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Multi-label class assignment in land-use modelling / Hichem Omrani in International journal of geographical information science IJGIS, vol 29 n° 6 (June 2015)
[article]
Titre : Multi-label class assignment in land-use modelling Type de document : Article/Communication Auteurs : Hichem Omrani, Auteur ; Fahed Abdallah, Auteur ; Omar Charif, Auteur Année de publication : 2015 Article en page(s) : pp 1023 - 1041 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] alignement semi-dirigé
[Termes IGN] analyse multivariée
[Termes IGN] apprentissage automatique
[Termes IGN] classification barycentrique
[Termes IGN] image aérienne
[Termes IGN] Luxembourg
[Termes IGN] modélisation
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] utilisation du solRésumé : (Auteur) During the last two decades, a variety of models have been applied to understand and predict changes in land use. These models assign a single-attribute label to each spatial unit at any particular time of the simulation. This is not realistic because mixed use of land is quite common. A more detailed classification allowing the modelling of mixed land use would be desirable for better understanding and interpreting the evolution of the use of land. A possible solution is the multi-label (ML) concept where each spatial unit can belong to multiple classes simultaneously. For example, a cluster of summer houses at a lake in a forested area should be classified as water, forest and residential (built-up). The ML concept was introduced recently, and it belongs to the machine learning field. In this article, the ML concept is introduced and applied in land-use modelling. As a novelty, we present a land-use change model that allows ML class assignment using the k nearest neighbour (kNN) method that derives a functional relationship between land use and a set of explanatory variables. A case study with a rich data-set from Luxembourg using biophysical data from aerial photography is described. The model achieves promising results based on the well-known ML evaluation criteria. The application described in this article highlights the value of the multi-label k nearest neighbour method (MLkNN) for land-use modelling. Numéro de notice : A2015-599 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1008004 En ligne : https://doi.org/10.1080/13658816.2015.1008004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78013
in International journal of geographical information science IJGIS > vol 29 n° 6 (June 2015) . - pp 1023 - 1041[article]The soil moisture active passive validation experiment 2012 (SMAPVEX12): Prelaunch calibration and validation of the SMAP Soil moisture algorithms / Heather McNairn in IEEE Transactions on geoscience and remote sensing, vol 53 n° 5 (mai 2015)
[article]
Titre : The soil moisture active passive validation experiment 2012 (SMAPVEX12): Prelaunch calibration and validation of the SMAP Soil moisture algorithms Type de document : Article/Communication Auteurs : Heather McNairn, Auteur ; Thomas J. Jackson, Auteur ; Grant Wiseman, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 2784 - 2801 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] analyse de données
[Termes IGN] bande L
[Termes IGN] étalonnage
[Termes IGN] étalonnage de capteur (imagerie)
[Termes IGN] humidité du sol
[Termes IGN] image aérienne
[Termes IGN] image radar
[Termes IGN] Soil Moisture Active Passive
[Termes IGN] télédétection en hyperfréquence
[Termes IGN] test de performanceRésumé : (auteur) The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite is scheduled for launch in January 2015. In order to develop robust soil moisture retrieval algorithms that fully exploit the unique capabilities of SMAP, algorithm developers had identified a need for long-duration combined active and passive L-band microwave observations. In response to this need, a joint Canada-U.S. field experiment (SMAPVEX12) was conducted in Manitoba (Canada) over a six-week period in 2012. Several times per week, NASA flew two aircraft carrying instruments that could simulate the observations the SMAP satellite would provide. Ground crews collected soil moisture data, crop measurements, and biomass samples in support of this campaign. The objective of SMAPVEX12 was to support the development, enhancement, and testing of SMAP soil moisture retrieval algorithms. This paper details the airborne and field data collection as well as data calibration and analysis. Early results from the SMAP active radar retrieval methods are presented and demonstrate that relative and absolute soil moisture can be delivered by this approach. Passive active L-band sensor (PALS) antenna temperatures and reflectivity, as well as backscatter, closely follow dry down and wetting events observed during SMAPVEX12. The SMAPVEX12 experiment was highly successful in achieving its objectives and provides a unique and valuable data set that will advance algorithm development. Numéro de notice : A2015-631 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2364913 En ligne : https://doi.org/10.1109/TGRS.2014.2364913 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78119
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 5 (mai 2015) . - pp 2784 - 2801[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015051 RAB Revue Centre de documentation En réserve L003 Disponible Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)
[article]
Titre : Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery Type de document : Article/Communication Auteurs : Gang Chen, Auteur ; Margaret R. Metz, Auteur ; David M. Rizzo, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 38 - 47 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse en composantes principales
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] délimitation
[Termes IGN] houppier
[Termes IGN] image à ultra haute résolution
[Termes IGN] image aérienne
[Termes IGN] image MASTER
[Termes IGN] impact sur l'environnement
[Termes IGN] incendie de forêt
[Termes IGN] maladie phytosanitaire
[Termes IGN] réflectance végétaleRésumé : (auteur) Forest ecosystems are subject to a variety of disturbances with increasing intensities and frequencies, which may permanently change the trajectories of forest recovery and disrupt the ecosystem services provided by trees. Fire and invasive species, especially exotic disease-causing pathogens and insects, are examples of disturbances that together could pose major threats to forest health. This study examines the impacts of fire and exotic disease (sudden oak death) on forests, with an emphasis on the assessment of post-fire burn severity in a forest where trees have experienced three stages of disease progression pre-fire: early-stage (trees retaining dried foliage and fine twigs), middle-stage (trees losing fine crown fuels), and late-stage (trees falling down). The research was conducted by applying Geographic Object-Based Image Analysis (GEOBIA) to MASTER airborne images that were acquired immediately following the fire for rapid assessment and contained both high-spatial (4 m) and high-spectral (50 bands) resolutions. Although GEOBIA has gradually become a standard tool for analyzing high-spatial resolution imagery, high-spectral resolution data (dozens to hundreds of bands) can dramatically reduce computation efficiency in the process of segmentation and object-based variable extraction, leading to complicated variable selection for succeeding modeling. Hence, we also assessed two widely used band reduction algorithms, PCA (principal component analysis) and MNF (minimum noise fraction), for the delineation of image objects and the subsequent performance of burn severity models using either PCA or MNF derived variables. To increase computation efficiency, only the top 5 PCA and MNF and top 10 PCA and MNF components were evaluated, which accounted for 10% and 20% of the total number of the original 50 spectral bands, respectively. Results show that if no band reduction was applied the models developed for the three stages of disease progression had relatively similar performance, where both spectral responses and texture contributed to burn assessments. However, the application of PCA and MNF introduced much greater variation among models across the three stages. For the early-stage disease progression, neither band reduction algorithms improved or retained the accuracy of burn severity modeling (except for the use of 10 MNF components). Compared to the no-band-reduction scenario, band reduction led to a greater level of overestimation of low-degree burns and underestimation of medium-degree burns, suggesting that the spectral variation removed by PCA and MNF was vital for distinguishing between the spectral reflectance from disease-induced dried crowns (still retaining high structural complexity) and fire ash. For the middle-stage, both algorithms improved the model R2 values by 2–37%, while the late-stage models had comparable or better performance to those using the original 50 spectral bands. This could be explained by the loss of tree crowns enabling better signal penetration, thus leading to reduced spectral variation from canopies. Hence, spectral bands containing a high degree of random noise were correctly removed by the band reduction algorithms. Compared to the middle-stage, the late-stage forest stands were covered by large piles of fallen trees and branches, resulting in higher variability of MASTER imagery. The ability of band reduction to improve the model performance for these late-stage forest stands was reduced, because the valuable spectral variation representing the actual late-stage forest status was partially removed by both algorithms as noise. Our results indicate that PCA and MNF are promising for balancing computation efficiency and the performance of burn severity models in forest stands subject to the middle and late stages of sudden oak death disease progression. Compared to PCA, MNF dramatically reduced image spectral variation, generating larger image objects with less complexity of object shapes. Whereas, PCA-based models delivered superior performance in most evaluated cases suggesting that some key spectral variability contributing to the accuracy of burn severity models in diseased forests may have been removed together with true spectral noise through MNF transformations. Numéro de notice : A2015-475 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.01.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.01.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77183
in ISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 38 - 47[article]Oblique aerial image acquisition, 3D city modeling, 3D city guide project for Konya metropolitan municipality / Tuncer Ozerbil in International journal of 3-D information modeling, vol 4 n° 2 (April - June 2015)
[article]
Titre : Oblique aerial image acquisition, 3D city modeling, 3D city guide project for Konya metropolitan municipality Type de document : Article/Communication Auteurs : Tuncer Ozerbil, Auteur ; Ergun Gokten, Auteur ; Mustafa Onder, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp34 - 37 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] CityGML
[Termes IGN] image aérienne à axe vertical
[Termes IGN] image aérienne oblique
[Termes IGN] intégration de données
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] Oracle
[Termes IGN] système d'information géographique
[Termes IGN] TurquieRésumé : (auteur) Usage of aerial oblique cameras and oblique images in generation of 3D city models has become popular all over the world in recent years and various solutions has been developed involving specialized methods and softwares. The first comprehensive step in this field was taken by Konya Metropolitan Municipality in Turkey in 2012 and the project undertaken by GEOGIS has been successfully completed in Februaty 2014. It is the fast Lime in Turkey that 3D city model of this large scale has been generated. The project involves: Aerial image acquisition of the project area with vertical and oblique cameras respectively and photogrammetric triangulation; Development of OttoPenta software, which can display oblique images in pentaview screen, make spatial queries and also can measure the horizontal, vertical distance and area; Digitization of roof and roof structures from vertical stereo images using photogrammetric intertetation techniques and generation of 3D solid building models using this data; Assigning building ID numbers to solid models to integrate with the GIS data of the Municipality that is available in Oracle Spatial database; Automatic texturing of 3D models with oblique images; Exporting of textuted 3D models into Oracle Spatial Database in CityGML format, complying the OGC standards; and development of KNVCity software, to create and publish the 3D city guide on WEB and mobile devices. The goal of this paper is sharing the experience and knowledge that was gained during the 3D City modeling and 3D city guide project which was performed for the first time in Turkey. Numéro de notice : A2015-586 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.4018/IJ3DIM.2015040103 En ligne : http://doi.org/10.4018/IJ3DIM.2015040103 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77862
in International journal of 3-D information modeling > vol 4 n° 2 (April - June 2015) . - pp34 - 37[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 138-2015021 RAB Revue Centre de documentation En réserve L003 Disponible A physics-based unmixing method to estimate subpixel temperatures on mixed pixels / Manuel Cubero-Castan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
[article]
Titre : A physics-based unmixing method to estimate subpixel temperatures on mixed pixels Type de document : Article/Communication Auteurs : Manuel Cubero-Castan, Auteur ; Jocelyn Chanussot, Auteur ; Véronique Achard, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 1894 - 1906 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] emissivité
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] image TASI
[Termes IGN] méthode des moindres carrés
[Termes IGN] rayonnement infrarouge thermique
[Termes IGN] température de luminanceRésumé : (Auteur) This paper presents a new algorithm for the analysis of linear spectral mixtures in the thermal infrared domain, with the goal to jointly estimate the abundance and the subpixel temperature in a mixed pixel, i.e., to estimate the relative proportion and the temperature of each material composing the mixed pixel. This novel approach is a two-step procedure. First, it estimates the emissivity and the temperature over pure pixels using the standard temperature and emissivity separation (TES) algorithm. Second, it estimates the abundance and the subpixel temperature using a new unmixing physics-based model, called Thermal Remote sensing Unmixing for Subpixel Temperature (TRUST). This model is based on an estimator of the subpixel temperature obtained by linearizing the black body law around the mean temperature of each material. The abundance is then retrieved by minimizing the reconstruction error with the estimation of the subpixel temperatures. The TRUST method is benchmarked on simulated scenes against the fully constrained least squares unmixing applied on the radiance and on the estimation of surface emissivity using the TES algorithm. The TRUST method shows better results on pure and mixed pixels composed of two materials. TRUST also shows promising results when applied on thermal hyperspectral data acquired with the Thermal Airborne Spectrographic Imager during the Detection in Urban scenario using Combined Airborne imaging Sensors campaign and estimates coherent localization of mixed-pixel areas. Numéro de notice : A2015-172 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2350771 Date de publication en ligne : 15/09/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2350771 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75890
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 1894 - 1906[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015041 RAB Revue Centre de documentation En réserve L003 Disponible Training set size, scale, and features in Geographic Object-Based Image Analysis of very high resolution unmanned aerial vehicle imagery / Lei Ma in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)PermalinkLocating control points in aerial images with a multi-scale approach based on terrestrial image patches / Adilson Berveglieri in Photogrammetric record, vol 30 n° 149 (March - May 2015)PermalinkLe SIG prend de la hauteur / Fanny Perrin d'Arloz in SIGmag, n° 4 (mars 2015)PermalinkCapabilities of BIOMASS tomography for investigating tropical forests / Ho Tong Minh Dinh in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)PermalinkLiDAR strip adjustment using multifeatures matched with aerial images / Yongjun Zhang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)PermalinkPermalinkData-driven feature learning for high resolution urban land-cover classification / Piotr Andrzej Tokarczyk (2015)PermalinkEssential Earth imaging for GIS / Lawrence Fox III (2015)PermalinkEstimation of the mean tree height of forest stands by photogrammetric measurement using digital aerial images of high spatial resolution / Ivan Balenović in Annals of forest research, vol 58 n° 1 (January 2015)PermalinkImproved land cover mapping using aerial photographs and satellite images / Katalin Varga in Open geosciences, vol 7 n° 1 (January 2015)Permalink