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A multiresolution hierarchical classification algorithm for filtering airborne LiDAR data / Chuanfa Chen in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 82 (August 2013) . - pp 1 - 9 Titre : A multiresolution hierarchical classification algorithm for filtering airborne LiDAR data Type de document : Article/Communication Auteurs : Chuanfa Chen, Auteur Année de publication : 2013 Article en page(s) : pp 1 - 9 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse multirésolution [Termes IGN] classification ascendante hiérarchique [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] filtrage de points [Termes IGN] interpolation [Termes IGN] Kappa de Cohen [Termes IGN] semis de points [Termes IGN] seuillage de points Résumé : (Auteur) We presented a multiresolution hierarchical classification (MHC) algorithm for differentiating ground from non-ground LiDAR point cloud based on point residuals from the interpolated raster surface. MHC includes three levels of hierarchy, with the simultaneous increase of cell resolution and residual threshold from the low to the high level of the hierarchy. At each level, the surface is iteratively interpolated towards the ground using thin plate spline (TPS) until no ground points are classified, and the classified ground points are used to update the surface in the next iteration. 15 groups of benchmark dataset, provided by the International Society for Photogrammetry and Remote Sensing (ISPRS) commission, were used to compare the performance of MHC with those of the 17 other publicized filtering methods. Results indicated that MHC with the average total error and average Cohen’s kappa coefficient of 4.11% and 86.27% performs better than all other filtering methods. Numéro de notice : A2013-407 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.05.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.05.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32545 [article]

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Accurate 3D comparison of complex topography with terrestrial laser scanner: Application to the Rangitikei canyon (N-Z) / Dimitri Lague in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 82 (August 2013) . - pp 10 - 26 Titre : Accurate 3D comparison of complex topography with terrestrial laser scanner: Application to the Rangitikei canyon (N-Z) Type de document : Article/Communication Auteurs : Dimitri Lague, Auteur ; Nicolas Brodu, Auteur ; Jérôme Leroux, Auteur Année de publication : 2013 Article en page(s) : pp 10 - 26 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse comparative [Termes IGN] détection de changement [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] rugosité du sol [Termes IGN] semis de points [Termes IGN] surveillance géologique [Termes IGN] télémétrie laser terrestre [Termes IGN] vallée Résumé : (Auteur) Surveying techniques such as terrestrial laser scanner have recently been used to measure surface changes via 3D point cloud (PC) comparison. Two types of approaches have been pursued: 3D tracking of homologous parts of the surface to compute a displacement field, and distance calculation between two point clouds when homologous parts cannot be defined. This study deals with the second approach, typical of natural surfaces altered by erosion, sedimentation or vegetation between surveys. Current comparison methods are based on a closest point distance or require at least one of the PC to be meshed with severe limitations when surfaces present roughness elements at all scales. To solve these issues, we introduce a new algorithm performing a direct comparison of point clouds in 3D. The method has two steps: (1) surface normal estimation and orientation in 3D at a scale consistent with the local surface roughness; (2) measurement of the mean surface change along the normal direction with explicit calculation of a local confidence interval. Comparison with existing methods demonstrates the higher accuracy of our approach, as well as an easier workflow due to the absence of surface meshing or Digital Elevation Model (DEM) generation. Application of the method in a rapidly eroding, meandering bedrock river (Rangitikei River canyon) illustrates its ability to handle 3D differences in complex situations (flat and vertical surfaces on the same scene), to reduce uncertainty related to point cloud roughness by local averaging and to generate 3D maps of uncertainty levels. We also demonstrate that for high precision survey scanners, the total error budget on change detection is dominated by the point clouds registration error and the surface roughness. Combined with mm-range local georeferencing of the point clouds, levels of detection down to 6 mm (defined at 95% confidence) can be routinely attained in situ over ranges of 50 m. We provide evidence for the self-affine behaviour of different surfaces. We show how this impacts the calculation of normal vectors and demonstrate the scaling behaviour of the level of change detection. The algorithm has been implemented in a freely available open source software package. It operates in complex 3D cases and can also be used as a simpler and more robust alternative to DEM differencing for the 2D cases. Numéro de notice : A2013-408 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.04.009 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.04.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32546 [article]

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Non-linear partial least square regression increases the estimation accuracy of grass nitrogen and phosphorus using in situ hyperspectral and environmental data / Abel Ramoelo in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 82 (August 2013) . - pp 27 - 40 Titre : Non-linear partial least square regression increases the estimation accuracy of grass nitrogen and phosphorus using in situ hyperspectral and environmental data Type de document : Article/Communication Auteurs : Abel Ramoelo, Auteur ; Andrew K. Skidmore, Auteur ; Moses Azong Cho, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 27 - 40 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Afrique du sud (état) [Termes IGN] azote [Termes IGN] données environnementales [Termes IGN] herbe [Termes IGN] image hyperspectrale [Termes IGN] indice de végétation [Termes IGN] parc naturel national [Termes IGN] parcours [Termes IGN] phosphore [Termes IGN] régression non linéaire [Termes IGN] savane Résumé : (Auteur) Grass nitrogen (N) and phosphorus (P) concentrations are direct indicators of rangeland quality and provide imperative information for sound management of wildlife and livestock. It is challenging to estimate grass N and P concentrations using remote sensing in the savanna ecosystems. These areas are diverse and heterogeneous in soil and plant moisture, soil nutrients, grazing pressures, and human activities. The objective of the study is to test the performance of non-linear partial least squares regression (PLSR) for predicting grass N and P concentrations through integrating in situ hyperspectral remote sensing and environmental variables (climatic, edaphic and topographic). Data were collected along a land use gradient in the greater Kruger National Park region. The data consisted of: (i) in situ-measured hyperspectral spectra, (ii) environmental variables and measured grass N and P concentrations. The hyperspectral variables included published starch, N and protein spectral absorption features, red edge position, narrow-band indices such as simple ratio (SR) and normalized difference vegetation index (NDVI). The results of the non-linear PLSR were compared to those of conventional linear PLSR. Using non-linear PLSR, integrating in situ hyperspectral and environmental variables yielded the highest grass N and P estimation accuracy (R2 = 0.81, root mean square error (RMSE) = 0.08, and R2 = 0.80, RMSE = 0.03, respectively) as compared to using remote sensing variables only, and conventional PLSR. The study demonstrates the importance of an integrated modeling approach for estimating grass quality which is a crucial effort towards effective management and planning of protected and communal savanna ecosystems. Numéro de notice : A2013-409 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.04.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.04.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32547 [article]

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3-D voxel-based solid modeling of a broad-leaved tree for accurate volume estimation using portable scanning lidar / Fumiki Hosoi in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 82 (August 2013) . - pp 41 - 48 Titre : 3-D voxel-based solid modeling of a broad-leaved tree for accurate volume estimation using portable scanning lidar Type de document : Article/Communication Auteurs : Fumiki Hosoi, Auteur ; Yohei Nakai, Auteur ; Kenji Omasa, Auteur Année de publication : 2013 Article en page(s) : pp 41 - 48 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre (flore) [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] feuille (végétation) [Termes IGN] modélisation 3D [Termes IGN] solide [Termes IGN] tronc [Termes IGN] volume (grandeur) [Termes IGN] voxel Résumé : (Auteur) We developed a method to produce a 3-D voxel-based solid model of a tree based on portable scanning lidar data for accurate estimation of the volume of the woody material. First, we obtained lidar measurements with a high laser pulse density from several measurement positions around the target, a Japanese zelkova tree. Next, we converted lidar-derived point-cloud data for the target into voxels. The voxel size was 0.5 cm x 0.5 cm x 0.5 cm. Then, we used differences in the spatial distribution of voxels to separate the stem and large branches (diameter > 1 cm) from small branches (diameter Numéro de notice : A2013-410 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.04.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.04.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32548 [article]

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Glacier surface velocity estimation using repeat TerraSAR-X images: Wavelet- vs. correlation-based image matching / Adrian Schubert in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 82 (August 2013) . - pp 49 - 62 Titre : Glacier surface velocity estimation using repeat TerraSAR-X images: Wavelet- vs. correlation-based image matching Type de document : Article/Communication Auteurs : Adrian Schubert, Auteur ; Annina Faes, Auteur ; Andreas Kääb, Auteur ; Erich Meier, Auteur Année de publication : 2013 Article en page(s) : pp 49 - 62 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse comparative [Termes IGN] appariement d'images [Termes IGN] corrélation [Termes IGN] glacier [Termes IGN] image radar moirée [Termes IGN] image TerraSAR-X [Termes IGN] ondelette [Termes IGN] Suisse [Termes IGN] surveillance écologique [Termes IGN] vitesse Résumé : (Auteur) For the observation and monitoring of glacier surface velocity (GSV), remote sensing is an increasingly suitable tool thanks to the high temporal and spatial resolution of the data. Radar sensors have the specific advantage over optical sensors of being nearly weather and time-independent. Two image pairs separated by 11 days, acquired with the high-resolution spotlight (HS) and stripmap (SM) modes of the German sensor TerraSAR-X, were used to estimate GSV over Switzerland’s Aletsch Glacier. The SM mode covers larger ground swaths, making it more suitable for glacier-wide observations, while the HS images cover less area but offer the highest-possible spatial resolution, approximately 1x1 m on the ground. The images were acquired during the summer to maximise feature visibility by minimal snow cover. GSV estimation was performed using two methods, the comparison of which was a major goal of this study: traditional cross-correlation optimisation and a dense image matching algorithm based on complex wavelet decomposition. Each method was found to have unique advantages and disadvantages, but it was concluded that for GSV monitoring, cross-correlation is probably preferable to the wavelet-based approach. While it generates fewer estimates per unit area, this is not necessarily a critical requirement for all glaciological applications, and the method requires less initial “tuning” (calibration) than the wavelet algorithm, making it a slightly better tool in operational contexts. Also, the use of the highest-resolution spotlight datasets is recommended over stripmap mode images when large-area coverage is less critical. The comparative lack of visible features at the resolution of the stripmap images made reliable GSV estimation difficult, with the exception of several small areas dominated by large crevasses. Numéro de notice : A2013-411 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.04.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.04.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32549 [article]

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Analysis of full-waveform LiDAR data for classification of an orange orchard scene / Karolina D. Fieber in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 82 (August 2013) . - pp 63 - 82 Titre : Analysis of full-waveform LiDAR data for classification of an orange orchard scene Type de document : Article/Communication Auteurs : Karolina D. Fieber, Auteur ; Ian J. Davenport, Auteur ; James M. Ferryman, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 63 - 82 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Citrus sinensis [Termes IGN] classification [Termes IGN] données lidar [Termes IGN] lidar à retour d'onde complète [Termes IGN] verger Résumé : (Auteur) Full-waveform laser scanning data acquired with a Riegl LMS-Q560 instrument were used to classify an orange orchard into orange trees, grass and ground using waveform parameters alone. Gaussian decomposition was performed on this data capture from the National Airborne Field Experiment in November 2006 using a custom peak-detection procedure and a trust-region-reflective algorithm for fitting Gauss functions. Calibration was carried out using waveforms returned from a road surface, and the backscattering coefficient Y was derived for every waveform peak. The processed data were then analysed according to the number of returns detected within each waveform and classified into three classes based on pulse width and Y. For single-peak waveforms the scatterplot of Y versus pulse width was used to distinguish between ground, grass and orange trees. In the case of multiple returns, the relationship between first (or first plus middle) and last return Y values was used to separate ground from other targets. Refinement of this classification, and further sub-classification into grass and orange trees was performed using the Y versus pulse width scatterplots of last returns. In all cases the separation was carried out using a decision tree with empirical relationships between the waveform parameters. Ground points were successfully separated from orange tree points. The most difficult class to separate and verify was grass, but those points in general corresponded well with the grass areas identified in the aerial photography. The overall accuracy reached 91%, using photography and relative elevation as ground truth. The overall accuracy for two classes, orange tree and combined class of grass and ground, yielded 95%. Finally, the backscattering coefficient Y of single-peak waveforms was also used to derive reflectance values of the three classes. The reflectance of the orange tree class (0.31) and ground class (0.60) are consistent with published values at the wavelength of the Riegl scanner (1550 nm). The grass class reflectance (0.46) falls in between the other two classes as might be expected, as this class has a mixture of the contributions of both vegetation and ground reflectance properties. Numéro de notice : A2013-412 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.05.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.05.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32550 [article]

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Partial iterates for symmetrizing non-parametric color correction / Bruno Vallet in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 82 (August 2013) . - pp 93 - 101 Titre : Partial iterates for symmetrizing non-parametric color correction Type de document : Article/Communication Auteurs : Bruno Vallet , Auteur ; Lâmân Lelégard , Auteur Année de publication : 2013 Article en page(s) : pp 93 - 101 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classificateur non paramétrique [Termes IGN] correction radiométrique [Termes IGN] luminance lumineuse [Termes IGN] mosaïquage d'images Résumé : (Auteur) Mosaic generation is a central tool in various fields ranging way beyond the scope of photogrammetry and requires the radiometry and color of the images to be corrected. Correction can either be done by a global parametric approach (looking for an optimal gain or gamma for each image of the mosaic), or by iteratively correcting image pairs with a non-parametric approach. Such non-parametric approaches allow for much finer correction but are asymmetric, i.e. they require the choice of a source image that will be corrected to match a target image. Thus the result on the whole mosaic will be very dependant on the order in which images are corrected. In this paper, we propose to use partial iterates to symmetrize non-parametric correction in order to solve this problem. Partial iterates formalize what partially applying a bijective function means and we explain how this can be done in both the continuous and discrete domain. This mechanism is applied to a simple non-parametric approach (histogram transfer of the luminance) to show its potential. Numéro de notice : A2013-413 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.05.005 Date de publication en ligne : 11/06/2013 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.05.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32551 [article]

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Advances in Geographic Object-Based Image Analysis with ontologies: A review of main contributions and limitations from a remote sensing perspective / Damien Arvor in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 82 (August 2013) . - pp 125 - 137 Titre : Advances in Geographic Object-Based Image Analysis with ontologies: A review of main contributions and limitations from a remote sensing perspective Type de document : Article/Communication Auteurs : Damien Arvor, Auteur ; Laurent Durieux, Auteur ; Samuel Andrés, Auteur ; Marie-Angélique Laporte, Auteur Année de publication : 2013 Article en page(s) : pp 125 - 137 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image orientée objet [Termes IGN] interprétation automatique [Termes IGN] objet géographique [Termes IGN] occupation du sol [Termes IGN] ontologie [Termes IGN] photo-interprétation assistée par ordinateur Résumé : (Auteur) Geographic Object-Based Image Analysis (GEOBIA) represents the most innovative new trend for processing remote sensing images that has appeared during the last decade. However, its application is mainly based on expert knowledge, which consequently highlights important scientific issues with respect to the robustness of the methods applied in GEOBIA. In this paper, we argue that GEOBIA would benefit from another technical enhancement involving knowledge representation techniques such as ontologies. Although the role of ontologies in Geographical Information Sciences (GISciences) is not a new topic, few works have discussed how ontologies, considered from the perspective of a remote sensing specialist, can contribute to advancing remote sensing science. We summarize the main applications of ontologies in GEOBIA, especially for data discovery, automatic image interpretation, data interoperability, workflow management and data publication. Finally, we discuss the major issues related to the construction of ontologies suitable for remote sensing applications and outline long-term future advances that can be expected for the remote sensing community. Numéro de notice : A2013-414 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.05.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.05.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32552 [article]

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Multi-feature based boresight self-calibration of a terrestrial mobile mapping system / Ting On Chan in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 82 (August 2013) . - pp 112 - 124 Titre : Multi-feature based boresight self-calibration of a terrestrial mobile mapping system Type de document : Article/Communication Auteurs : Ting On Chan, Auteur ; Derek D. Lichti, Auteur ; Craig L. Glennie, Auteur Année de publication : 2013 Article en page(s) : pp 112 - 124 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] angle de visée [Termes IGN] auto-étalonnage [Termes IGN] compensation par moindres carrés [Termes IGN] étalonnage in situ [Termes IGN] ligne de visée [Termes IGN] semis de points [Termes IGN] système de numérisation mobile Résumé : (Auteur) This paper presents a multi-feature based system calibration method for estimating the boresight angles of a land-based mobile mapping system (MMS) comprised of multiple two dimensional (2D) scanners. The method invokes a least-squares adjustment (LSA) to simultaneously estimate several sets of boresight angles for multiple laser scanners incorporated in an MMS as well as the parameters associated with one or more types of geometric features. This is achieved by constraining the groups of feature point clouds captured by multiple runs to fit their corresponding geometric models in such a way that the weighted sum of squares of adjustment residuals is minimized. The method is particularly suitable for in situ calibration because the geometric features involved are commonly occurring structures (e.g. building façades, bridge surfaces, highway signs and hanging power cables) that are usually captured during the actual survey. In addition to using a planar feature model for calibration, a novel and rigorous three-dimensional (3D) catenary curve model is proposed for geometric modelling of hanging cables to augment the calibration. The proposed calibrations were examined with several different combinations of groups of planar and catenary features and the resulting analysis suggests that the in situ calibrations are effective when compared to the manufacturer’s dedicated calibration, with the overall point cloud accuracies for plane fitting being 5.5 cm and 5.4 cm for the vertical and horizontal directions, respectively. It has been successfully demonstrated that the proposed method can be used in a scene having no building façades but only some long hanging cables and horizontal ground surfaces. This is particularly useful for rural areas or inter-city/provincial highways where building façades cannot commonly be captured. Parameter correlations in the calibrations were also addressed. It has also been shown that using catenary features in addition to planar features for the calibration can help de-correlate some parameters and improve the overall accuracy. The in situ nature and the high flexibility of integrating different features of the calibration make the proposed method straightforward for most end-users. Numéro de notice : A2013-424 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.04.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.04.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32562 [article]

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