Descripteur
Termes IGN > télédétection > télédétection électromagnétique
télédétection électromagnétique |
Documents disponibles dans cette catégorie (944)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Object-based automatic multi-index built-up areas extraction method for WorldView-2 satellite imagery / Zhenhui Sun in Geocarto international, Vol 35 n° 8 ([01/06/2020])
[article]
Titre : Object-based automatic multi-index built-up areas extraction method for WorldView-2 satellite imagery Type de document : Article/Communication Auteurs : Zhenhui Sun, Auteur ; Qingyan Meng, Auteur Année de publication : 2020 Article en page(s) : pp 801 - 817 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] détection du bâti
[Termes IGN] extraction automatique
[Termes IGN] image à haute résolution
[Termes IGN] image multibande
[Termes IGN] image Worldview
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] Normalized Difference Water Index
[Termes IGN] optimisation par essaim de particules
[Termes IGN] segmentation d'imageRésumé : (auteur) The WorldView-2 high spatial resolution satellite with eight multispectral imaging bands is ideally suited for extracting built-up areas (BUs) from remote sensing images. In this study, an object-based automatic multi-index BUs extraction method was developed. First, several indices, including BUs extraction index (NBEIr-c), vegetation extraction index(NDVInir2-r) and water extraction index (NDWI b-nir1), were developed to obtain the BUs, vegetation and water maps, and then the fractional-order Darwinian particle swarm optimization (FODPSO) algorithm was employed to automatically segment the multi-index images and obtained BUs, water, vegetation and bare soil (BS) information. Finally, the extracted BUs results were optimized via an object-based analysis method and the results were compared with those of two other relevant indices, which confirmed the proposed method had a higher accuracy and exhibited higher performance when separating the BS from the BUs. Numéro de notice : A2020-273 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1544290 Date de publication en ligne : 07/02/2019 En ligne : https://doi.org/10.1080/10106049.2018.1544290 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95058
in Geocarto international > Vol 35 n° 8 [01/06/2020] . - pp 801 - 817[article]The geometric imaging model for high-resolution optical remote sensing satellites considering light aberration and atmospheric refraction errors / Mi Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 6 (June 2020)
[article]
Titre : The geometric imaging model for high-resolution optical remote sensing satellites considering light aberration and atmospheric refraction errors Type de document : Article/Communication Auteurs : Mi Wang, Auteur ; Ying Zhu, Auteur ; Yanli Wang, Auteur ; Yufeng Cheng, Auteur Année de publication : 2020 Article en page(s) : pp 373 -382 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] aberration chromatique
[Termes IGN] aberration géométrique
[Termes IGN] correction atmosphérique
[Termes IGN] image optique
[Termes IGN] réfraction atmosphérique
[Termes IGN] satellite d'observation de la Terre
[Termes IGN] télédétection spatialeRésumé : (Auteur) With advances in satellite maneuvering imaging capability, stereoscopic images with large roll and pitch angles can be captured to improve the efficiency of observations. At the same time, the influences of light aberration and atmospheric refraction on image positioning accuracy will be more significant. However, these errors are not accounted for in the traditional imaging and calibration model for optical agile satellites. In this study, the formation mechanisms of the aberration and atmospheric refraction errors in optical remote sensing satellite Earth observation imaging were analyzed quantitatively, and correction models were constructed. From this, the traditional geometric imaging model was refined by introducing a correction model for aberration and atmospheric refraction errors to create a more comprehensive geometric imaging model. The feasibility of an extended rational function model, based on the constructed more comprehensive geometric imaging model, was verified quantitatively. Numéro de notice : A2020-242 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.6.373 Date de publication en ligne : 01/06/2020 En ligne : https://doi.org/10.14358/PERS.86.6.373 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95204
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 6 (June 2020) . - pp 373 -382[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 105-2020061 SL Revue Centre de documentation Revues en salle Disponible Under-canopy UAV laser scanning for accurate forest field measurements / Eric Hyyppä in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)
[article]
Titre : Under-canopy UAV laser scanning for accurate forest field measurements Type de document : Article/Communication Auteurs : Eric Hyyppä, Auteur ; Juha Hyyppä, Auteur ; Teemu Hakala, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 41 - 60 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] balayage laser
[Termes IGN] canopée
[Termes IGN] cartographie et localisation simultanées
[Termes IGN] densité du bois
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] erreur moyenne quadratique
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] hauteur à la base du houppier
[Termes IGN] hauteur des arbres
[Termes IGN] image captée par drone
[Termes IGN] inventaire forestier local
[Termes IGN] modèle de croissance végétale
[Termes IGN] semis de points
[Termes IGN] télédétection aérienne
[Termes IGN] télémètre laser terrestre
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] troncRésumé : (auteur) Surveying and robotic technologies are converging, offering great potential for robotic-assisted data collection and support for labour intensive surveying activities. From a forest monitoring perspective, there are several technological and operational aspects to address concerning under-canopy flying unmanned airborne vehicles (UAV). To demonstrate this emerging technology, we investigated tree detection and stem curve estimation using laser scanning data obtained with an under-canopy flying UAV. To this end, we mounted a Kaarta Stencil-1 laser scanner with an integrated simultaneous localization and mapping (SLAM) system on board an UAV that was manually piloted with the help of video goggles receiving a live video feed from the onboard camera of the UAV. Using the under-canopy flying UAV, we collected SLAM-corrected point cloud data in a boreal forest on two 32 m 32 m test sites that were characterized as sparse ( = 42 trees) and obstructed ( = 43 trees), respectively. Novel data processing algorithms were applied for the point clouds in order to detect the stems of individual trees and to extract their stem curves and diameters at breast height (DBH). The estimated tree attributes were compared against highly accurate field reference data that was acquired semi-manually with a multi-scan terrestrial laser scanner (TLS). The proposed method succeeded in detecting 93% of the stems in the sparse plot and 84% of the stems in the obstructed plot. In the sparse plot, the DBH and stem curve estimates had a root-mean-squared error (RMSE) of 0.60 cm (2.2%) and 1.2 cm (5.0%), respectively, whereas the corresponding values for the obstructed plot were 0.92 cm (3.1%) and 1.4 cm (5.2%). By combining the stem curves extracted from the under-canopy UAV laser scanning data with tree heights derived from above-canopy UAV laser scanning data, we computed stem volumes for the detected trees with a relative RMSE of 10.1% in both plots. Thus, the combination of under-canopy and above-canopy UAV laser scanning allowed us to extract the stem volumes with an accuracy comparable to the past best studies based on TLS in boreal forest conditions. Since the stems of several spruces located on the test sites suffered from severe occlusion and could not be detected with the stem-based method, we developed a separate work flow capable of detecting trees with occluded stems. The proposed work flow enabled us to detect 98% of trees in the sparse plot and 93% of the trees in the obstructed plot with a 100% correction level in both plots. A key benefit provided by the under-canopy UAV laser scanner is the short period of time required for data collection, currently demonstrated to be much faster than the time required for field measurements and TLS. The quality of the measurements acquired with the under-canopy flying UAV combined with the demonstrated efficiency indicates operational potential for supporting fast and accurate forest resource inventories. Numéro de notice : A2020-240 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.03.021 Date de publication en ligne : 11/04/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.03.021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94994
in ISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 41 - 60[article]Réservation
Réserver ce documentExemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020061 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020063 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020062 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Wheat leaf area index retrieval using RISAT-1 hybrid polarized SAR data / Thota Sivasankar in Geocarto international, Vol 35 n° 8 ([01/06/2020])
[article]
Titre : Wheat leaf area index retrieval using RISAT-1 hybrid polarized SAR data Type de document : Article/Communication Auteurs : Thota Sivasankar, Auteur ; Dheeraj Kumar, Auteur ; Hari Shanker Srivastava, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 905 - 915 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande C
[Termes IGN] blé (céréale)
[Termes IGN] coefficient de corrélation
[Termes IGN] image radar moirée
[Termes IGN] image Risat-1
[Termes IGN] indice foliaire
[Termes IGN] polarisation
[Termes IGN] régression non linéaire
[Termes IGN] rétrodiffusion
[Termes IGN] séparateur à vaste marge
[Termes IGN] surveillance de la végétationRésumé : (auteur) Leaf Area Index (LAI) is a key parameter to characterize the canopy–atmosphere interface, where most of the energy fluxes exchange. Space-borne satellite images have shown their relevance for various applications including LAI retrieval over large areas. Although optical data have been used for this purpose in previous studies, the constraints to acquire optical data during extreme weather conditions due to the presence of clouds, haze, smoke etc. hinders its use for uninterrupted monitoring. This study aims to analyze the relationships of C-band RISAT-1 hybrid polarized SAR data (σ˚RH and σ˚RV) with wheat LAI. The results have shown the correlation coefficient (|r|) of 0.57 and 0.73 for RH and RV backscatter, respectively, using non-linear regression approach. It is also observed that the accuracy of LAI retrieval has been significantly improved with |r| and RMSE of 0.81 and 0.54 (m2/m2), respectively, by considering both RH and RV backscatter as inputs for support vector machine-based model. Numéro de notice : A2020-341 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10106049.2019.1566404 Date de publication en ligne : 07/02/2019 En ligne : https://doi.org/10.1080/10106049.2019.1566404 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95219
in Geocarto international > Vol 35 n° 8 [01/06/2020] . - pp 905 - 915[article]Year-to-year crown condition poorly contributes to ring width variations of beech trees in French ICP level I network / Clara Tallieu in Forest ecology and management, Vol 465 (1st June 2020)
[article]
Titre : Year-to-year crown condition poorly contributes to ring width variations of beech trees in French ICP level I network Type de document : Article/Communication Auteurs : Clara Tallieu, Auteur ; Vincent Badeau, Auteur ; Denis Allard, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 15 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage automatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] dendrochronologie
[Termes IGN] Fagus (genre)
[Termes IGN] Fagus sylvatica
[Termes IGN] feuille (végétation)
[Termes IGN] houppier
[Termes IGN] indice foliaire
[Termes IGN] pollution atmosphérique
[Termes IGN] sécheresse
[Termes IGN] stress hydrique
[Termes IGN] surveillance forestière
[Termes IGN] variation saisonnière
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Since the 1980-90′s episodes of decline in Central European Forests, forest condition has been surveyed thanks to the trans-national network the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests). It has been traditionally accepted that leaf loss is directly related to impairment of physiological condition of the tree. A few studies tried to correlate crown condition and growth trends while others concentrated on linking annual growth with crown observation at one date clustered into fertility classes. However, none focussed on the high frequency synchronism between leaf loss from annual network observations and annual radial growth issued from dendrochronology. Therefore, we jointly studied annual leaf loss observations and tree-ring width measurements on 715 common beech (Fagus sylvatica L.) trees distributed in the French part of the ICP monitoring network. Detrended inter-annual variations of leaf loss and tree-ring width index were used as response variables in the machine-learning algorithm Random Forest to investigate a common response to abiotic (current and lagged) and biotic hazards, to test the extent to which leaf loss helped to predict inter-annual variations in radial growth. Using Random Forest was effective to identify a common sensitivity to soil water deficit at different time lags. Previous-year climatic variables tended to control leaf loss while radial growth was more sensitive to current-year soil water deficit. Late frost damages were observed on crown condition in mountainous regions but no impact was detected on radial growth. Few significant biotic damages were observed on growth or leaf loss. Leaf loss series did not show a clear common signal among trees from a plot as did radial growth and captured fewer pointer years. Radial growth index did not fall below normal until a 20% leaf loss was reached. However, this threshold is driven by a few extreme leaf loss events. As shown by our joint analysis of leaf loss and radial growth pointer years, no relationship occurred in cases of slight or moderate defoliation. Crown condition is a poorer descriptor of tree vitality than radial growth. Numéro de notice : A2020-287 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2020.118071 Date de publication en ligne : 01/04/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118071 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95111
in Forest ecology and management > Vol 465 (1st June 2020) . - 15 p.[article]Assessment of winter season land surface temperature in the Himalayan regions around the Kullu area in India using Landsat-8 data / Divyesh Varade in Geocarto international, vol 35 n° 6 ([01/05/2020])PermalinkIntertidal topography mapping using the waterline method from Sentinel-1 & -2 images: The examples of Arcachon and Veys Bays in France / Edward Salameh in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)PermalinkModeling strawberry biomass and leaf area using object-based analysis of high-resolution images / Zhen Guan in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)PermalinkShrub biomass estimates in former burnt areas using Sentinel 2 images processing and classification / Jose Aranha in Forests, vol 11 n° 5 (May 2020)PermalinkAbove-ground biomass estimation and yield prediction in potato by using UAV-based RGB and hyperspectral imaging / Bo Li in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)PermalinkDetection of Xylella fastidiosa infection symptoms with airborne multispectral and thermal imagery: Assessing bandset reduction performance from hyperspectral analysis / T. Poblete in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)PermalinkA Fusion Approach for Water Area Classification Using Visible, Near Infrared and Synthetic Aperture Radar for South Asian Conditions / Shahryar K. Ahmad in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)PermalinkSpatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow river, China / Mingyue Wang in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)PermalinkTemporal Validation of Four LAI Products over Grasslands in the Northeastern Tibetan Plateau / Gaofei Yin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 4 (April 2020)PermalinkWavelet and non-parametric statistical based approach for long term land cover trend analysis using time series EVI data / Niraj Priyadarshi in Geocarto international, vol 35 n° 5 ([01/04/2020])PermalinkRadar Vegetation Index for assessing cotton crop condition using RISAT-1 data / Dipanwita Haldar in Geocarto international, vol 35 n° 4 ([15/03/2020])PermalinkA framework for extracting urban functional regions based on multiprototype word embeddings using points-of-interest data / Sheng Hu in Computers, Environment and Urban Systems, vol 80 (March 2020)PermalinkImproving operational radar rainfall estimates using profiler observations over complex terrain in Northern California / Haonan Chen in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)PermalinkThermal unmixing based downscaling for fine resolution diurnal land surface temperature analysis / Jiong Wang in ISPRS Journal of photogrammetry and remote sensing, vol 161 (March 2020)PermalinkEstimating wheat yields in Australia using climate records, satellite image time series and machine learning methods / Elisa Kamir in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)PermalinkLandslide susceptibility mapping using maximum entropy and support vector machine models along the highway corridor, Garhwal Himalaya / Vijendra Kumar Pandey in Geocarto international, vol 35 n° 2 ([01/02/2020])PermalinkMODIS-based land surface temperature for climate variability and change research: the tale of a typical semi-arid to arid environment / Salahuddin M. Jaber in European journal of remote sensing, vol 53 n° 1 (2020)PermalinkPlant survival monitoring with UAVs and multispectral data in difficult access afforested areas / Maria Luz Gil-Docampo in Geocarto international, vol 35 n° 2 ([01/02/2020])PermalinkPrediction of plant diversity in grasslands using Sentinel-1 and -2 satellite image time series / Mathieu Fauvel in Remote sensing of environment, Vol 237 (February 2020)PermalinkRed-edge band vegetation indices for leaf area index estimation from Sentinel-2/MSI imagery / Yuanheng Sun in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)PermalinkThe effects of different combinations of simulated climate change-related stressors on juveniles of seven forest tree species grown as mono-species and mixed cultures / Alfas Pliüra in Baltic forestry, vol 26 n° 1 ([01/02/2020])PermalinkThe potentiality of Sentinel-2 to assess the effect of fire events on Mediterranean mountain vegetation / Walter de Simone in Plant sociology, vol 57 n° 1 ([01/02/2020])PermalinkAnalyse automatique du couvert végétal pour la gestion du risque végétation en milieu ferroviaire à partir d'imagerie aérienne / Hélène Rouillon (2020)PermalinkCaractérisation du manteau neigeux arctique, suivi climatique et télédétection micro-onde / Céline Vargel (2020)PermalinkCombination of linear regression lines to understand the response of Sentinel-1 dual polarization SAR data with crop phenology - case study in Miyazaki, Japan / Emal Wali in Remote sensing, vol 12 n° 1 (January 2020)PermalinkDétermination conjointe des inondations et du type d’eau au moyen de l’imagerie multi-spectrale / Sabrine Amzil (2020)PermalinkFusion of 3D point clouds and hyperspectral data for the extraction of geometric and radiometric features of trees / Eduardo Alejandro Tusa Jumbo (2020)PermalinkGéodésie, topographie, cartographie / Bernard Lamy (2020)PermalinkIndividual tree detection and classification for mapping pine wilt disease using multispectral and visible color imagery acquired from unmanned aerial vehicle / Takeshi Hoshikawa in Journal of The Remote Sensing Society of Japan, vol 40 n° 1 (2020)PermalinkOn the joint exploitation of optical and SAR satellite imagery for grassland monitoring / Anatol Garioud (2020)PermalinkPhotogrammetric Bathymetry for the Canadian Arctic / Matus Hodul in Marine geodesy, Vol 43 n° 1 (January 2020)PermalinkRegional-scale forest mapping over fragmented landscapes using global forest products and Landsat time series classification / Viktor Myroniuk in Remote sensing, vol 12 n° 1 (January 2020)PermalinkPermalinkPermalinkA systematic evaluation of influence of image selection process on remote sensing-based burn severity indices in North American boreal forest and tundra ecosystems / Dong Chen in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)PermalinkUncertainty analysis of remotely-acquired thermal infrared data to extract the thermal Properties of active lava surfaces / James A. Thompson in Remote sensing, vol 12 n° 1 (January 2020)PermalinkUsing remote sensing to assess the effect of time of day on the spatial and temporal variation of LST in urban areas / Akram Abdulla (2020)PermalinkUso de QGIS en la teledetección, Vol. 2. QGIS y sus aplicaciones en la agricultura y la silvicultura / Nicolas Baghdadi (2020)PermalinkUso de QGIS en la teledetección, Vol. 4. QGIS y sus aplicaciones en agua y en gestion del riego / Nicolas Baghdadi (2020)PermalinkPermalinkAn implicit radar convolutional burn index for burnt area mapping with Sentinel-1 C-band SAR data / Puzhao Zhang in ISPRS Journal of photogrammetry and remote sensing, Vol 158 (December 2019)PermalinkCombining thermal imaging with photogrammetry of an active volcano using UAV: an example from Stromboli, Italy / Zoë E. Wakeford in Photogrammetric record, vol 34 n° 168 (December 2019)PermalinkQuantification 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)PermalinkSpatiotemporal variation in the relationship between boreal forest productivity proxies and climate data / Clémentine Ols in Dendrochronologia, vol 58 (December 2019)PermalinkAccurate 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)PermalinkDeep 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)PermalinkNew 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)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)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)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)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)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)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)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)PermalinkChallenges in grassland mowing event detection with multimodal Sentinel images / Anatol Garioud (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)PermalinkExploitation of hyperspectral data for assessing vegetation health under exposure to petroleum hydrocarbons / Guillaume Lassalle (2019)PermalinkExploitation de séries temporelles d'images multi-sources pour la cartographie des surfaces en eau / Filsa Bioresita (2019)PermalinkPermalinkImproving the spatial bias correction algorithm in SMOS image reconstruction processor : validation of soil moisture retrievals with in situ data / Ali Khazaal in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)PermalinkIndividual tree detection and crown delineation with 3D information from multi-view satellite Images / Changlin Xiao in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)PermalinkMonitoring crops water needs at high spatio-temporal resolution by synergy of optical / thermal and radar observations / Abdelhakim Amazirh (2019)PermalinkPermalinkPermalinkPermalinkPermalinkPermalinkPermalinkSimultaneous characterization of objects temperature and radiative properties through multispectral infrared thermography / Thibaud Toullier (2019)PermalinkPermalinkPermalink