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Assessment of the image misregistration effects on object-based change detection / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 19 - 27 Titre : Assessment of the image misregistration effects on object-based change detection Type de document : Article/Communication Auteurs : Gang Chen, Auteur ; Kaiguang Zhao, Auteur ; Ryan Powers, Auteur Année de publication : 2014 Article en page(s) : pp 19 - 27 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse diachronique [Termes IGN] classification orientée objet [Termes IGN] détection de changement [Termes IGN] estimation de précision [Termes IGN] image multitemporelle [Termes IGN] image SPOT 5 Résumé : (Auteur) High-spatial resolution remote sensing imagery provides unique opportunities for detailed characterization and monitoring of landscape dynamics. To better handle such data sets, change detection using the object-based paradigm, i.e., object-based change detection (OBCD), have demonstrated improved performances over the classic pixel-based paradigm. However, image registration remains a critical pre-process, with new challenges arising, because objects in OBCD are of various sizes and shapes. In this study, we quantified the effects of misregistration on OBCD using high-spatial resolution SPOT 5 imagery (5 m) for three types of landscapes dominated by urban, suburban and rural features, representing diverse geographic objects. The experiments were conducted in four steps: (i) Images were purposely shifted to simulate the misregistration effect. (ii) Image differencing change detection was employed to generate difference images with all the image-objects projected to a feature space consisting of both spectral and texture variables. (iii) The changes were extracted using the Mahalanobis distance and a change ratio. (iv) The results were compared to the ‘real’ changes from the image pairs that contained no purposely introduced registration error. A pixel-based change detection method using similar steps was also developed for comparisons. Results indicate that misregistration had a relatively low impact on object size and shape for most areas. When the landscape is comprised of small mean object sizes (e.g., in urban and suburban areas), the mean size of ‘change’ objects was smaller than the mean of all objects and their size discrepancy became larger with the decrease in object size. Compared to the results using the pixel-based paradigm, OBCD was less sensitive to the misregistration effect, and the sensitivity further decreased with an increase in local mean object size. However, high-spatial resolution images typically have higher spectral variability within neighboring pixels than the relatively low resolution datasets. As a result, accurate image registration remains crucial to change detection even if an object-based approach is used. Numéro de notice : A2014-008 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32913 [article]

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Deriving leaf mass per area (LMA) from foliar reflectance across a variety of plant species using continuous wavelet analysis / Tao Cheng in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 28 - 38 Titre : Deriving leaf mass per area (LMA) from foliar reflectance across a variety of plant species using continuous wavelet analysis Type de document : Article/Communication Auteurs : Tao Cheng, Auteur ; Benoit Rivard, Auteur ; Arturo G. Sanchez-Azofeifa, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 28 - 38 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] biomasse [Termes IGN] espèce végétale [Termes IGN] indice foliaire [Termes IGN] Leaf Mass per Area [Termes IGN] modèle physique [Termes IGN] ondelette [Termes IGN] réflectance végétale [Termes IGN] réponse spectrale [Termes IGN] transformation en ondelettes Résumé : (Auteur) Leaf mass per area (LMA), the ratio of leaf dry mass to leaf area, is a trait of central importance to the understanding of plant light capture and carbon gain. It can be estimated from leaf reflectance spectroscopy in the infrared region, by making use of information about the absorption features of dry matter. This study reports on the application of continuous wavelet analysis (CWA) to the estimation of LMA across a wide range of plant species. We compiled a large database of leaf reflectance spectra acquired within the framework of three independent measurement campaigns (ANGERS, LOPEX and PANAMA) and generated a simulated database using the PROSPECT leaf optical properties model. CWA was applied to the measured and simulated databases to extract wavelet features that correlate with LMA. These features were assessed in terms of predictive capability and robustness while transferring predictive models from the simulated database to the measured database. The assessment was also conducted with two existing spectral indices, namely the Normalized Dry Matter Index (NDMI) and the Normalized Difference index for LMA (NDLMA). Five common wavelet features were determined from the two databases, which showed significant correlations with LMA (R2: 0.51–0.82, p Numéro de notice : A2014-009 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.009 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32914 [article]

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Integrating environmental variables and WorldView-2 image data to improve the prediction and mapping of Thaumastocoris peregrinus (bronze bug) damage in plantation forests / Zakariyyaa Oumar in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 39 - 46 Titre : Integrating environmental variables and WorldView-2 image data to improve the prediction and mapping of Thaumastocoris peregrinus (bronze bug) damage in plantation forests Type de document : Article/Communication Auteurs : Zakariyyaa Oumar, Auteur ; Onisimo Mutanga, Auteur Année de publication : 2014 Article en page(s) : pp 39 - 46 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Afrique du sud (état) [Termes IGN] Araneae [Termes IGN] carte de la végétation [Termes IGN] dommage matériel [Termes IGN] Eucalyptus (genre) [Termes IGN] image Worldview [Termes IGN] rayonnement proche infrarouge Résumé : (Auteur) This study integrated environmental variables together with high spectral resolution WorldView-2 imagery to detect and map Thaumastocoris peregrinus damage in Eucalypt plantation forests in KwaZulu-Natal, South Africa. The WorldView-2 bands, vegetation indices and environmental variables were entered separately into PLS regression models to predict T. peregrinus damage. The datasets were then integrated to test the collective strength in predicting T. peregrinus damage. Important variables were identified by variable importance (VIP) scores and were re-entered into a PLS regression model. The VIP model was then extrapolated to map the severity of damage and predicted T. peregrinus damage with an R2 value of 0.71 and a RMSE of 3.26% on an independent test dataset. The red edge and near-infrared bands of the WorldView-2 sensor together with the temperature dataset were identified as important variables in predicting T. peregrinus damage. The results indicate the potential of integrating WorldView-2 data and environmental variables to improve the mapping and monitoring of insect outbreaks in plantation forests. The result is critical for plantation health monitoring using a new sensor which contains important vegetation wavelengths. Numéro de notice : A2014-010 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32915 [article]

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An algorithm for automatic detection of pole-like street furniture objects from Mobile Laser Scanner point clouds / C. Cabo in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 47 - 56 Titre : An algorithm for automatic detection of pole-like street furniture objects from Mobile Laser Scanner point clouds Type de document : Article/Communication Auteurs : C. Cabo, Auteur ; C. Ordonez, Auteur ; S. Garcia-Cortés, Auteur ; J. Martinez, Auteur Année de publication : 2014 Article en page(s) : pp 47 - 56 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] détection automatique [Termes IGN] discrétisation [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] mobilier urbain [Termes IGN] semis de points [Termes IGN] voxel Résumé : (Auteur) An algorithm for automatic extraction of pole-like street furniture objects using Mobile Laser Scanner data was developed and tested. The method consists in an initial simplification of the point cloud based on the regular voxelization of the space. The original point cloud is spatially discretized and a version of the point cloud whose amount of data represents 20–30% of the total is created. All the processes are carried out with the reduced version of the data, but the original point cloud is always accessible without any information loss, as each point is linked to its voxel. All the horizontal sections of the voxelized point cloud are analyzed and segmented separately. The two-dimensional fragments compatible with a section of a target pole are selected and grouped. Finally, the three-dimensional voxel representation of the detected pole-like objects is identified and the points from the original point cloud belonging to each pole-like object are extracted. The algorithm can be used with data from any Mobile Laser Scanning system, as it transforms the original point cloud and fits it into a regular grid, thus avoiding irregularities produced due to point density differences within the point cloud. The algorithm was tested in four test sites with different slopes and street shapes and features. All the target pole-like objects were detected, with the only exception of those severely occluded by large objects and some others which were either attached or too close to certain features. Numéro de notice : A2014-011 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.008 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32916 [article]

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EarthEnv-DEM90: A nearly-global, void-free, multi-scale smoothed, 90m digital elevation model from fused ASTER and SRTM data / Natalie Robinson in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 57 - 67 Titre : EarthEnv-DEM90: A nearly-global, void-free, multi-scale smoothed, 90m digital elevation model from fused ASTER and SRTM data Type de document : Article/Communication Auteurs : Natalie Robinson, Auteur ; James Regetz, Auteur ; Robert P. Guralnick, Auteur Année de publication : 2014 Article en page(s) : pp 57 - 67 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie spatiale [Termes IGN] filtrage du bruit [Termes IGN] fusion de données [Termes IGN] image Terra-ASTER [Termes IGN] lissage de données [Termes IGN] MNS SRTM [Termes IGN] modèle numérique mondial de surface Résumé : (Auteur) A variety of DEM products are available to the public at no cost, though all are characterized by trade-offs in spatial coverage, data resolution, and quality. The absence of a high-resolution, high-quality, well-described and vetted, free, global consensus product was the impetus for the creation of a new DEM product described here, ‘EarthEnv-DEM90’. This new DEM is a compilation dataset constructed via rigorous techniques by which ASTER GDEM2 and CGIAR-CSI v4.1 products were fused into a quality-enhanced, consistent grid of elevation estimates that spans ?91% of the globe. EarthEnv-DEM90 was assembled using methods for seamlessly merging input datasets, thoroughly filling voids, and smoothing data irregularities (e.g. those caused by DEM noise) from the approximated surface. The result is a DEM product in which elevational artifacts are strongly mitigated from the input data fusion zone, substantial voids are filled in the northern-most regions of the globe, and the entire DEM exhibits reduced terrain noise. As important as the final product is a well defined methodology, along with new processing techniques and careful attention to final outputs, that extends the value and usability of the work beyond just this single product. Finally, we outline EarthEnv-DEM90 acquisition instructions and metadata availability, so that researchers can obtain this high-resolution, high-quality, nearly-global new DEM product for the study of wide-ranging global phenomena. Numéro de notice : A2014-012 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.11.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.11.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32917 [article]

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Maximum-likelihood estimation for multi-aspect multi-baseline SAR interferometry of urban areas / Michael Schmitt in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 68 - 77 Titre : Maximum-likelihood estimation for multi-aspect multi-baseline SAR interferometry of urban areas Type de document : Article/Communication Auteurs : Michael Schmitt, Auteur ; Uwe Stilla, Auteur Année de publication : 2014 Article en page(s) : pp 68 - 77 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] classification par maximum de vraisemblance [Termes IGN] image aérienne [Termes IGN] image radar moirée [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] matrice de covariance [Termes IGN] milieu urbain [Termes IGN] modèle numérique de surface [Termes IGN] Munich [Termes IGN] reconstruction 3D Résumé : (Auteur) The reconstruction of digital surface models (DSMs) of urban areas from interferometric synthetic aperture radar (SAR) data is a challenging task. In particular the SAR inherent layover and shadowing effects need to be coped with by sophisticated processing strategies. In this paper, a maximum-likelihood estimation procedure for the reconstruction of DSMs from multi-aspect multi-baseline InSAR imagery is proposed. In this framework, redundant as well as contradicting observations are exploited in a statistically optimal way. The presented method, which is especially suited for single-pass SAR interferometers, is examined using test data consisting of experimental airborne millimeterwave SAR imagery. The achievable accuracy is evaluated by comparison to LiDAR-derived reference data. It is shown that the proposed estimation procedure performs better than a comparable non-statistical reconstruction method. Numéro de notice : A2014-013 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32918 [article]

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081-2014011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Fusion 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)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 78 - 92 Titre : Fusion of airborne laserscanning point clouds and images for supervised and unsupervised scene classification Type de document : Article/Communication Auteurs : Markus Gerke, Auteur ; Jing Xiao, Auteur Année de publication : 2014 Article en page(s) : pp 78 - 92 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] champ aléatoire de Markov [Termes IGN] classification dirigée [Termes IGN] classification non dirigée [Termes IGN] classification par arbre de décision [Termes IGN] conflation [Termes IGN] densification [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] semis de points [Termes IGN] toit [Termes IGN] voxel Résumé : (Auteur) Automatic urban object detection from airborne remote sensing data is essential to process and efficiently interpret the vast amount of airborne imagery and Laserscanning (ALS) data available today. This paper combines ALS data and airborne imagery to exploit both: the good geometric quality of ALS and the spectral image information to detect the four classes buildings, trees, vegetated ground and sealed ground. A new segmentation approach is introduced which also makes use of geometric and spectral data during classification entity definition. Geometric, textural, low level and mid level image features are assigned to laser points which are quantified into voxels. The segment information is transferred to the voxels and those clusters of voxels form the entity to be classified. Two classification strategies are pursued: a supervised method, using Random Trees and an unsupervised approach, embedded in a Markov Random Field framework and using graph-cuts for energy optimization. A further contribution of this paper concerns the image-based point densification for building roofs which aims to mitigate the accuracy problems related to large ALS point spacing. Results for the ISPRS benchmark test data show that to rely on color information to separate vegetation from non-vegetation areas does mostly lead to good results, but in particular in shadow areas a confusion between classes might occur. The unsupervised classification strategy is especially sensitive in this respect. As far as the point cloud densification is concerned, we observe similar sensitivity with respect to color which makes some planes to be missed out, or false detections still remain. For planes where the densification is successful we see the expected enhancement of the outline. Numéro de notice : A2014-014 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32919 [article]

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Using mobile laser scanning data for automated extraction of road markings / Haiyan Guan in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 93 - 107 Titre : Using mobile laser scanning data for automated extraction of road markings Type de document : Article/Communication Auteurs : Haiyan Guan, Auteur ; Jonathan Li, Auteur ; Yongtao Yu, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 93 - 107 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] densité des points [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction automatique [Termes IGN] interpolation inversement proportionnelle à la distance [Termes IGN] morphologie mathématique [Termes IGN] semis de points [Termes IGN] seuillage de points [Termes IGN] signalisation routière Résumé : (Auteur) A mobile laser scanning (MLS) system allows direct collection of accurate 3D point information in unprecedented detail at highway speeds and at less than traditional survey costs, which serves the fast growing demands of transportation-related road surveying including road surface geometry and road environment. As one type of road feature in traffic management systems, road markings on paved roadways have important functions in providing guidance and information to drivers and pedestrians. This paper presents a stepwise procedure to recognize road markings from MLS point clouds. To improve computational efficiency, we first propose a curb-based method for road surface extraction. This method first partitions the raw MLS data into a set of profiles according to vehicle trajectory data, and then extracts small height jumps caused by curbs in the profiles via slope and elevation-difference thresholds. Next, points belonging to the extracted road surface are interpolated into a geo-referenced intensity image using an extended inverse-distance-weighted (IDW) approach. Finally, we dynamically segment the geo-referenced intensity image into road-marking candidates with multiple thresholds that correspond to different ranges determined by point-density appropriate normality. A morphological closing operation with a linear structuring element is finally used to refine the road-marking candidates by removing noise and improving completeness. This road-marking extraction algorithm is comprehensively discussed in the analysis of parameter sensitivity and overall performance. An experimental study performed on a set of road markings with ground-truth shows that the proposed algorithm provides a promising solution to the road-marking extraction from MLS data. Numéro de notice : A2014-015 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.11.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.11.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32920 [article]

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Hierarchical extraction of landslides from multiresolution remotely sensed optical images / Camille Kurtz in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 122 - 136 Titre : Hierarchical extraction of landslides from multiresolution remotely sensed optical images Type de document : Article/Communication Auteurs : Camille Kurtz, Auteur ; André Stumpf, Auteur ; Jean-Philippe Malet, Auteur ; Pierre Gançarski, Auteur ; Anne Puissant, Auteur ; Nicolas Passat, Auteur Année de publication : 2014 Article en page(s) : pp 122 - 136 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Barcelonnette [Termes IGN] corrélation par régions de niveaux de gris [Termes IGN] effondrement de terrain [Termes IGN] image à résolution submétrique [Termes IGN] image à ultra haute résolution [Termes IGN] image Landsat-TM [Termes IGN] image optique [Termes IGN] image RapidEye [Termes IGN] modèle numérique de terrain [Termes IGN] niveau de détail [Termes IGN] segmentation d'image Résumé : (Auteur) The automated detection and mapping of landslides from Very High Resolution (VHR) images present several challenges related to the heterogeneity of landslide sizes, shapes and soil surface characteristics. However, a common geomorphological characteristic of landslides is to be organized with a series of embedded and scaled features. These properties motivated the use of a multiresolution image analysis approach for their detection. In this work, we propose a hybrid segmentation/classification region-based method, devoted to this specific issue. The method, which uses images of the same area at various spatial resolutions (Medium to Very High Resolution), relies on a recently introduced top-down hierarchical framework. In the specific context of landslide analysis, two main novelties are introduced to enrich this framework. The first novelty consists of using non-spectral information, obtained from Digital Terrain Model (DTM), as a priori knowledge for the guidance of the segmentation/classification process. The second novelty consists of using a new domain adaptation strategy, that allows to reduce the expert’s interaction when handling large image datasets. Experiments performed on satellite images acquired over terrains affected by landslides demonstrate the efficiency of the proposed method with different hierarchical levels of detail addressing various operational needs. Numéro de notice : A2014-016 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.11.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.11.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32921 [article]

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Contextual classification of lidar data and building object detection in urban areas / Joachim Niemeyer in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 152 - 165 Titre : Contextual classification of lidar data and building object detection in urban areas Type de document : Article/Communication Auteurs : Joachim Niemeyer, Auteur ; Franz Rottensteiner, Auteur ; Uwe Soergel, Auteur Année de publication : 2014 Article en page(s) : pp 152 - 165 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] champ aléatoire de Markov [Termes IGN] classification contextuelle [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] détection du bâti [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] milieu urbain [Termes IGN] reconstruction 3D du bâti [Termes IGN] semis de points Résumé : (Auteur) In this work we address the task of the contextual classification of an airborne LiDAR point cloud. For that purpose, we integrate a Random Forest classifier into a Conditional Random Field (CRF) framework. It is a flexible approach for obtaining a reliable classification result even in complex urban scenes. In this way, we benefit from the consideration of context on the one hand and from the opportunity to use a large amount of features on the other hand. Considering the interactions in our experiments increases the overall accuracy by 2%, though a larger improvement becomes apparent in the completeness and correctness of some of the seven classes discerned in our experiments. We compare the Random Forest approach to linear models for the computation of unary and pairwise potentials of the CRF, and investigate the relevance of different features for the LiDAR points as well as for the interaction of neighbouring points. In a second step, building objects are detected based on the classified point cloud. For that purpose, the CRF probabilities for the classes are plugged into a Markov Random Field as unary potentials, in which the pairwise potentials are based on a Potts model. The 2D binary building object masks are extracted and evaluated by the benchmark ISPRS Test Project on Urban Classification and 3D Building Reconstruction. The evaluation shows that the main buildings (larger than 50 m2) can be detected very reliably with a correctness larger than 96% and a completeness of 100%. Numéro de notice : A2014-017 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.11.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.11.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32922 [article]

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081-2014011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Assessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping / Luca Demarchi in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 166 - 179 Titre : Assessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping Type de document : Article/Communication Auteurs : Luca Demarchi, Auteur ; Frank Canters, Auteur ; Claude Cariou, Auteur ; Giorgio Licciardi, Auteur ; Jonathan Cheung-Wai Chan, Auteur Année de publication : 2014 Article en page(s) : pp 166 - 179 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Airborne Prism Experiment [Termes IGN] carte d'occupation du sol [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par réseau neuronal [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] image APEX [Termes IGN] image hyperspectrale [Termes IGN] Perceptron multicouche Résumé : (Auteur) Despite the high richness of information content provided by airborne hyperspectral data, detailed urban land-cover mapping is still a challenging task. An important topic in hyperspectral remote sensing is the issue of high dimensionality, which is commonly addressed by dimensionality reduction techniques. While many studies focus on methodological developments in data reduction, less attention is paid to the assessment of the proposed methods in detailed urban hyperspectral land-cover mapping, using state-of-the-art image classification approaches. In this study we evaluate the potential of two unsupervised data reduction techniques, the Autoassociative Neural Network (AANN) and the BandClust method – the first a transformation based approach, the second a feature-selection based approach – for mapping of urban land cover at a high level of thematic detail, using an APEX 288-band hyperspectral dataset. Both methods were tested in combination with four state-of-the-art machine learning classifiers: Random Forest (RF), AdaBoost (ADB), the multiple layer perceptron (MLP), and support vector machines (SVM). When used in combination with a strong learner (MLP, SVM) BandClust produces classification accuracies similar to or higher than obtained with the full dataset, demonstrating the method’s capability of preserving critical spectral information, required for the classifier to successfully distinguish between the 22 urban land-cover classes defined in this study. In the AANN data reduction process, on the other hand, important spectral information seems to be compromised or lost, resulting in lower accuracies for three of the four classifiers tested. Detailed analysis of accuracies at class level confirms the superiority of the SVM/Bandclust combination for accurate urban land-cover mapping using a reduced hyperspectral dataset. This study also demonstrates the potential of the new APEX sensor data for detailed mapping of land cover in spatially and spectrally complex urban areas. Numéro de notice : A2014-018 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32923 [article]

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Geographic Object-Based Image Analysis: Towards a new paradigm / Thomas Blaschke in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 180 - 191 Titre : Geographic Object-Based Image Analysis: Towards a new paradigm Type de document : Article/Communication Auteurs : Thomas Blaschke, Auteur ; Geoffrey Hay, Auteur ; Maggi Kelly, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 180 - 191 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse d'image numérique [Termes IGN] classification [Termes IGN] information sémantique [Termes IGN] modèle orienté objet [Termes IGN] objet géographique [Termes IGN] ontologie [Termes IGN] pixel [Termes IGN] segmentation d'image Résumé : (Auteur) The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the ‘per-pixel paradigm’ and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm. Numéro de notice : A2014-019 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.09.014 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.09.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32924 [article]

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081-2014011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

An innovative support vector machine based method for contextual image classification / Rogério Galante Negri in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 241 - 248 Titre : An innovative support vector machine based method for contextual image classification Type de document : Article/Communication Auteurs : Rogério Galante Negri, Auteur ; Luciano Vieira Dutra, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 241 - 248 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] classification contextuelle [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] image ALOS-PALSAR [Termes IGN] image radar moirée Résumé : (Auteur) Several remote sensing studies have adopted the Support Vector Machine (SVM) method for image classification. Although the original formulation of the SVM method does not incorporate contextual information, there are different proposals to incorporate this type of information into it. Usually, these proposals modify the SVM training phase or make an integration of SVM classifications using stochastic models. This study presents a new perspective on the development of contextual SVMs. The main concept of this proposed method is to use the contextual information to displace the separation hyperplane, initially defined by the traditional SVM. This displaced hyperplane could cause a change of the class initially assigned to the pixel. To evaluate the classification effectiveness of the proposed method a case study is presented comparing the results with the standard SVM and the SVM post-processed by the mode (majority) filter. An ALOS/PALSAR image, PLR mode, acquired over an Amazon area was used in the experiment. Considering the inner area of test sites, the accuracy results obtained by the proposed method is better than SVM and similar to SVM post-processed by the mode filter. The proposed method, however, produces better results than mode post-processed SVM when considering the classification near the edges between regions. One drawback of the method is the computational cost of the proposed method is significantly greater than the compared methods. Numéro de notice : A2014-020 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.11.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.11.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32925 [article]

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081-2014011	RAB	Revue	Centre de documentation	En réserve L003	Disponible