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Radargrammetric registration of airborne multi-aspect SAR data of urban areas / Michael Schmitt in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 86 (December 2013) . - pp 11 - 20 Titre : Radargrammetric registration of airborne multi-aspect SAR data of urban areas Type de document : Article/Communication Auteurs : Michael Schmitt, Auteur ; Oliver Maksymiuk, Auteur ; Christophe Magnard, Auteur ; Uwe Stilla, Auteur Année de publication : 2013 Article en page(s) : pp 11 - 20 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] image aérienne [Termes IGN] image radar moirée [Termes IGN] modèle géométrique [Termes IGN] Munich [Termes IGN] radargrammétrie [Termes IGN] superposition d'images [Termes IGN] zone urbaine Résumé : (Auteur) In this paper, the registration of decimeter-resolution airborne multi-aspect SAR (MASAR) data of inner city areas by application of the radargrammetric range-Doppler equations is investigated. The geometrical model is adapted to linear flight trajectories and zero-Doppler processed SAR data, whereas the observed trajectory parameters are adjusted using a strict Gauss–Helmert model and known ground control points. The significance of the estimated corrections is examined and the most suitable set of free parameters is determined. Finally, the methodology is applied to real test data of an airborne campaign over the city of Munich, Germany, and the feasability of the proposed radargrammetric registration method is shown. Numéro de notice : A2013-702 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.09.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.09.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32838 [article]

Automated detection of buildings from single VHR multispectral images using shadow information and graph cuts / Ali Ozgun Ok in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 86 (December 2013) . - pp 21 - 40 Titre : Automated detection of buildings from single VHR multispectral images using shadow information and graph cuts Type de document : Article/Communication Auteurs : Ali Ozgun Ok, Auteur Année de publication : 2013 Article en page(s) : pp 21 - 40 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] détection de régions [Termes IGN] détection du bâti [Termes IGN] image à très haute résolution [Termes IGN] image Geoeye [Termes IGN] image multibande [Termes IGN] ombre [Termes IGN] segmentation d'image Résumé : (Auteur) In this study, we propose a novel methodology for automated detection of buildings from single very-high-resolution (VHR) multispectral images. The methodology uses the principal evidence of buildings: the shadows that they cast. We model the directional spatial relationship between buildings and their shadows using a recently proposed probabilistic landscape approach. An effective shadow post-processing step is developed to focus on landscapes that belong to building regions. The building regions are detected using an original two-level graph theory approach. In the first level, each shadow region is addressed separately, and building regions are identified via iterative graph cuts designed in two-label partitioning. The final building regions are characterised in a second level in which the previously labelled building regions are subjected to a single-step multi-label graph optimisation performed over the entire image domain. Numerical assessments performed on 16 VHR GeoEye-1 images demonstrate that the proposed approach is highly robust and reliable. A distinctive specialty of the proposed approach is its applicability to buildings with diverse characteristics as well as to VHR images with significantly different illumination properties. Numéro de notice : A2013-703 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.09.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.09.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32839 [article]

Change detection in urban areas by object-based analysis and on-the-fly comparison of multi-view ALS data / Marcus Hebel in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 86 (December 2013) . - pp 52 - 64 Titre : Change detection in urban areas by object-based analysis and on-the-fly comparison of multi-view ALS data Type de document : Article/Communication Auteurs : Marcus Hebel, Auteur ; Michael Arens, Auteur ; Uwe Stilla, Auteur Année de publication : 2013 Article en page(s) : pp 52 - 64 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse comparative [Termes IGN] analyse diachronique [Termes IGN] classification de Dempster-Shafer [Termes IGN] détection de changement [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] télémétrie laser aéroporté [Termes IGN] zone urbaine Résumé : (Auteur) The use of helicopters as a sensor platform offers flexible fields of application due to adaptable flying speed at low flight levels. Modern helicopters are equipped with radar altimeters, inertial navigation systems (INS), forward-looking cameras and even laser scanners for automatic obstacle avoidance. If the 3D geometry of the terrain is already available, the analysis of airborne laser scanner (ALS) measurements may also be used for terrain-referenced navigation and change detection. In this paper, we present a framework for on-the-fly comparison of current ALS data to given reference data of an urban area. In contrast to classical difference methods, our approach extends the concept of occupancy grids known from robot mapping. However, it does not blur the measured information onto the grid cells. The proposed change detection method applies the Dempster–Shafer theory to identify conflicting evidence along the laser pulse propagation path. Additional attributes are considered to decide whether detected changes are of man-made origin or occurring due to seasonal effects. The concept of online change detection has been successfully validated in offline experiments with recorded ALS data streams. Results are shown for an urban test site at which multi-view ALS data were acquired at an interval of 1 year. Numéro de notice : A2013-704 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.09.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.09.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32840 [article]

The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques / Chengbin Deng in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 86 (December 2013) . - pp 100 - 110 Titre : The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques Type de document : Article/Communication Auteurs : Chengbin Deng, Auteur ; Changshan Wu, Auteur Année de publication : 2013 Article en page(s) : pp 100 - 110 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse de mélange spectral d’extrémités multiples [Termes IGN] analyse des mélanges spectraux [Termes IGN] apprentissage automatique [Termes IGN] image multibande [Termes IGN] image Terra-MODIS [Termes IGN] méthode des moindres carrés [Termes IGN] surface imperméable [Termes IGN] zone urbaine Résumé : (Auteur) Urban impervious surface information is essential for urban and environmental applications at the regional/national scales. As a popular image processing technique, spectral mixture analysis (SMA) has rarely been applied to coarse-resolution imagery due to the difficulty of deriving endmember spectra using traditional endmember selection methods, particularly within heterogeneous urban environments. To address this problem, we derived endmember signatures through a least squares solution (LSS) technique with known abundances of sample pixels, and integrated these endmember signatures into SMA for mapping large-scale impervious surface fraction. In addition, with the same sample set, we carried out objective comparative analyses among SMA (i.e. fully constrained and unconstrained SMA) and machine learning (i.e. Cubist regression tree and Random Forests) techniques. Analysis of results suggests three major conclusions. First, with the extrapolated endmember spectra from stratified random training samples, the SMA approaches performed relatively well, as indicated by small MAE values. Second, Random Forests yields more reliable results than Cubist regression tree, and its accuracy is improved with increased sample sizes. Finally, comparative analyses suggest a tentative guide for selecting an optimal approach for large-scale fractional imperviousness estimation: unconstrained SMA might be a favorable option with a small number of samples, while Random Forests might be preferred if a large number of samples are available. Numéro de notice : A2013-705 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.09.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.09.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32841 [article]

Automatic detection of a one dimensional ranging pole for robust external camera calibration in mobile mapping / Koen Douterloigne in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 86 (December 2013) . - pp 111 - 123 Titre : Automatic detection of a one dimensional ranging pole for robust external camera calibration in mobile mapping Type de document : Article/Communication Auteurs : Koen Douterloigne, Auteur ; Werner Goeman, Auteur ; Sidharta Gautama, Auteur ; Wilfreid Philips, Auteur Année de publication : 2013 Article en page(s) : pp 111 - 123 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] détection automatique [Termes IGN] étalonnage de capteur (imagerie) [Termes IGN] méthode robuste [Termes IGN] point d'appui [Termes IGN] stadia topographique [Termes IGN] système de numérisation mobile Résumé : (Auteur) A mobile mapping system (MMS) is the answer of the geoinformation community to the exponentially growing demand for various geospatial data with increasingly higher accuracies, captured by multiple sensors. As the mobile mapping technology is pushed to explore its use for various applications on water, rail, or road, the need emerges to have an external sensor calibration procedure that is portable, fast and easy to perform. This way, sensors can be mounted and demounted depending on the application requirements without the need for time consuming calibration procedures. A new methodology is presented to provide a high quality external calibration of cameras which is automatic, robust and fool proof. The method uses a portable, standard ranging pole which needs to be positioned on a known ground control point. While the literature focuses on solving the absolute orientation problem of the calibration, an automatic method to detect the calibration object is missing. Here, we present a mutual information based image registration technique for automatic sub-pixel localization of the ranging pole under realistic outdoor conditions. We include several robust error detection rules to allow the calibration to run without human intervention, giving as little outliers as possible, to ensure a correct calibration. Several tests are performed under various lighting and noise conditions which prove the methodology’s robustness. Numéro de notice : A2013-706 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.09.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.09.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32842 [article]

Photogrammetric modeling of the relative orientation in underwater environments / Gili Telem in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 86 (December 2013) . - pp 150 - 156 Titre : Photogrammetric modeling of the relative orientation in underwater environments Type de document : Article/Communication Auteurs : Gili Telem, Auteur ; Sagi Filin, Auteur Année de publication : 2013 Article en page(s) : pp 150 - 156 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] compensation par faisceaux [Termes IGN] coplanarité [Termes IGN] espace objet [Termes IGN] orientation relative [Termes IGN] photogrammétrie métrologique [Termes IGN] photogrammétrie sous-marine [Termes IGN] photogrammétrie terrestre Résumé : (Auteur) Underwater photogrammetry provides an efficient means for documentation of environments which are complex and have limited accessibility. Yet the establishment of reference control networks in such settings is oftentimes difficult. In this regard, use of the coplanarity condition, which requires neither knowledge of object space coordinates nor setting a reference control network, seems to be an attractive solution. However, the coplanarity relation does not hold in such environments because of the refraction effect, and methods that have been proposed thus far for geometrical modeling of its effect require knowledge of object-space quantities. Thus, this paper proposes a geometrically-driven approach which fulfills the coplanarity condition and thereby requires no knowledge of object space data. Such an approach may prove useful not only for object space reconstruction but also as a preparatory step for application of bundle block adjustment and for outlier detection. All are key features in photogrammetric practices. Results show that no unique setup is needed for estimating the relative orientation parameters using the model and that high levels of accuracy can be achieved. Numéro de notice : A2013-707 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32843 [article]

Gaussian processes uncertainty estimates in experimental Sentinel-2 LAI and leaf chlorophyll content retrieval / Jochem Verrlest in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 86 (December 2013) . - pp 157 - 167 Titre : Gaussian processes uncertainty estimates in experimental Sentinel-2 LAI and leaf chlorophyll content retrieval Type de document : Article/Communication Auteurs : Jochem Verrlest, Auteur ; Juan Pablo Rivera, Auteur ; José Moreno, Auteur ; Gustavo Camps-Valls, Auteur Année de publication : 2013 Article en page(s) : pp 157 - 167 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme de Gauss [Termes IGN] apprentissage automatique [Termes IGN] chlorophylle [Termes IGN] image Sentinel-MSI [Termes IGN] incertitude des données [Termes IGN] indice foliaire [Termes IGN] Leaf Area Index [Termes IGN] régression [Termes IGN] surveillance de la végétation [Termes IGN] teneur en chlorophylle des feuilles [Termes IGN] variable biophysique (végétation) Résumé : (Auteur) ESA’s upcoming Sentinel-2 (S2) Multispectral Instrument (MSI) foresees to provide continuity to land monitoring services by relying on optical payload with visible, near infrared and shortwave infrared sensors with high spectral, spatial and temporal resolution. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods, which ideally should provide uncertainty intervals for the predictions. Statistical learning regression algorithms are powerful candidats for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. In this paper, we focus on a new emerging technique in the field of Bayesian nonparametric modeling. We exploit Gaussian process regression (GPR) for retrieval, which is an accurate method that also provides uncertainty intervals along with the mean estimates. This distinct feature is not shared by other machine learning approaches. In view of implementing the regressor into operational monitoring applications, here the portability of locally trained GPR models was evaluated. Experimental data came from the ESA-led field campaign SPARC (Barrax, Spain). For various simulated S2 configurations (S2-10m, S2-20m and S2-60m) two important biophysical parameters were estimated: leaf chlorophyll content (LCC) and leaf area index (LAI). Local evaluation of an extended training dataset with more variation over bare soil sites led to improved LCC and LAI mapping with reduced uncertainties. GPR reached the 10% precision required by end users, with for LCC a NRMSE of 3.5–9.2% (r2: 0.95–0.99) and for LAI a NRMSE of 6.5–7.3% (r2: 0.95–0.96). The developed GPR models were subsequently applied to simulated Sentinel images over various sites. The associated uncertainty maps proved to be a good indicator for evaluating the robustness of the retrieval performance. The generally low uncertainty intervals over vegetated surfaces suggest that the locally trained GPR models are portable to other sites and conditions. Numéro de notice : A2013-708 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.09.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.09.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32844 [article]