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Fusion of waveform LiDAR data and hyperspectral imagery for land cover classification / Hongzhou Wang in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 1 - 11 Titre : Fusion of waveform LiDAR data and hyperspectral imagery for land cover classification Type de document : Article/Communication Auteurs : Hongzhou Wang, Auteur ; Craig L. Glennie, Auteur Année de publication : 2015 Article en page(s) : pp 1 - 11 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] classification par maximum de vraisemblance [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] données lidar [Termes IGN] extraction de traits caractéristiques [Termes IGN] forme d'onde pleine [Termes IGN] fusion d'images [Termes IGN] fusion de données [Termes IGN] image hyperspectrale [Termes IGN] occupation du sol [Termes IGN] onde lidar [Termes IGN] semis de points [Termes IGN] superposition d'images [Termes IGN] voxel Résumé : (auteur) Current research into the fusion of hyperspectral imagery (HI) and full waveform LiDAR (Light Detection And Ranging) has relied on first processing the full waveform LiDAR (FWL) data to a set of discrete returns before merging because the data structure and sampling interval of HI and FWL are distinctly different. However, additional information about target properties can potentially be recovered if the waveform shape is preserved in the fusion process. This paper proposes a “voxelization” method to register FWL data to HI by dividing the waveform data into voxels, and then synthesizing all waveforms which intersect a voxel column into one three-dimensional superposition waveform: the synthesized waveform (SWF). A vertical energy distribution coefficients (VEDC) feature is proposed for extracting features from SWF, and then the SWF and HI are fused to form a complete feature space for classification. A pairwise classifier was adapted and completed using both Maximum Likelihood and Support Vector Machine classifiers for the combined SWF/HI features. Results show that this method of generating SWF from FWL data can effectively preserve information from the original waveforms, and the fusion of SWF and HI enhanced land cover classification compared to both using either data set alone or the merging of HI with a discrete LiDAR return point cloud. Numéro de notice : A2015-848 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.05.012 Date de publication en ligne : 23/06/2015 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.05.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79218 [article]

Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 12 – 32 Titre : Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas Type de document : Article/Communication Auteurs : Timothy Dube, Auteur ; Onisimo Mutanga, Auteur Année de publication : 2015 Article en page(s) : pp 12 – 32 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] Afrique du sud (état) [Termes IGN] biodiversité [Termes IGN] biomasse aérienne [Termes IGN] biomasse forestière [Termes IGN] classification [Termes IGN] classification dirigée [Termes IGN] espèce végétale [Termes IGN] Eucalyptus dunii [Termes IGN] Eucalyptus grandis [Termes IGN] image Landsat-8 [Termes IGN] image Landsat-OLI [Termes IGN] Pinus taeda [Termes IGN] régression [Termes IGN] sous-étage [Termes IGN] sylviculture [Termes IGN] texture d'image Résumé : (auteur) The successful launch of the 30-m Landsat-8 Operational Land Imager (OLI) pushbroom sensor offers a new primary data source necessary for aboveground biomass (AGB) estimation, especially in resource-limited environments. In this work, the strength and performance of Landsat-8 OLI image derived texture metrics (i.e. texture measures and texture ratios) in estimating plantation forest species AGB was investigated. It was hypothesized that the sensor’s pushbroom design, coupled with the presence of refined spectral properties, enhanced radiometric resolution (i.e. from 8 bits to 12 bits) and improved signal-to-noise ratio have the potential to provide detailed spectral information necessary for significantly strengthening AGB estimation in medium-density forest canopies. The relationship between image texture metrics and measurements of forest attributes can be used to help characterize complex forests, and enhance fine vegetation biophysical properties, a difficult challenge when using spectral vegetation indices especially in closed canopies. This study examines the prospects of using Landsat-8 OLI sensor derived texture metrics for estimating AGB for three medium-density plantation forest species in KwaZulu Natal, South Africa. In order to achieve this objective, three unique data pre-processing techniques were tested (analysis I: Landsat-8 OLI raw spectral-bands vs. raw texture bands; analysis II: Landsat-8 OLI raw spectral-band ratios vs. texture band ratios and analysis III: Landsat-8 OLI derived vegetation indices vs. texture band ratios). The landsat-8 OLI derived texture parameters were examined for robustness in estimating AGB using linear regression, stepwise-multiple linear regression and stochastic gradient boosting regression models. The results of this study demonstrated that all texture parameters particularly band texture ratios calculated using a 3 × 3 window size, could enhance AGB estimation when compared to simple spectral reflectance, simple band ratios and the most popular spectral vegetation indices. For instance, the use of combined texture ratios yielded the highest R2 values of 0.76 (RMSE = 9.55 t ha−1 (18.07%) and CV-RMSE of 0.18); 0.74 (RMSE = 12.81 t ha−1 (17.72%) and CV-RMSE of 0.08); 0.74 (RMSE = 12.67 t ha−1 (06.15%) and CV-RMSE of 0.06) and 0.53 (RMSE = 20.15 t ha−1 (14.40%) and CV-RMSE of 0.15) overall for Eucalyptus dunii, Eucalyptus grandis, Pinus taeda individually and all species, respectively. Overall, the findings of this study provide the necessary insight and motivation to the remote sensing community, particularly in resource constrained regions, to shift towards embracing various texture metrics obtained from the readily-available and cheap multispectral Landsat-8 OLI sensor. Numéro de notice : A2015-849 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.002 Date de publication en ligne : 25/06/2015 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.06.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79219 [article]

Leveraging in-scene spectra for vegetation species discrimination with MESMA-MDA / Brian D. Bue in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 33 - 48 Titre : Leveraging in-scene spectra for vegetation species discrimination with MESMA-MDA Type de document : Article/Communication Auteurs : Brian D. Bue, Auteur ; David R. Thompson, Auteur ; R. Glenn Sellar, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 33 - 48 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse de mélange spectral d’extrémités multiples [Termes IGN] analyse discriminante [Termes IGN] espèce végétale [Termes IGN] image hyperspectrale [Termes IGN] réflectance végétale [Termes IGN] signature spectrale [Termes IGN] spectromètre imageur Résumé : (auteur) We describe an approach to improve Multiple Endmember Spectral Mixture Analysis (MESMA) results for applications involving discrimination among spectrally-similar species, and commonly occur in multispectral and hyperspectral vegetation remote sensing studies. Such applications are inherently difficult, due to the high degree of similarity between distinct species, coupled with potentially high intra-species variability caused by factors such as growing conditions, canopy structure, ambient illumination, or substrate characteristics. We describe a method to map spectra to a feature space where distinctions between plant species are emphasized using a transformation based on Multiclass Discriminant Analysis. We compute this transformation using groups of pixels that represent individual plant canopies similar to the endmembers in MESMA’s spectral library, and describe a technique to automatically select such spectra from a given image. Compared to conventional MESMA, and also to several alternative MESMA formulations, we observe up to twofold increases in accuracy, along with a factor of ten reduction in computation time using our MESMA approach in several species discrimination applications. We demonstrate the effectiveness of our approach for agricultural species discrimination applications using spectra captured by two different imaging spectrometers. Numéro de notice : A2015-850 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.06.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79220 [article]

Stochastic geometrical model and Monte Carlo optimization methods for building reconstruction from InSAR data / Yue Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 49 – 61 Titre : Stochastic geometrical model and Monte Carlo optimization methods for building reconstruction from InSAR data Type de document : Article/Communication Auteurs : Yue Zhang, Auteur ; Xuan Sun, Auteur ; Antje Thiele, Auteur ; Stefan Hinz, Auteur Année de publication : 2015 Article en page(s) : pp 49 – 61 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] image radar moirée [Termes IGN] image TanDEM-X [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] méthode de Monte-Carlo [Termes IGN] modèle stochastique [Termes IGN] optimisation (mathématiques) [Termes IGN] reconstruction 3D du bâti Résumé : (auteur) Synthetic aperture radar (SAR) systems, such as TanDEM-X, TerraSAR-X and Cosmo-SkyMed, acquire imagery with high spatial resolution (HR), making it possible to observe objects in urban areas with high detail. In this paper, we propose a new top-down framework for three-dimensional (3D) building reconstruction from HR interferometric SAR (InSAR) data. Unlike most methods proposed before, we adopt a generative model and utilize the reconstruction process by maximizing a posteriori estimation (MAP) through Monte Carlo methods. The reason for this strategy refers to the fact that the noisiness of SAR images calls for a thorough prior model to better cope with the inherent amplitude and phase fluctuations. In the reconstruction process, according to the radar configuration and the building geometry, a 3D building hypothesis is mapped to the SAR image plane and decomposed to feature regions such as layover, corner line, and shadow. Then, the statistical properties of intensity, interferometric phase and coherence of each region are explored respectively, and are included as region terms. Roofs are not directly considered as they are mixed with wall into layover area in most cases. When estimating the similarity between the building hypothesis and the real data, the prior, the region term, together with the edge term related to the contours of layover and corner line, are taken into consideration. In the optimization step, in order to achieve convergent reconstruction outputs and get rid of local extrema, special transition kernels are designed. The proposed framework is evaluated on the TanDEM-X dataset and performs well for buildings reconstruction. Numéro de notice : A2015-851 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.004 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.06.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79221 [article]

Distinctive order based self-similarity descriptor for multi-sensor remote sensing image matching / Amin Sedaghat in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 62 – 71 Titre : Distinctive order based self-similarity descriptor for multi-sensor remote sensing image matching Type de document : Article/Communication Auteurs : Amin Sedaghat, Auteur ; Hamid Ebadi, Auteur Année de publication : 2015 Article en page(s) : pp 62 – 71 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement d'images [Termes IGN] extraction automatique [Termes IGN] image Geoeye [Termes IGN] image IRS [Termes IGN] image Landsat-ETM+ [Termes IGN] image multicapteur [Termes IGN] image Quickbird [Termes IGN] image SPOT 4 [Termes IGN] image SPOT 5 [Termes IGN] image SPOT 6 [Termes IGN] image Terra-ASTER [Termes IGN] image Worldview [Termes IGN] invariant [Termes IGN] SIFT (algorithme) Résumé : (auteur) Robust, well-distributed and accurate feature matching in multi-sensor remote sensing image is a difficult task duo to significant geometric and illumination differences. In this paper, a robust and effective image matching approach is presented for multi-sensor remote sensing images. The proposed approach consists of three main steps. In the first step, UR-SIFT (Uniform robust scale invariant feature transform) algorithm is applied for uniform and dense local feature extraction. In the second step, a novel descriptor namely Distinctive Order Based Self Similarity descriptor, DOBSS descriptor, is computed for each extracted feature. Finally, a cross matching process followed by a consistency check in the projective transformation model is performed for feature correspondence and mismatch elimination. The proposed method was successfully applied for matching various multi-sensor satellite images as: ETM+, SPOT 4, SPOT 5, ASTER, IRS, SPOT 6, QuickBird, GeoEye and Worldview sensors, and the results demonstrate its robustness and capability compared to common image matching techniques such as SIFT, PIIFD, GLOH, LIOP and LSS. Numéro de notice : A2015-852 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.06.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79222 [article]

Improved wide-angle, fisheye and omnidirectional camera calibration / Steffen Urban in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 72 – 79 Titre : Improved wide-angle, fisheye and omnidirectional camera calibration Type de document : Article/Communication Auteurs : Steffen Urban, Auteur ; Jens Leitloff, Auteur ; Stefan Hinz, Auteur Année de publication : 2015 Article en page(s) : pp 72 – 79 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] étalonnage de capteur (imagerie) [Termes IGN] objectif grand angulaire [Termes IGN] orientation du capteur intégrée Résumé : (auteur) In this paper an improved method for calibrating wide-angle, fisheye and omnidirectional imaging systems is presented. We extend the calibration procedure proposed by Scaramuzza et al. by replacing the residual function and joint refinement of all parameters. In doing so, we achieve a more stable, robust and accurate calibration (up to factor 7) and can reduce the number of necessary calibration steps from five to three. After introducing the camera model and highlighting the differences from the current calibration procedure, we perform a comprehensive performance evaluation using several data sets and show the impact of the proposed calibration procedure on the calibration results. Numéro de notice : A2015-853 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.06.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79223 [article]