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Télédétection aérospatiale Télédétection par satellite Télédétection satellitaire Télédétection spatiale Appareils enregistreurs >> Agriculture de précision Capteurs (technologie) Photogrammétrie aérienne Photographie aérienne >>Terme(s) spécifique(s) : Télédétection en sciences de la Terre Cartographie radar Traitement d'images -- Techniques numériques Images de télédétection Radar à antenne synthétique Radar en sciences de la Terre Reconnaissance aérienne Satellites artificiels en télédétection Satellites de télédétection des ressources terrestres SPOT (satellites de télédétection) Surveillance électronique Télédétection hyperfréquence Télémesure spatiale Thermographie Equiv. LCSH : Remote sensing Domaine(s) : 500; 600 |
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Quantification of the adjacency effect on measurements in the thermal infrared region / Xiaopo Zheng in IEEE Transactions on geoscience and remote sensing, vol 57 n° 12 (December 2019)
[article]
Titre : Quantification of the adjacency effect on measurements in the thermal infrared region Type de document : Article/Communication Auteurs : Xiaopo Zheng, Auteur ; Zhao-Liang Li, Auteur ; Xia Zhang, Auteur ; Guofei Shang, Auteur Année de publication : 2019 Article en page(s) : pp 9674 - 9687 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Télédétection
[Termes IGN] adjacence
[Termes IGN] exitance spectrale
[Termes IGN] image à haute résolution
[Termes IGN] image thermique
[Termes IGN] modèle de transfert radiatif
[Termes IGN] réflectivité
[Termes IGN] température au solRésumé : (auteur) Sensor-observed energy from adjacent pixels, known as the adjacency effect, influences land surface reflectivity retrieval accuracy in optical remote sensing. As the spatial resolution of thermal infrared (TIR) images increases, the adjacency effect may influence land surface temperature (LST) retrieval accuracy in TIR remote sensing. However, to our knowledge, few studies have focused on quantifying this adjacency effect on TIR measurements. In this study, a forward adjacency effect radiative transfer model (FAERTM) was developed to quantify the adjacency effect on high-spatial-resolution TIR measurements. The model was verified to be in good agreement with moderate resolution atmospheric transmission (MODTRAN) code, with a discrepancy 3 K in some cases. These findings indicate that the adjacency effect should be considered when retrieving LSTs from TIR measurements, at least in some specific conditions. The proposed FAERTM provides a useful model for quantifying and addressing the adjacency effect on TIR measurements Numéro de notice : A2019-600 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2928525 Date de publication en ligne : 06/08/2019 En ligne : http://doi.org/10.1109/TGRS.2019.2928525 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94599
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 12 (December 2019) . - pp 9674 - 9687[article]Spatiotemporal variation in the relationship between boreal forest productivity proxies and climate data / Clémentine Ols in Dendrochronologia, vol 58 (December 2019)
[article]
Titre : Spatiotemporal variation in the relationship between boreal forest productivity proxies and climate data Type de document : Article/Communication Auteurs : Clémentine Ols , Auteur ; Ingvil Kålås, Auteur ; Igor Drobyshev, Auteur ; Lars Söderström, Auteur ; Annika Hofgaard, Auteur Année de publication : 2019 Projets : PREREAL / Ali, Ahmed Adam Article en page(s) : n° 125648 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] croissance des arbres
[Termes IGN] données météorologiques
[Termes IGN] données spatiotemporelles
[Termes IGN] écosystème forestier
[Termes IGN] forêt boréale
[Termes IGN] hauteur des arbres
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] Norvège
[Termes IGN] Pinus sylvestris
[Termes IGN] productivité
[Termes IGN] puits de carbone
[Termes IGN] série temporelle
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) The impacts of climate change on high-latitude forest ecosystems are still uncertain. Divergent forest productivity trends have recently been reported both at the local and regional level challenging the projections of boreal tree growth dynamics. The present study investigated (i) the responses of different forest productivity proxies to monthly climate (temperature and precipitation) through space and time; and (ii) the local coherency between these proxies through time at four high-latitude boreal Scots pine sites (coastal and inland) in Norway. Forest productivity proxies consisted of two proxies representing stem growth dynamics (radial and height growth) and one proxy representing canopy dynamics (cumulative May-to-September Normalized Difference Vegetation Index (NDVI)). Between-proxy and climate-proxy correlations were computed over the 1982–2011 period and over two 15-yr sub-periods. Over the entire period, radial growth significantly correlated with current year July temperature, and height growth and cumulative NDVI significantly correlated with previous and current growing season temperatures. Significant climate responses were quite similar across sites, despite some higher sensitivity to non-growing season climate at inland sites. Significant climate-proxy correlations identified over the entire period were temporarily unstable. Local coherency between proxies was generally insignificant. The spatiotemporal instability in climate-proxy correlations observed for all proxies underlines evolving responses to climate and challenges the modelling of forest productivity. The general lack of local coherency between proxies at our four study sites suggests that forest productivity estimations based on a single proxy should be considered with great caution. The combined use of different forest growth metrics may help circumvent uncertainties in capturing responses of forest productivity to climate variability and improve estimations of carbon sequestration by forest ecosystems. Numéro de notice : A2019-618 Affiliation des auteurs : LIF+Ext (2012-2019) Autre URL associée : vers HAL Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.dendro.2019.125648 Date de publication en ligne : 06/11/2019 En ligne : https://doi.org/10.1016/j.dendro.2019.125648 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95346
in Dendrochronologia > vol 58 (December 2019) . - n° 125648[article]Accurate modelling of canopy traits from seasonal Sentinel-2 imagery based on the vertical distribution of leaf traits / Tawanda W. Gara in ISPRS Journal of photogrammetry and remote sensing, vol 157 (November 2019)
[article]
Titre : Accurate modelling of canopy traits from seasonal Sentinel-2 imagery based on the vertical distribution of leaf traits Type de document : Article/Communication Auteurs : Tawanda W. Gara, Auteur ; Roshanak Darvishzadeh, Auteur ; Andrew K. Skidmore, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 108 - 123 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Bavière (Allemagne)
[Termes IGN] canopée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] écosystème forestier
[Termes IGN] hétérogénéité spatiale
[Termes IGN] image Sentinel-MSI
[Termes IGN] indice foliaire
[Termes IGN] Leaf Mass per Area
[Termes IGN] photosynthèse
[Termes IGN] variation saisonnièreRésumé : (Auteur) Leaf traits at canopy level (hereinafter canopy traits) are conventionally expressed as a product of total canopy leaf area index (LAI) and leaf trait content based on samples collected from the exposed upper canopy. This traditional expression is centered on the theory that absorption of incident photosynthetically active radiation (PAR) follow a bell-shaped function skewed to the upper canopy. However, the validity of this theory has remained untested for a suite of canopy traits in a temperate forest ecosystem across multiple seasons using multispectral imagery. In this study, we examined the effect of canopy traits expression in modelling canopy traits using Sentinel-2 multispectral data across the growing season in Bavaria Forest National Park (BFNP), Germany. To achieve this, we measured leaf mass per area (LMA), chlorophyll (Cab), nitrogen (N) and carbon content and LAI from the exposed upper and shaded lower canopy respectively over three seasons (spring, summer and autumn). Subsequently, we estimated canopy traits using two expressions, i.e. the traditional expression-based on the product of LAI and leaf traits content of samples collected from the sunlit upper canopy (hereinafter top-of-canopy expression) and the weighted expression - established on the proportion between the shaded lower and sunlit upper canopy LAI and their respective leaf traits content. Using a Random Forest machine-learning algorithm, we separately modelled canopy traits estimated from the two expressions using Sentinel-2 spectral bands and vegetation indices. Our results showed that dry matter related canopy traits (LMA, N and carbon) estimated based on the weighted canopy expression yield stronger correlations and higher prediction accuracy (NRMSECV 0.48 µg/cm2) across all seasons. We also developed a generalized model that explained 52.57–67.82% variation in canopy traits across the three seasons. Using the most accurate Random Forest model for each season, we demonstrated the capability of Sentinel-2 data to map seasonal dynamics of canopy traits across the park. Results presented in this study revealed that canopy trait expression can have a profound effect on modelling the accuracy of canopy traits using satellite imagery throughout the growing seasons. These findings have implications on model accuracy when monitoring the dynamics of ecosystem functions, processes and services. Numéro de notice : A2019-493 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.09.005 Date de publication en ligne : 11/09/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.09.005 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93725
in ISPRS Journal of photogrammetry and remote sensing > vol 157 (November 2019) . - pp 108 - 123[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2019111 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019113 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019112 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Deep learning for multi-modal classification of cloud, shadow and land cover scenes in PlanetScope and Sentinel-2 imagery / Yuri Shendryk in ISPRS Journal of photogrammetry and remote sensing, vol 157 (November 2019)
[article]
Titre : Deep learning for multi-modal classification of cloud, shadow and land cover scenes in PlanetScope and Sentinel-2 imagery Type de document : Article/Communication Auteurs : Yuri Shendryk, Auteur ; Yannik Rist, Auteur ; Catherine Ticehurst, Auteur ; Peter Thorburn, Auteur Année de publication : 2019 Article en page(s) : pp 124 - 136 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Amazonie
[Termes IGN] apprentissage profond
[Termes IGN] Australie
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection d'ombre
[Termes IGN] état de l'art
[Termes IGN] image à haute résolution
[Termes IGN] image PlanetScope
[Termes IGN] image Sentinel-MSI
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] nuage
[Termes IGN] occupation du sol
[Termes IGN] zone tropicale humideRésumé : (Auteur) With the increasing availability of high-resolution satellite imagery it is important to improve the efficiency and accuracy of satellite image indexing, retrieval and classification. Furthermore, there is a need for utilizing all available satellite imagery in identifying general land cover types and monitoring their changes through time irrespective of their spatial, spectral, temporal and radiometric resolutions. Therefore, in this study, we developed deep learning models able to efficiently and accurately classify cloud, shadow and land cover scenes in different high-resolution ( Numéro de notice : A2019-494 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.08.018 Date de publication en ligne : 17/09/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.08.018 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93727
in ISPRS Journal of photogrammetry and remote sensing > vol 157 (November 2019) . - pp 124 - 136[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2019111 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019113 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019112 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt New method for environmental monitoring in armed conflict zones: a case study of Syria / Samira Mobaied in Environmental Monitoring and Assessment, vol 191 n° 11 (November 2019)
[article]
Titre : New method for environmental monitoring in armed conflict zones: a case study of Syria Type de document : Article/Communication Auteurs : Samira Mobaied, Auteur ; Jean-Paul Rudant , Auteur Année de publication : 2019 Projets : 1-Pas de projet / Ali, Ahmed Adam Article en page(s) : n° 643 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] base de données d'occupation du sol
[Termes IGN] cartographie des risques
[Termes IGN] dégradation de l'environnement
[Termes IGN] guerre
[Termes IGN] image Sentinel-MSI
[Termes IGN] protection de la biodiversité
[Termes IGN] risque environnemental
[Termes IGN] Syrie
[Termes IGN] système d'information géographique
[Termes IGN] télédétection spatiale
[Termes IGN] zone à risqueRésumé : (auteur) Today, armed conflict affects some twenty countries, covering an area making up 11% of the surface area of the Earth. Any degradation of nature in these areas represents a harmful depletion of the world’s natural heritage. Despite this, environmental issues are neglected during these periods of conflict, considered secondary to the urgency of restoring peace and safeguarding human life. Yet their consequences are potentially severe. In these areas, it is future generations who will suffer the effects of the current devastation for a very long time. In this context, the method developed in this study, named (Geographic Information System) for Environmental Monitoring in Wartime, can be used to calculate a risk indicator for environmental degradation, spatial monitoring and risk management. This will make it possible to identify the main threats to protected areas, catalogue the damage caused to the environment by armed conflicts and create a dynamic risk map. In this paper, GIS-EMW has been applied to calculate a risk indicator for environmental degradation in Syria. Numéro de notice : A2019-509 Affiliation des auteurs : UPEM-LASTIG+Ext (2016-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10661-019-7805-5 Date de publication en ligne : 10/10/2019 En ligne : https://doi.org/10.1007/s10661-019-7805-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93794
in Environmental Monitoring and Assessment > vol 191 n° 11 (November 2019) . - n° 643[article]Potential of Landsat-8 and Sentinel-2A composite for land use land cover analysis / Divyesh Varade in Geocarto international, vol 34 n° 14 ([30/10/2019])PermalinkResidences information extraction from Landsat imagery using the multi-parameter decision tree method / Yujie Yang in Geocarto international, vol 34 n° 14 ([30/10/2019])PermalinkAutomatic canola mapping using time series of Sentinel 2 images / Davoud Ashourloo in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)PermalinkConsidering spatiotemporal processes in big data analysis: Insights from remote sensing of land cover and land use / Alexis Comber in Transactions in GIS, Vol 23 n° 5 (October 2019)PermalinkA machine learning approach to detect crude oil contamination in a real scenario using hyperspectral remote sensing / Ran Pelta in International journal of applied Earth observation and geoinformation, vol 82 (October 2019)PermalinkSaliency-guided deep neural networks for SAR image change detection / Jie Geng in IEEE Transactions on geoscience and remote sensing, Vol 57 n° 10 (October 2019)PermalinksUAS-based remote rensing of river discharge using thermal particle image velocimetry and bathymetric lidar / Paul J. Kinzel in Remote sensing, vol 11 n° 19 (October-1 2019)PermalinkMapping of forest tree distribution and estimation of forest biodiversity using Sentinel-2 imagery in the University Research Forest Taxiarchis in Chalkidiki, Greece / Maria Kampouri in Geocarto international, vol 34 n° 12 ([15/09/2019])PermalinkDevelopment and evaluation of a deep learning model for real-time ground vehicle semantic segmentation from UAV-based thermal infrared imagery / Mehdi Khoshboresh Masouleh in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)PermalinkQuantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale / Elena Barbierato in European journal of remote sensing, vol 52 n° 4 (2019)PermalinkCalculating potential evapotranspiration and single crop coefficient based on energy balance equation using Landsat 8 and Sentinel-2 / Ali Mokhtari in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)PermalinkEstimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images / Jie Wang in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)PermalinkGalileo and QZSS precise orbit and clock determination using new satellite metadata / Xingxing Li in Journal of geodesy, vol 93 n° 8 (August 2019)PermalinkHigh‐resolution national land use scenarios under a shrinking population in Japan / Haruka Ohashi in Transactions in GIS, vol 23 n° 4 (August 2019)PermalinkCombining spatiotemporal fusion and object-based image analysis for improving wetland mapping in complex and heterogeneous urban landscapes / Meng Zhang in Geocarto international, vol 34 n° 10 ([15/07/2019])PermalinkMapping the wavelength position of mineral features in hyperspectral thermal infrared data / Christoph Hecker in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)PermalinkMonitoring the structure of forest restoration plantations with a drone-lidar system / D.R.A. Almeida in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)PermalinkA novel method for separating woody and herbaceous time series / Qiang Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)PermalinkUsing LiDAR-modified topographic wetness index, terrain attributes with leaf area index to improve a single-tree growth model in south-eastern Finland / Cheikh Mohamedou in Forestry, an international journal of forest research, vol 92 n° 3 (July 2019)PermalinkLettre : Existe-t-il des relations formelles entre coefficients de diffusion radar et facteurs de réflectance en optique ? / Jean-Paul Rudant in Revue Française de Photogrammétrie et de Télédétection, n° 219-220 (juin - octobre 2019)PermalinkLong-term soil moisture content estimation using satellite and climate data in agricultural area of Mongolia / Enkhjargal Natsagdorj in Geocarto international, vol 34 n° 7 ([01/06/2019])PermalinkMise en oeuvre d'outils open source pour le suivi opérationnel de l'occupation des sols et de la déforestation à partir des données Sentinel radar optique : études de cas en Guyane et au Togo / Cédric Lardeux in Revue Française de Photogrammétrie et de Télédétection, n° 219-220 (juin - octobre 2019)PermalinkA new stochastic simulation algorithm for image-based classification : Feature-space indicator simulation / Qing Wang in ISPRS Journal of photogrammetry and remote sensing, vol 152 (June 2019)PermalinkTélédétection radar : de l'image d'intensité initiale au choix du mode de calibration des coefficients de diffusion / Jean-Paul Rudant in Revue Française de Photogrammétrie et de Télédétection, n° 219-220 (juin - octobre 2019)PermalinkUsing Sentinel-1A DInSAR interferometry and Landsat 8 data for monitoring water level changes in two lakes in Crete, Greece / D.D. Alexakis in Geocarto international, vol 34 n° 7 ([01/06/2019])PermalinkFusion of thermal imagery with point clouds for building façade thermal attribute mapping / Dong Lin in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)PermalinkCartographie de l’aléa érosif dans le bassin sud du Litani-Liban / Hussein El Hage Hassan in Revue internationale de géomatique, vol 29 n° 2 (avril - juin 2019)PermalinkThe process-based forest growth model 3-PG for use in forest management : A review / Rajit Gupta in Ecological modelling, vol 397 (1 April 2019)PermalinkWood quality of black spruce and balsam fir trees defoliated by spruce budworm: A case study in the boreal forest of Quebec, Canada / Carlos Paixao in Forest ecology and management, vol 437 (1 April 2019)PermalinkDiscrimination and classification of mangrove forests using EO-1 Hyperion data : a case study of Indian Sundarbans / Tanumi Kumar in Geocarto international, vol 34 n° 4 ([15/03/2019])PermalinkFeasibility study of vegetation indices derived from Sentinel-2 and PlanetScope satellite images for validating the LAI biophysical parameter to monitoring development stages of winter wheat / Radoslaw Gurdak in Geoinformation issues, Vol 10 n°1 (2018)PermalinkQuantifying spatiotemporal post‐disturbance recovery using field inventory, tree growth, and remote sensing / Shengli Huang in Earth and space science, vol 6 n° 3 (March 2019)PermalinkRadiometric calibration assessments for UAS-borne multispectral cameras: Laboratory and field protocols / Sen Cao in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)PermalinkLeaf area density from airborne LiDAR: Comparing sensors and resolutions in a temperate broadleaf forest ecosystem / Aaron G. Kamoske in Forest ecology and management, vol 433 (15 February 2019)Permalink3D radiative transfer modeling over complex vegetation canopies and forest reconstruction from LIDAR measurements / Jianbo Qi (2019)PermalinkDe l'agrandissement des exploitations agricoles à la transformation des paysages de bocage : analyse comparative des recompositions foncières et paysagères en Normandie / Thibault Preux (2019)PermalinkAilanthus altissima mapping from multi-temporal very high resolution satellite images / Cristina Tarantino in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)PermalinkAnalyse de données d’OpenStreetMap en vue de discriminer l’usage du sol lié au bâti / Jocelyn Le Maître (2019)PermalinkAssessment of different vegetation parameters for parameterizing the coupled water cloud model and advanced integral equation model for soil moisture retrieval using time series Sentinel-1A data / Long Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)PermalinkBridging the gap: toward a French MS-NFI for territories / Jean-Pierre Renaud (2019)PermalinkPermalinkChallenges in grassland mowing event detection with multimodal Sentinel images / Anatol Garioud (2019)PermalinkClimate variability and climate change impacts on land surface, hydrological processes and water management / Yongqiang Zhang (2019)PermalinkDataPink, l'IA au service de l'information géographique / Anonyme in Géomatique expert, n° 126 (janvier - février 2019)PermalinkEvaluation of time-series SAR and optical images for the study of winter land-use / Julien Denize (2019)Permalink