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Near real-time flood detection in urban and rural areas using high-resolution synthetic aperture radar images / D.C. Mason in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3041 - 3052 Titre : Near real-time flood detection in urban and rural areas using high-resolution synthetic aperture radar images Type de document : Article/Communication Auteurs : D.C. Mason, Auteur ; Ian J. Davenport, Auteur ; J.C. Neal, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 3041 - 3052 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] Angleterre [Termes IGN] détection [Termes IGN] image TerraSAR-X [Termes IGN] inondation [Termes IGN] temps réel [Termes IGN] zone rurale [Termes IGN] zone urbaine Résumé : (Auteur) A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high-resolution synthetic aperture radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high-resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, classifying 89% of flooded pixels correctly, with an associated false positive rate of 6%. Of the urban water pixels visible to TerraSAR-X, 75% were correctly detected, with a false positive rate of 24%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 57% and 18%, respectively. Numéro de notice : A2012-380 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2178030 Date de publication en ligne : 21/02/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2178030 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31826 [article]

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Evaluating classification techniques for mapping vertical geology using field-based hyperspectral sensors / R.J. Murphy in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3066 - 3080 Titre : Evaluating classification techniques for mapping vertical geology using field-based hyperspectral sensors Type de document : Article/Communication Auteurs : R.J. Murphy, Auteur ; S. Monteiro, Auteur ; S. Schneider, Auteur Année de publication : 2012 Article en page(s) : pp 3066 - 3080 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Australie occidentale (Australie) [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] classification Spectral angle mapper [Termes IGN] image aérienne [Termes IGN] image hyperspectrale [Termes IGN] mine [Termes IGN] ombre Résumé : (Auteur) Hyperspectral data acquired from field-based platforms present new challenges for their analysis, particularly for complex vertical surfaces exposed to large changes in the geometry and intensity of illumination. The use of hyperspectral data to map rock types on a vertical mine face is demonstrated, with a view to providing real-time information for automated mining applications. The performance of two classification techniques, namely, spectral angle mapper (SAM) and support vector machines (SVMs), is compared rigorously using a spectral library acquired under various conditions of illumination. SAM and SVM are then applied to a mine face, and results are compared with geological boundaries mapped in the field. Effects of changing conditions of illumination, including shadow, were investigated by applying SAM and SVM to imagery acquired at different times of the day. As expected, classification of the spectral libraries showed that, on average, SVM gave superior results for SAM, although SAM performed better where spectra were acquired under conditions of shadow. In contrast, when applied to hypserspectral imagery of a mine face, SVM did not perform as well as SAM. Shadow, through its impact upon spectral curve shape and albedo, had a profound impact on classification using SAM and SVM. Numéro de notice : A2012-381 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2178419 Date de publication en ligne : 03/02/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2178419 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31827 [article]

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Satellite image time series analysis under time warping / F. Petitjean in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3081 - 3095 Titre : Satellite image time series analysis under time warping Type de document : Article/Communication Auteurs : F. Petitjean, Auteur ; Jordi Inglada, Auteur ; Pierre Gançarski, Auteur Année de publication : 2012 Article en page(s) : pp 3081 - 3095 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse de groupement [Termes IGN] déformation temporelle dynamique (algorithme) [Termes IGN] échantillon [Termes IGN] image optique [Termes IGN] série temporelle Résumé : (Auteur) Satellite Image Time Series are becoming increasingly available and will continue to do so in the coming years thanks to the launch of space missions which aim at providing a coverage of the Earth every few days with high spatial resolution. In the case of optical imagery, it will be possible to produce land use and cover change maps with detailed nomenclatures. However, due to meteorological phenomena, such as clouds, these time series will become irregular in terms of temporal sampling, and one will need to compare time series with different lengths. In this paper, we present an approach to image time series analysis which is able to deal with irregularly sampled series and which also allows the comparison of pairs of time series where each element of the pair has a different number of samples. We present the dynamic time warping from a theoretical point of view and illustrate its capabilities with two applications to real-time series. Numéro de notice : A2012-382 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2179050 Date de publication en ligne : 31/01/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2179050 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31828 [article]

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Memory-based cluster sampling for remote sensing image classification / Michele Volpi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3096 - 3106 Titre : Memory-based cluster sampling for remote sensing image classification Type de document : Article/Communication Auteurs : Michele Volpi, Auteur ; Devis Tuia, Auteur ; Mikhail Kanevski, Auteur Année de publication : 2012 Article en page(s) : pp 3096 - 3106 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse de groupement [Termes IGN] apprentissage automatique [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] image à très haute résolution [Termes IGN] image hyperspectrale Résumé : (Auteur) In this paper, we address the problem of semi-automatic definition of training sets for the classification of remotely sensed images. We propose two approaches based on active learning aiming at removing both the proximal (low diversity) and the dense (low exploration during iterations) sampling redundancies. The first is encountered when several samples carrying similar spectral information are selected by the algorithm, while the second occurs when the heuristic is unable to explore undiscovered parts of the feature space during iterations. For this purpose, kernel k-means is used to cluster a set of uncertain candidates in the same space spanned by the kernel function defined in the SVM classification step. Two heuristics are proposed to maximize the speed of convergence to high classification accuracies: The first is based on binary hierarchical partitioning of the set of selected uncertain samples, while the second extends this approach by considering memory in the selection and thus dynamically adapts to the problem throughout the iterations. Experiments on both VHR and hyperspectral imagery confirm fast convergence of the algorithm, that outperforms state-of-the-art sampling schemes. Numéro de notice : A2012-383 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2179661 Date de publication en ligne : 21/02/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2179661 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31829 [article]

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Local coregistration adjustment for anomalous change detection / J. Theiler in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3107 - 3116 Titre : Local coregistration adjustment for anomalous change detection Type de document : Article/Communication Auteurs : J. Theiler, Auteur ; B. Wohlberg, Auteur Année de publication : 2012 Article en page(s) : pp 3107 - 3116 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] détection de changement [Termes IGN] image hyperspectrale [Termes IGN] image multibande [Termes IGN] imprécision géométrique [Termes IGN] scène [Termes IGN] superposition d'images Résumé : (Auteur) We describe an approach for improving the robustness to misregistration of pixel-wise anomalous change detection (ACD) algorithms. The aim of ACD is to distinguish actual anomalous changes from the irrelevant incidental differences that occur throughout the scene. For such change detection to be effective, it is important that corresponding pixels in the two images of interest correspond to the same location in the scene. Indeed, one of the most confounding sources of incidental differences is the inevitable imprecision in the coregistration of the two images. We address this with small local adjustments to the coregistration which leads to a modified misregistration-insensitive measure of anomalousness. Several variants are considered, and the resulting performance improvements are evaluated using both real and simulated changes, and real and simulated misregistration. Numéro de notice : A2012-384 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2179942 Date de publication en ligne : 31/01/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2179942 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31830 [article]

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Automatic detection and segmentation of orchards using very high resolution imagery / Selim Aksoy in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3117 - 3131 Titre : Automatic detection and segmentation of orchards using very high resolution imagery Type de document : Article/Communication Auteurs : Selim Aksoy, Auteur ; I. Yalniz, Auteur ; K. Tasdemir, Auteur Année de publication : 2012 Article en page(s) : pp 3117 - 3131 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse texturale [Termes IGN] détection automatique [Termes IGN] image à très haute résolution [Termes IGN] image Ikonos [Termes IGN] image optique [Termes IGN] image Quickbird [Termes IGN] segmentation d'image [Termes IGN] Turquie [Termes IGN] verger Résumé : (Auteur) Spectral information alone is often not sufficient to distinguish certain terrain classes such as permanent crops like orchards, vineyards, and olive groves from other types of vegetation. However, instances of these classes possess distinctive spatial structures that can be observable in detail in very high spatial resolution images. This paper proposes a novel unsupervised algorithm for the detection and segmentation of orchards. The detection step uses a texture model that is based on the idea that textures are made up of primitives (trees) appearing in a near-regular repetitive arrangement (planting patterns). The algorithm starts with the enhancement of potential tree locations by using multi-granularity isotropic filters. Then, the regularity of the planting patterns is quantified using projection profiles of the filter responses at multiple orientations. The result is a regularity score at each pixel for each granularity and orientation. Finally, the segmentation step iteratively merges neighboring pixels and regions belonging to similar planting patterns according to the similarities of their regularity scores and obtains the boundaries of individual orchards along with estimates of their granularities and orientations. Extensive experiments using Ikonos and QuickBird imagery as well as images taken from Google Earth show that the proposed algorithm provides good localization of the target objects even when no sharp boundaries exist in the image data. Numéro de notice : A2012-385 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2180912 Date de publication en ligne : 31/01/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2180912 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31831 [article]

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Stable target detection and coherence estimation in interferometric SAR stacks / P. Guccione in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3171 - 3178 Titre : Stable target detection and coherence estimation in interferometric SAR stacks Type de document : Article/Communication Auteurs : P. Guccione, Auteur ; A. Monti-Guarnieri, Auteur Année de publication : 2012 Article en page(s) : pp 3171 - 3178 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] artefact [Termes IGN] coin réflecteur [Termes IGN] détection de cible [Termes IGN] image radar moirée [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] polarisation [Termes IGN] qualité des données Résumé : (Auteur) We propose a novel method to select long-term coherent targets from a set of repeated-pass interferometric acquisitions. The major assumption is that targets are so close together to share the same optical path. This leads to an efficient singular-value-decomposition-based estimator of the targets' phase and, then, to PS detection. The estimated phase can be used to define the PS coherence for each image. Being sensitive to acquisition and processing artifacts, the PS coherence is a valuable tool for quality assessment of the interferometric stack. Results are shown with real data sets in both single and full polarizations. Numéro de notice : A2012-386 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2178246 Date de publication en ligne : 18/01/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2178246 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31832 [article]

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TOPS interferometry with TerraSAR-X / Pau Prats-Iraola in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3179 - 3188 Titre : TOPS interferometry with TerraSAR-X Type de document : Article/Communication Auteurs : Pau Prats-Iraola, Auteur ; Rolf Scheiber, Auteur ; L. Marotti, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 3179 - 3188 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] image radar moirée [Termes IGN] image TerraSAR-X [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] superposition d'images Résumé : (Auteur) This paper presents results on SAR interferometry for data acquired in the Terrain Observation by Progressive Scans (TOPS) imaging mode. The rationale to retrieve accurate interferometric products in this mode is expounded, emphasizing the critical step of coregistration. Due to the particularities of the TOPS mode, a high Doppler centroid is present at burst edges, demanding a very high azimuth coregistration performance. A coregistration accuracy of around one tenth of a pixel, as it is usually recommended for stripmap interferometric data, could result in large undesired azimuth phase ramps in each TOPS burst. This paper presents two approaches based on the spectral diversity technique to precisely estimate this coregistration offset with the required accuracy and evaluates their performance. The effect of squint at burst edges in terms of an undesired impulse response shift during focusing and the impact on the interferometric coregistration performance is also addressed. Repeat-pass TOPS data acquired experimentally by TerraSAR-X are used to validate the proposed approaches. Numéro de notice : A2012-387 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2178246 Date de publication en ligne : 18/01/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2178246 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31833 [article]

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The TropiSAR airborne campaign in French Guiana : objectives, description, and observed temporal behavior of the backscatter signal / P. Dubois-Fernandez in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3228 - 3241 Titre : The TropiSAR airborne campaign in French Guiana : objectives, description, and observed temporal behavior of the backscatter signal Type de document : Article/Communication Auteurs : P. Dubois-Fernandez, Auteur ; Thuy Le Toan, Auteur ; S. Daniel, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 3228 - 3241 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande P [Termes IGN] biomasse [Termes IGN] forêt tropicale [Termes IGN] Guyane (département français) [Termes IGN] image aérienne [Termes IGN] image radar moirée [Termes IGN] image SETHI [Termes IGN] polarisation croisée [Termes IGN] qualité radiométrique (image) Résumé : (Auteur) The TropiSAR campaign has been conducted in August 2009 in French Guiana with the ONERA airborne radar system SETHI. The main objective of this campaign was to collect data to support the Phase A of the 7th Earth Explorer candidate mission, BIOMASS. Several specific questions needed to be addressed to consolidate the mission concept following the Phase 0 studies, and the data collection strategy was constructed accordingly. More specifically, a tropical forest data set was required in order to provide test data for the evaluation of the foreseen inversion algorithms and data products. The paper provides a description of the resulting data set which is now available through the European Space Agency website under the airborne campaign link. First results from the TropiSAR database analysis are presented with two in-depth analyses about both the temporal radiometric variation and temporal coherence at P-band. The temporal variations of the backscatter values are less than 0.5 dB throughout the campaign, and the coherence values are observed to stay high even after 22 days. These results are essential for the BIOMASS mission. The observed temporal stability of the backscatter is a good indicator of the expected robustness of the biomass estimation in tropical forests, from cross-polarized backscatter values as regarding environmental changes such as soil moisture. The high temporal coherence observed after a 22-day period is a prerequisite for SAR Polarimetric Interferometry and Tomographic applications in a single satellite configuration. The conclusion then summarizes the paper and identifies the next steps in the analysis. Numéro de notice : A2012-388 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2178246 Date de publication en ligne : 18/01/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2178246 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31834 [article]

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A robust signal preprocessing chain for small-footprint waveform LiDAR / J. Wu in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3242 - 3255 Titre : A robust signal preprocessing chain for small-footprint waveform LiDAR Type de document : Article/Communication Auteurs : J. Wu, Auteur ; Jan Van Aardt, Auteur ; J. Mcglinchy, Auteur ; Gregory P. Asner, Auteur Année de publication : 2012 Article en page(s) : pp 3242 - 3255 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Afrique du sud (état) [Termes IGN] biomasse [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] étalonnage [Termes IGN] forme d'onde [Termes IGN] lasergrammétrie [Termes IGN] prétraitement du signal [Termes IGN] savane [Termes IGN] signal lidar Résumé : (Auteur) The extraction of structural object metrics from a next-generation remote sensing modality, namely waveform Light Detection and Ranging (LiDAR), has garnered increasing interest from the remote sensing research community. However, the raw incoming (received) LiDAR waveform typically exhibits a stretched, misaligned, and relatively distorted character. In other words, the LiDAR signal is smeared and the effective temporal (vertical) resolution decreases, which is attributed to a fixed time span allocated for detection, the sensor's variable outgoing pulse signal, off-nadir scanning, the receiver impulse response impacts, and system noise. Theoretically, such a loss of resolution and increased data ambiguity can be remediated by using proven signal preprocessing approaches. In this paper, we present a robust signal preprocessing chain for waveform LiDAR calibration, which includes noise reduction, deconvolution, waveform registration, and angular rectification. This preprocessing chain was initially validated using simulated waveform data, which were derived via the digital imaging and remote sensing image generation modeling environment. We also verified the approach using real small-footprint waveform LiDAR data collected by the Carnegie Airborne Observatory in a savanna region of South Africa and specifically in terms of modeling woody biomass in this region. Metrics, including the spectral angle for cross-section recovery assessment and goodness-of-fit (R2) statistics, along with the root-mean-squared error for woody biomass estimation, were used to provide a comprehensive quantitative evaluation of the performance of this preprocessing chain. Results showed that our approach significantly increased our ability to recover the temporal signal resolution, improved geometric rectification of raw waveform LiDAR, and resulted in improved waveform-based woody biomass estimation. This preprocessing chain has the potential to be applied across the board for h- gh fidelity processing of small-footprint waveform LiDAR data, thereby facilitating the extraction of valid and useful structural metrics from ground objects. Numéro de notice : A2012-389 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2178420 Date de publication en ligne : 04/01/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2178420 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31835 [article]

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