amitrano in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)PermalinkUsing machine learning to map Western Australian landscapes for mineral exploration / Thomas Albrecht in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)PermalinkCoral habitat mapping: a comparison between maximum likelihood, Bayesian and Dempster–Shafer classifiers / Mohammad Shawkat Hossain in Geocarto international, vol 36 n° 11 ([15/06/2021])PermalinkFast unsupervised multi-scale characterization of urban landscapes based on Earth observation data / Claire Teillet in Remote sensing, vol 13 n° 12 (June-2 2021)PermalinkCloud-native seascape mapping of Mozambique’s Quirimbas National Park with Sentinel-2 / Dimitris Poursanidis in Remote sensing in ecology and conservation, vol 7 n° 2 (June 2021)PermalinkDiscovery of new colonies by Sentinel2 reveals good and bad news for emperor penguins / Peter T. Fretwell in Remote sensing in ecology and conservation, vol 7 n° 2 (June 2021)PermalinkEvaluating 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)PermalinkFractional 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)PermalinkIdentifying the effects of chronic saltwater intrusion in coastal floodplain swamps using remote sensing / Elliott White Jr in Remote sensing of environment, vol 258 (June 2021)PermalinkMapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine / Tongxi Hu in ISPRS Journal of photogrammetry and remote sensing, vol 176 (June 2021)PermalinkRapid ecosystem change at the southern limit of the Canadian Arctic, Torngat Mountains National Park / Emma L. Davis in Remote sensing, vol 13 n° 11 (June-1 2021)PermalinkReference evapotranspiration (ETo) methods implemented as ArcMap models with remote-sensed and ground-based inputs, examined along with MODIS ET, for Peloponnese, Greece / Stavroula Dimitriadou in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)PermalinkThe use of land cover indices for rapid surface urban heat island detection from multi-temporal Landsat imageries / Nagihan Aslan in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)PermalinkUncertainty management for robust probabilistic change detection from multi-temporal Geoeye-1 imagery / Mahmoud Salah in Applied geomatics, vol 13 n° 2 (June 2021)PermalinkAnalysing the impact of climate change on hydrological ecosystem services in Laguna del Sauce (Uruguay) using the SWAT model and remote sensing data / Celina Aznarez in Remote sensing, vol 13 n°10 (May-2 2021)Permalink