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Geospatial-based machine learning techniques for land use and land cover mapping using a high-resolution unmanned aerial vehicle image / Taposh Mollick in Remote Sensing Applications: Society and Environment, RSASE, vol 29 (January 2023)
[article]
Titre : Geospatial-based machine learning techniques for land use and land cover mapping using a high-resolution unmanned aerial vehicle image Type de document : Article/Communication Auteurs : Taposh Mollick, Auteur ; MD Golam Azam, Auteur ; Sabrina Karim, Auteur Année de publication : 2023 Article en page(s) : n° 100859 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse d'image orientée objet
[Termes IGN] apprentissage automatique
[Termes IGN] Bangladesh
[Termes IGN] classification non dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par nuées dynamiques
[Termes IGN] classification pixellaire
[Termes IGN] image captée par drone
[Termes IGN] image multibande
[Termes IGN] occupation du sol
[Termes IGN] rendement agricole
[Termes IGN] segmentation d'image
[Termes IGN] utilisation du solRésumé : (auteur) Bangladesh is primarily an agricultural country where technological advancement in the agricultural sector can ensure the acceleration of economic growth and ensure long-term food security. This research was conducted in the south-western coastal zone of Bangladesh, where rice is the main crop and other crops are also grown. Land use and land cover (LULC) classification using remote sensing techniques such as the use of satellite or unmanned aerial vehicle (UAV) images can forecast the crop yield and can also provide information on weeds, nutrient deficiencies, diseases, etc. to monitor and treat the crops. Depending on the reflectance received by sensors, remotely sensed images store a digital number (DN) for each pixel. Traditionally, these pixel values have been used to separate clusters and classify various objects. However, it frequently generates a lot of discontinuity in a particular land cover, resulting in small objects within a land cover that provide poor image classification output. It is called the salt-and-pepper effect. In order to classify land cover based on texture, shape, and neighbors, Pixel-Based Image Analysis (PBIA) and Object-Based Image Analysis (OBIA) methods use digital image classification algorithms like Maximum Likelihood (ML), K-Nearest Neighbors (KNN), k-means clustering algorithm, etc. to smooth this discontinuity. The authors evaluated the accuracy of both the PBIA and OBIA approaches by classifying the land cover of an agricultural field, taking into consideration the development of UAV technology and enhanced image resolution. For classifying multispectral UAV images, we used the KNN machine learning algorithm for object-based supervised image classification and Maximum Likelihood (ML) classification (parametric) for pixel-based supervised image classification. Whereas, for unsupervised classification using pixels, we used the K-means clustering technique. For image analysis, Near-infrared (NIR), Red (R), Green (G), and Blue (B) bands of a high-resolution ground sampling distance (GSD) 0.0125m UAV image was used in this research work. The study found that OBIA was 21% more accurate than PBIA, indicating 94.9% overall accuracy. In terms of Kappa statistics, OBIA was 27% more accurate than PBIA, indicating Kappa statistics accuracy of 93.4%. It indicates that OBIA provides better classification performance when compared to PBIA for the classification of high-resolution UAV images. This study found that by suggesting OBIA for more accurate identification of types of crops and land cover, which will help crop management, agricultural monitoring, and crop yield forecasting be more effective. Numéro de notice : A2023-021 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rsase.2022.100859 Date de publication en ligne : 22/11/2022 En ligne : https://doi.org/10.1016/j.rsase.2022.100859 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102224
in Remote Sensing Applications: Society and Environment, RSASE > vol 29 (January 2023) . - n° 100859[article]Change alignment-based image transformation for unsupervised heterogeneous change detection / Kuowei Xiao in Remote sensing, vol 14 n° 21 (November-1 2022)
[article]
Titre : Change alignment-based image transformation for unsupervised heterogeneous change detection Type de document : Article/Communication Auteurs : Kuowei Xiao, Auteur ; Yuli Sun, Auteur ; Lin Lei, Auteur Année de publication : 2022 Article en page(s) : n° 5622 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] alignement
[Termes IGN] classification non dirigée
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] décomposition d'image
[Termes IGN] détection de changement
[Termes IGN] données hétérogènes
[Termes IGN] masqueRésumé : (auteur) Change detection (CD) with heterogeneous images is currently attracting extensive attention in remote sensing. In order to make heterogeneous images comparable, the image transformation methods transform one image into the domain of another image, which can simultaneously obtain a forward difference map (FDM) and backward difference map (BDM). However, previous methods only fuse the FDM and BDM in the post-processing stage, which cannot fundamentally improve the performance of CD. In this paper, a change alignment-based change detection (CACD) framework for unsupervised heterogeneous CD is proposed to deeply utilize the complementary information of the FDM and BDM in the image transformation process, which enhances the effect of domain transformation, thus improving CD performance. To reduce the dependence of the transformation network on labeled samples, we propose a graph structure-based strategy of generating prior masks to guide the network, which can reduce the influence of changing regions on the transformation network in an unsupervised way. More importantly, based on the fact that the FDM and BDM are representing the same change event, we perform change alignment during the image transformation, which can enhance the image transformation effect and enable FDM and BDM to effectively indicate the real change region. Comparative experiments are conducted with six state-of-the-art methods on five heterogeneous CD datasets, showing that the proposed CACD achieves the best performance with an average overall accuracy (OA) of 95.9% on different datasets and at least 6.8% improvement in the kappa coefficient. Numéro de notice : A2022-855 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14215622 Date de publication en ligne : 07/11/2022 En ligne : https://doi.org/10.3390/rs14215622 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102103
in Remote sensing > vol 14 n° 21 (November-1 2022) . - n° 5622[article]Unsupervised multi-view CNN for salient view selection and 3D interest point detection / Ran Song in International journal of computer vision, vol 130 n° 5 (May 2022)
[article]
Titre : Unsupervised multi-view CNN for salient view selection and 3D interest point detection Type de document : Article/Communication Auteurs : Ran Song, Auteur ; Wei Zhang, Auteur ; Yitian Zhao, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1210 - 1227 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] classification non dirigée
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection d'objet
[Termes IGN] objet 3D
[Termes IGN] point d'intérêt
[Termes IGN] saillanceRésumé : (auteur) We present an unsupervised 3D deep learning framework based on a ubiquitously true proposition named by us view-object consistency as it states that a 3D object and its projected 2D views always belong to the same object class. To validate its effectiveness, we design a multi-view CNN instantiating it for salient view selection and interest point detection of 3D objects, which quintessentially cannot be handled by supervised learning due to the difficulty of collecting sufficient and consistent training data. Our unsupervised multi-view CNN, namely UMVCNN, branches off two channels which encode the knowledge within each 2D view and the 3D object respectively and also exploits both intra-view and inter-view knowledge of the object. It ends with a new loss layer which formulates the view-object consistency by impelling the two channels to generate consistent classification outcomes. The UMVCNN is then integrated with a global distinction adjustment scheme to incorporate global cues into salient view selection. We evaluate our method for salient view section both qualitatively and quantitatively, demonstrating its superiority over several state-of-the-art methods. In addition, we showcase that our method can be used to select salient views of 3D scenes containing multiple objects. We also develop a method based on the UMVCNN for 3D interest point detection and conduct comparative evaluations on a publicly available benchmark, which shows that the UMVCNN is amenable to different 3D shape understanding tasks. Numéro de notice : A2022-415 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s11263-022-01592-x Date de publication en ligne : 16/03/2022 En ligne : https://doi.org/10.1007/s11263-022-01592-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100771
in International journal of computer vision > vol 130 n° 5 (May 2022) . - pp 1210 - 1227[article]Automatic extraction of building geometries based on centroid clustering and contour analysis on oblique images taken by unmanned aerial vehicles / Leilei Zhang in International journal of geographical information science IJGIS, vol 36 n° 3 (March 2022)
[article]
Titre : Automatic extraction of building geometries based on centroid clustering and contour analysis on oblique images taken by unmanned aerial vehicles Type de document : Article/Communication Auteurs : Leilei Zhang, Auteur ; Guoxin Wang, Auteur ; Weijian Sun, Auteur Année de publication : 2022 Article en page(s) : pp 453 - 475 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] classification barycentrique
[Termes IGN] classification non dirigée
[Termes IGN] détection de contours
[Termes IGN] détection du bâti
[Termes IGN] extraction automatique
[Termes IGN] image captée par drone
[Termes IGN] image oblique
[Termes IGN] modèle numérique de surface
[Termes IGN] orthophotocarte
[Termes IGN] précision géométrique (imagerie)Résumé : (auteur) This paper introduces a method based on centroid clustering and contour analysis to extract area and height measurements on buildings from the 3D model generated by oblique images. The method comprises three steps: (1) extract the contour plane from the fused data of the digital surface model (DSM) and digital orthophoto map (DOM); (2) identify building contour clusters based on the number of centroids contained in each category determined by mean-shift centroid clustering; (3) remove the mis-identified contours in a given building contour cluster by a contour analysis and obtain the geometric information of the building using map algebra. The proposed approach was tested against four datasets. Compared with other results, the detection has effective completeness, correctness, quality, and higher geometric accuracy. The maximum average relative error of building height and area extraction is less than 8%. The method is fast for a large-scale collection of building attributes and improves the applicability of oblique photography in GIS. Numéro de notice : A2022-205 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1937632 Date de publication en ligne : 14/06/2021 En ligne : https://doi.org/10.1080/13658816.2021.1937632 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100020
in International journal of geographical information science IJGIS > vol 36 n° 3 (March 2022) . - pp 453 - 475[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2022031 SL Revue Centre de documentation Revues en salle Disponible Neural map style transfer exploration with GANs / Sidonie Christophe in International journal of cartography, vol 8 n° 1 (March 2022)
[article]
Titre : Neural map style transfer exploration with GANs Type de document : Article/Communication Auteurs : Sidonie Christophe , Auteur ; Samuel Mermet , Auteur ; Morgan Laurent, Auteur ; Guillaume Touya , Auteur Année de publication : 2022 Projets : 1-Pas de projet / Article en page(s) : pp 18 - 36 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage profond
[Termes IGN] classification non dirigée
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] grille d'échantillonnage
[Termes IGN] orthoimage
[Termes IGN] représentation cartographique
[Termes IGN] réseau antagoniste génératif
[Termes IGN] style cartographique
[Termes IGN] visualisation cartographique
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Neural Style Transfer is a Computer Vision topic intending to transfer the visual appearance or the style of images to other images. Developments in deep learning nicely generate stylized images from texture-based examples or transfer the style of a photograph to another one. In map design, the style is a multi-dimensional complex problem related to recognizable visual salient features and topological arrangements, supporting the description of geographic spaces at a specific scale. The map style transfer is still at stake to generate a diversity of possible new styles to render geographical features. Generative adversarial Networks (GANs) techniques, well supporting image-to-image translation tasks, offer new perspectives for map style transfer. We propose to use accessible GAN architectures, in order to experiment and assess neural map style transfer to ortho-images, while using different map designs of various geographic spaces, from simple-styled (Plan maps) to complex-styled (old Cassini, Etat-Major, or Scan50 B&W). This transfer task and our global protocol are presented, including the sampling grid, the training and test of Pix2Pix and CycleGAN models, such as the perceptual assessment of the generated outputs. Promising results are discussed, opening research issues for neural map style transfer exploration with GANs. Numéro de notice : A2022-172 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2022.2031554 Date de publication en ligne : 13/02/2022 En ligne : https://doi.org/10.1080/23729333.2022.2031554 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99807
in International journal of cartography > vol 8 n° 1 (March 2022) . - pp 18 - 36[article]Probabilistic unsupervised classification for large-scale analysis of spectral imaging data / Emmanuel Paradis in International journal of applied Earth observation and geoinformation, vol 107 (March 2022)PermalinkApprentissage de représentations et modèles génératifs profonds dans les systèmes dynamiques / Jean-Yves Franceschi (2022)PermalinkDeep image translation with an affinity-based change prior for unsupervised multimodal change detection / Luigi Tommaso Luppino in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)PermalinkPermalinkFlexible Gabor-based superpixel-level unsupervised LDA for hyperspectral image classification / Sen Jia in IEEE Transactions on geoscience and remote sensing, vol 59 n° 12 (December 2021)PermalinkA feature based change detection approach using multi-scale orientation for multi-temporal SAR images / R. Vijaya Geetha in European journal of remote sensing, vol 54 sup 2 (2021)PermalinkUnsupervised self-adaptive deep learning classification network based on the optic nerve microsaccade mechanism for unmanned aerial vehicle remote sensing image classification / Ming Cong in Geocarto international, vol 36 n° 18 ([01/10/2021])PermalinkUnsupervised representation high-resolution remote sensing image scene classification via contrastive learning convolutional neural network / Fengpeng Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 8 (August 2021)PermalinkUnsupervised denoising for satellite imagery using wavelet directional cycleGAN / Shaoyang Kong in IEEE Transactions on geoscience and remote sensing, vol 59 n° 8 (August 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])PermalinkReview of spectral indices for urban remote sensing / Akib Javed in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 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)PermalinkA novel unsupervised change detection method from remotely sensed imagery based on an improved thresholding algorithm / Sara Khanbani in Applied geomatics, vol 13 n° 1 (May 2021)PermalinkUnsupervised multi-level feature extraction for improvement of hyperspectral classification / Qiaoqiao Sun in Remote sensing, vol 13 n° 8 (April-2 2021)PermalinkExtraction of sea ice cover by Sentinel-1 SAR based on support vector machine with unsupervised generation of training data / Xiao-Ming Li in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)PermalinkSpectral–spatial-aware unsupervised change detection with stochastic distances and support vector machines / Rogério Galante Negri in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)PermalinkUnsupervised pansharpening based on self-attention mechanism / Ying Qu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)PermalinkImproving the unsupervised mapping of riparian bugweed in commercial forest plantations using hyperspectral data and LiDAR / Kabir Peerbhay in Geocarto international, vol 36 n° 4 ([01/03/2021])PermalinkRobust unsupervised small area change detection from SAR imagery using deep learning / Xinzheng Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 173 (March 2021)PermalinkUnsupervised deep representation learning for real-time tracking / Ning Wang in International journal of computer vision, vol 129 n° 2 (February 2021)PermalinkPermalinkLearning disentangled representations of satellite image time series in a weakly supervised manner / Eduardo Hugo Sanchez (2021)PermalinkModélisation de l’aire de réception d’une antenne AIS en fonction de données d’altitude et de cartes de prévision de propagation d’ondes VHF / Zackary Vanche (2021)PermalinkA framework for unsupervised wildfire damage assessment using VHR satellite images with PlanetScope data / Minkyung Chung in Remote sensing, vol 12 n° 22 (December-1 2020)PermalinkUnsupervised deep joint segmentation of multitemporal high-resolution images / Sudipan Saha in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)PermalinkA fractal projection and Markovian segmentation-based approach for multimodal change detection / Max Mignotte in IEEE Transactions on geoscience and remote sensing, vol 58 n° 11 (November 2020)PermalinkCoupling fuzzy clustering and cellular automata based on local maxima of development potential to model urban emergence and expansion in economic development zones / Xun Liang in International journal of geographical information science IJGIS, vol 34 n° 10 (October 2020)PermalinkA novel framework based on polarimetric change vectors for unsupervised multiclass change detection in dual-pol intensity SAR images / David Pirrone in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)PermalinkUnsupervised semantic and instance segmentation of forest point clouds / Di Wang in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)PermalinkCoastline change modelling induced by climate change using geospatial techniques in Togo (West Africa) / Yawo Konko in Advances in Remote Sensing, vol 9 n° 2 (June 2020)PermalinkUnsupervised change detection between SAR images based on hypergraphs / Jun Wang in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkUnsupervised extraction of urban features from airborne lidar data by using self-organizing maps / Alper Sen in Survey review, vol 52 n° 371 (March 2020)PermalinkMulti-spectral image change detection based on single-band iterative weighting and fuzzy C-means clustering / Liyuan Ma in European journal of remote sensing, vol 53 n° 1 (2020)PermalinkPermalinkUnsupervised classification of multispectral images embedded with a segmentation of panchromatic images using localized clusters / Ting Mao in IEEE Transactions on geoscience and remote sensing, vol 57 n° 11 (November 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)PermalinkVoxel-based 3D point cloud semantic segmentation: unsupervised geometric and relationship featuring vs deep learning methods / Florent Poux in ISPRS International journal of geo-information, vol 8 n° 5 (May 2019)PermalinkPermalinkLe vandalisme dans l’information géographique volontaire, détection de l’IG volontaire vandalisée : du concept à la détection non supervisée d’anomalie / Quy Thy Truong in Revue internationale de géomatique, vol 29 n° 1 (janvier - mars 2019)PermalinkContextual classification using photometry and elevation data for damage detection after an earthquake event / Ewelina Rupnik in European journal of remote sensing, vol 51 n° 1 (2018)PermalinkAdapting an existing semi-automatized image processing chain to enable Sentinel-2 data classification. / Hiyam Elbadri (2018)PermalinkUse of satellite image classifications to update and enhance a land cover database / Mohamed Touiti (2018)PermalinkUse of unsupervised classification for the determination of prevailing land use typology / Miha Konjar in Geodetski vestnik, vol 61 n° 4 (December 2017 - February 2018)PermalinkAn unsupervised two-stage clustering approach for forest structure classification based on X-band InSAR data — A case study in complex temperate forest stands / Sahra Abdullahi in International journal of applied Earth observation and geoinformation, vol 57 (May 2017)PermalinkUnsupervised object-based differencing for land-cover change detection / Jinxia Zhu in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 3 (March 2017)PermalinkJoint analysis of passive and active land surface responses for Global Precipitation Measurement / Iris de Gelis (2017)PermalinkMRF-based segmentation and unsupervised classification for building and road detection in peri-urban areas of high-resolution satellite images / Ilias Grinias in ISPRS Journal of photogrammetry and remote sensing, vol 122 (December 2016)PermalinkShadow detection and removal in RGB VHR images for land use unsupervised classification / A. Movia in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)PermalinkUnsupervised classification of airborne laser scanning data to locate potential wildlife habitats for forest management planning / Jari Vauhkonen in Forestry, an international journal of forest research, vol 89 n° 4 (August 2016)PermalinkAn evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States / Jochen Wendel in Cartography and Geographic Information Science, Vol 43 n° 3 (June 2016)PermalinkUsing classification trees to predict forest structure types from LiDAR data / Chiara Torresan in Annals of forest research, vol 59 n° 2 (July - December 2016)PermalinkContributions à la segmentation non supervisée d'images hyperspectrales : trois approches algébriques et géométriques / Saadallah El Asmar (2016)PermalinkA semiautomated probabilistic framework for tree-cover delineation from 1-m NAIP imagery using a high-performance computing architecture / S. Basu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)PermalinkAn unsupervised urban change detection procedure by using luminance and saturation for multispectral remotely sensed images / Su Ye in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 8 (August 2015)PermalinkA new sparse source separation-based classification approach / M.A. Loghmari in IEEE Transactions on geoscience and remote sensing, vol 52 n° 11 tome 1 (November 2014)PermalinkToward satellite-based land cover classification through optimum-path forest / Rodrigo José Pisani in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)PermalinkGeospatial method for computing supplemental multi-decadal US coastal land use and land cover classification products, using Landsat data and C-CAP products / Joseph P. Spruce in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)PermalinkConnaissance de la biodiversité végétale / Jan-Bernard Bouzillé (2014)PermalinkFusion of airborne laserscanning point clouds and images for supervised and unsupervised scene classification / Markus Gerke in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)PermalinkClassification automatique des images satellitaires optimisée par l'algorithme des chauves-souris / Soumia Benmostefa in Revue Française de Photogrammétrie et de Télédétection, n° 203 (Juillet 2013)PermalinkClassification and reconstruction from random projections for hyperspectral imagery / W. Li in IEEE Transactions on geoscience and remote sensing, vol 51 n° 2 (February 2013)PermalinkComparaison et évaluation de méthodes d'extraction automatique d'objets sur des images optique et radar / Charlotte Benedetto (2013)PermalinkCrop yield estimation based on unsupervised linear unmixing of multidate hyperspectral imagery / B. Luo in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 1 (January 2013)PermalinkExploring geomorphometry through user generated content: Comparing an unsupervised geomorphometric classification with terms attached to georeferenced images in Great Britain / C. Gschwend in Transactions in GIS, vol 16 n° 4 (August 2012)PermalinkHyperspectral unmixing based on mixtures of Dirichlet components / J. Nascimento in IEEE Transactions on geoscience and remote sensing, vol 50 n° 3 (March 2012)PermalinkTraitements numériques des images de télédétection, Vol. 3. Traitements appliqués à la photo-interprétation / Olivier de Joinville (2012)PermalinkApproche non supervisée par processus ponctuels marqués pour l'extraction d'objets à partir d'images aériennes et satellitaires / S. Ben Hadj in Revue Française de Photogrammétrie et de Télédétection, n° 194 (Mai 2011)PermalinkAutomatic fuzzy clustering using modified differential evolution for image classification / U. Maulik in IEEE Transactions on geoscience and remote sensing, vol 48 n° 9 (September 2010)PermalinkExtraction automatique des discontinuités planes à partir d'une scannérisation laser 3D en milieu rocheux / Souhail Hajri in Revue Française de Photogrammétrie et de Télédétection, n° 192 (Septembre 2010)PermalinkApplication de la classification floue (fuzzy k-NN) à l'étude de l'occupation du sol d'une zone urbaine : le cas de la région de Genève / S. Rakotoniaina in Photo interprétation, European journal of applied remote sensing, vol 46 n° 2 (juin 2010)PermalinkCommentaire de la carte des changements de l'occupation du sol dans les Rivières-du-Sud / J. Andrieu in Le monde des cartes, n° 203 (mars 2010)PermalinkMapping an annual weed with colour-infared aerial photography and image analysis / James H. Everitt in Geocarto international, vol 25 n° 1 (February 2010)PermalinkTraitement des données de télédétection / Michel-Claude Girard (2010)PermalinkAutomated extraction of buildings from Ikonos imagery by integrating spectral and spatial information / X. Wang in Geomatica, vol 63 n° 3 (September 2009)PermalinkEvaluation du bilan d'érosion et de dépôt des sols au pré-Rif (Maroc) en utilisant le modèle RUSLE, la télédétection et l'analyse spatiale / Abdelkader El Garouani in Revue internationale de géomatique, vol 19 n° 3 (septembre - novembre 2009)PermalinkApprentissage automatique des classes d'occupation du sol et représentation en mots visuels des images satellitaires / Marie Lauginie Lienou (2009)PermalinkClassifications hiérarchiques orientées objet / Olivier de Joinville (2009)PermalinkIntegration of Hyperion satellite data and a household social survey to caracterize the causes and consequences of reforestation patterns in the Northern Ecuadorian Amazon / S.J. Walsh in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 6 (June 2008)Permalinkvol 46 n° 5 - May 2008 - Special issue on data fusion (Bulletin de IEEE Transactions on geoscience and remote sensing) / Geoscience and remote sensing societyPermalinkUrban-trees extraction from Quickbird imagery using multiscale spectex-filtering and non-parametric classification / Y.O. Ouma in ISPRS Journal of photogrammetry and remote sensing, vol 63 n° 3 (May - June 2008)PermalinkClassification non supervisée d'image RSO à l'aide d'extremums locaux d'histogramme : applications à la cartographie de la mangrove littorale camerounaise / J. Fotsing in Revue Française de Photogrammétrie et de Télédétection, n° 189 (Mars 2008)PermalinkClassification of floodplain vegetation by data fusion of spectral (CASI) and LiDAR data / G.W. Geerling in International Journal of Remote Sensing IJRS, vol 28 n°19-20 (October 2007)PermalinkConsultation et classification d'échantillons cartographiques / Guillaume Ménégaux (2007)PermalinkDEM resolution dependencies of terrain attributes across a landscape / Y. Deng in International journal of geographical information science IJGIS, vol 21 n° 1-2 (january 2007)PermalinkEvolution des habitats dans les montagnes d'Araucania / Rémi Pas (2007)PermalinkMapping urban land cover using Quickbird NDVI and GIS spatial modeling for runoff coefficient determination / P. Thanapura in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 1 (January 2007)PermalinkWoody vegetation increase in Alpine areas: a proposal for a classification and validation scheme / M. Maggi in International Journal of Remote Sensing IJRS, vol 28 n° 1-2 (January 2007)PermalinkDelineating lakes and enclosed islands in satellite imagery by geodesic active contour model / C. Shen in International Journal of Remote Sensing IJRS, vol 27 n°23-24 (December 2006)PermalinkExploiting class hierarchies for knowledge transfer in hyperspectral data / S. Rajan in IEEE Transactions on geoscience and remote sensing, vol 44 n° 11 Tome 2 (November 2006)PermalinkSélection adaptative des dimensions de l'indexation visuelle d'images mal annotées en fonction du mot recherché / S. Tollari in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 11 n° 4 (juillet - août 2006)PermalinkApport de la classification combinée supervisée et non supervisée d'une image Landsat ETM+ à la cartographie géologique de la boutonnière de Kerdous, anti-atlas, Maroc / M. Hakdaoui in Photo interprétation, vol 42 n° 2 (Juin 2006)PermalinkContextual reconstruction of cloud-contaminated multitemporal multispectral image / F. Melgani in IEEE Transactions on geoscience and remote sensing, vol 44 n° 2 (February 2006)PermalinkCAp 2006, 8e conférence francophone sur l'apprentissage automatique, 22 - 24 mai 2006, Trégastel, France / Laurent Miclet (2006)PermalinkEtude de différents facteurs influant les classifications d'images multi-résolution / F. Kazemipour (2006)PermalinkAménagement et développement rural dans le bas Loukkos (Maroc) : suivi et évaluation à l'aide de la télédetection et des SIG / R. Ragala in Photo interprétation, vol 41 n° 4 (Novembre 2005)PermalinkDynamique urbaine et télédétection : le choix de l'indicateur végétal, les cas de Montréal, Paris et Pékin / I. Biraud-Burot in Photo interprétation, vol 41 n° 4 (Novembre 2005)PermalinkChange detection with heterogeneous data using ecoregional stratification, statistical summaries and a land allocation algorithm / K.M. Bergen in Remote sensing of environment, vol 97 n° 4 (15/09/2005)PermalinkCombining spectral and spatial information into hidden Markov models for unsupervised image classification / B. Tso in International Journal of Remote Sensing IJRS, vol 26 n° 10 (May 2005)PermalinkIntegration of spatial and spectral information by means of unsupervised extraction and classification for homogenous objects applied to multispectral and hyperspectral data / L.O. Jimenez in IEEE Transactions on geoscience and remote sensing, vol 43 n° 4 (April 2005)PermalinkSatellite image classification using genetically guided fuzzy clustering with spatial information / S. Bandyopadhyay in International Journal of Remote Sensing IJRS, vol 26 n° 3 (February 2005)PermalinkDetection of land use/land cover changes for the northern part of the Nile delta (Burullus region), Egypt / Kh. M. Dewidar in International Journal of Remote Sensing IJRS, vol 25 n° 20 (October 2004)PermalinkIs the Amik Basin (SE Turkey) a triple-junction area? Analyses of SPOT XS imagery and seismicity / S. Over in International Journal of Remote Sensing IJRS, vol 25 n° 19 (October 2004)PermalinkLe boosting : essai d'une méthode de classification adaptée à la télédétection / David Levrel in Revue internationale de géomatique, vol 14 n° 3 - 4 (septembre 2004 – février 2005)PermalinkTree cover discrimination in panchromatic aerial imagery of Pinyon-Juniper woodlands / J.J. Anderson in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 9 (September 2004)PermalinkUsing Thematic Mapper data for change detection and sustainable use of cultivated land: a case study in the Yellow River delta, China / G.X. Zhao in International Journal of Remote Sensing IJRS, vol 25 n° 13 (July 2004)PermalinkCartographie de la densité du bâti par analyse granulométrique des images de télédetection / Franck Chopin in Revue Française de Photogrammétrie et de Télédétection, n°173-174 (Juin 2004)PermalinkÉtude de l'extension du bâti sur le littoral sénégalais à partir des paramètres texturaux de Haralick / G. Ackermann in Revue Française de Photogrammétrie et de Télédétection, n°173-174 (Juin 2004)PermalinkLand cover characterization of temperate east Asia using multi-temporal vegetation sensor data / S.H. Boles in Remote sensing of environment, vol 90 n° 4 (30/04/2004)PermalinkUsing maximum likelihood (ML) and maximum a prior probability (MAP) in iterative self-organizing data (Isodata) / Hassan A. Karimi in Geocarto international, vol 19 n° 1 (March - May 2004)PermalinkUnsupervised classification of hyperspectral data: an ICA mixture model based approach / Chintan A. Shah in International Journal of Remote Sensing IJRS, vol 25 n° 2 (January 2004)PermalinkTraitement des données de télédétection / Michel-Claude Girard (2004)PermalinkA new maximum-likelihood joint segmentation technique for multitemporal SAR and multiband optical images / P. Lombardo in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)PermalinkA comparison of urban mapping methods using high-resolution digital imagery / N. Thomas in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 9 (September 2003)PermalinkLand-use and land-cover change, urban heat island phenomenon, and health implications: a remote sensing approach / C.P. Lo in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 9 (September 2003)PermalinkSpace mapping the arctic tundra / Gita Laidler in GEO:connexion, vol 2 n° 5 (may 2003)PermalinkSampling method and sampling placement: how do they affect the accuracy of remotely sensed maps? / L. Plourde in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 3 (March 2003)PermalinkUnsupervised classification of radar images using hidden Markov chains and hidden Markov random fields / R. Fjortoft in IEEE Transactions on geoscience and remote sensing, vol 41 n° 3 (March 2003)PermalinkClass-guided building extraction from imagery / D. Scott Lee in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 2 (February /2003)PermalinkApport de la télédétection spatiale à la gestion intégrée du lagon de Saint-Gilles - la Saline à l'Île de la Réunion, un exemple d'application / V. Soti (2003)PermalinkTélédétection THRS / Jean-Charles Pruvost (2003)PermalinkLandscape dynamics of the spread of sudden oak death / M. Kelly in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 10 (October 2002)PermalinkA multiple-cascade-classifier system for a robust and partially unsupervised updating of land-cover maps / Lorenzo Bruzzone in IEEE Transactions on geoscience and remote sensing, vol 40 n° 9 (September 2002)PermalinkTechniques for mapping suburban sprawl / J. Epstein in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 9 (September 2002)PermalinkLarge-area land-cover mapping through scene-based classification compositing / B. Guindon in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 6 (June 2002)PermalinkTextural and contextual land-cover classification using single and multiple classifier systems / O. Debeir in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 6 (June 2002)PermalinkThe role of remote sensing and GIS in enforcement of areas of permanent preservation in the Brazilian Amazon / L.A. Firestone in Geocarto international, vol 17 n° 2 (June - August 2002)PermalinkEstimation interactive de l'indice foliaire à l'échelle régionale par décomposition "sub-pixelaire" du signal Spot4-Végétation / Fabrice Cipriani in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 167 (Avril 2002)PermalinkImagerie spatiale et aménagements forestiers au Gabon / Marcellin Nziengui in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 167 (Avril 2002)PermalinkLinear spectral random mixture analysis for hyperspectral imagery / C.I. Chang in IEEE Transactions on geoscience and remote sensing, vol 40 n° 2 (February 2002)PermalinkScale and texture in digital image classification / J.S. Ferro in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 1 (January 2002)PermalinkA synergic automatic clustering technique (syneract) for multispectral image analysis / K.Y. Huang in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 1 (January 2002)PermalinkUse of knowledge based systems for the detection and monitoring of unplanned developments / Faith Njoki Karanja (2002)PermalinkPositional and shape quality of areal entities in geographic databases: quality information aggregation versus measures classification / Atef Bel Hadj Ali (2001)PermalinkPermalinkFusion de données satellitales basée sur la théorie de Dempster-Shafer pour la cartographie et l'occupation du sol en milieu semi-aride / Mohamed Saber Naceur in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 158 (Avril 2000)PermalinkDéconvolution des signatures spectrales de séries d'images satellitales / Sonia Zine (2000)Permalink