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In situ calibration of light sensors for long-term monitoring of vegetation / Hongxiao Jin in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 6 (June 2015) . - pp 3405 - 3416 Titre : In situ calibration of light sensors for long-term monitoring of vegetation Type de document : Article/Communication Auteurs : Hongxiao Jin, Auteur ; Lars Eklundh, Auteur Année de publication : 2015 Article en page(s) : pp 3405 - 3416 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] capteur terrestre [Termes IGN] étalonnage de capteur (imagerie) [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] photosynthèse [Termes IGN] propagation d'erreur [Termes IGN] surveillance forestière Résumé : (Auteur) Light sensors are increasingly used to monitor vegetation growing status by measuring reflectance or transmittance in multispectral or photosynthetically active radiation (PAR) bands. The measurements are then used to estimate vegetation indices or the fraction of absorbed PAR (FPAR) in a continuous and long-term manner and to serve as inputs to environmental monitoring and calibration/validation data for satellite remote sensing. However, light-sensor calibration is often overlooked or not properly attended to, which leads to difficulties when comparing the measurement results across sites and through time. In this paper, we investigate a practical and accurate user-level in situ calibration method in daylight. The calibration of a sensor pair is made for measuring either bihemispherical reflectance or hemispherical-conical reflectance, which are the two most common ground-based spectral measurements. Procedures and considerations are suggested for user calibration. We also provide a method for calibrating and measuring a single-sensor reflectance-derived Normalized Difference Vegetation Index (NDVI) from red and near-infrared bands. The calibration error propagation is analyzed, and the induced uncertainties in vegetation reflectance and in the NDVI are evaluated. The analysis and field measurements show that the NDVI estimated from a user calibration factor can be as accurate as, or even more accurate than, the manufacturer's calibration. The in situ calibration described here remedies the situation where reflectance for large field-of-view sensors cannot be always estimated from the manufacturer's calibration. The method developed in this paper may help improve the reliability of long-term field spectral measurements and contributes to the near-surface remote sensing of vegetation. Numéro de notice : A2015-275 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2375381 Date de publication en ligne : 18/12/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2375381 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76388 [article]

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Invariant rules for multipolarization SAR change detection / Vincenzo Carotenuto in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 6 (June 2015) . - pp 3294 - 3311 Titre : Invariant rules for multipolarization SAR change detection Type de document : Article/Communication Auteurs : Vincenzo Carotenuto, Auteur ; Antonio de Maio, Auteur ; Carmine Clemente, Auteur ; John J. Soraghan, Auteur Année de publication : 2015 Article en page(s) : pp 3294 - 3311 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] détection de changement [Termes IGN] image radar moirée [Termes IGN] invariant [Termes IGN] polarisation Résumé : (auteur) This paper deals with coherent (in the sense that both amplitudes and relative phases of the polarimetric returns are used to construct the decision statistic) multipolarization synthetic aperture radar (SAR) change detection assuming the availability of reference and test images collected from N multiple polarimetric channels. At the design stage, the change detection problem is formulated as a binary hypothesis testing problem, and the principle of invariance is used to come up with decision rules sharing the constant false alarm rate property. The maximal invariant statistic and the maximal invariant in the parameter space are obtained. Hence, the optimum invariant test is devised proving that a uniformly most powerful invariant detector does not exist. Based on this, the class of suboptimum invariant receivers, which also includes the generalized likelihood ratio test, is considered. At the analysis stage, the performance of some tests, belonging to the aforementioned class, is assessed and compared with the optimum clairvoyant invariant detector. Finally, detection maps on real high-resolution SAR data are computed showing the effectiveness of the considered invariant decision structures. Numéro de notice : A2015-276 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2372900 En ligne : https://doi.org/10.1109/TGRS.2014.2372900 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76389 [article]

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Real-time GPS precise point positioning-based precipitable water vapor estimation for rainfall monitoring and forecasting / Junbo Shi in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 6 (June 2015) . - pp 3452 - 3459 Titre : Real-time GPS precise point positioning-based precipitable water vapor estimation for rainfall monitoring and forecasting Type de document : Article/Communication Auteurs : Junbo Shi, Auteur ; Chaoqian Xu, Auteur ; Jiming Guo, Auteur ; Yang Gao, Auteur Année de publication : 2015 Article en page(s) : pp 3452 - 3459 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] estimation statistique [Termes IGN] positionnement cinématique en temps réel [Termes IGN] positionnement par GPS [Termes IGN] positionnement ponctuel précis [Termes IGN] précipitation [Termes IGN] prévision météorologique [Termes IGN] surveillance météorologique [Termes IGN] vapeur d'eau Résumé : (Auteur) GPS-based precipitable water vapor (PWV) estimation has been proven as a cost-effective approach for numerical weather prediction. Most previous efforts focus on the performance evaluation of post-processed GPS-derived PWV estimates using International GNSS Service (IGS) satellite products with at least 3-9-h latency. However, the suggested timeliness for meteorological nowcasting is 5-30 min. Therefore, the latency has limited the GPS-based PWV estimation in real-time meteorological nowcasting. The limitation has been overcome since April 2013 when IGS released real-time GPS orbit and clock products. This becomes the focus of this paper, which investigates real-time GPS precise point positioning (PPP)-based PWV estimation and its potential for rainfall monitoring and forecasting. This paper first evaluates the accuracy of IGS CLK90 real-time orbit and clock products. Root-mean-square (RMS) errors of Numéro de notice : A2015-279 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2377041 Date de publication en ligne : 22/12/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2377041 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76390 [article]

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Substance dependence constrained sparse NMF for hyperspectral unmixing / Yuan Yuan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 6 (June 2015) . - pp 2975 - 2986 Titre : Substance dependence constrained sparse NMF for hyperspectral unmixing Type de document : Article/Communication Auteurs : Yuan Yuan, Auteur ; Min Fu, Auteur ; Xiaoqiang Lu, Auteur Année de publication : 2015 Article en page(s) : pp 2975 - 2986 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des mélanges spectraux [Termes IGN] classification barycentrique [Termes IGN] état de l'art [Termes IGN] factorisation [Termes IGN] factorisation de matrice non-négative [Termes IGN] image hyperspectrale [Termes IGN] matrice creuse Résumé : (Auteur) Hyperspectral unmixing is one of the most important problems in analyzing remote sensing images, which aims to decompose a mixed pixel into a collection of constituent materials named endmembers and their corresponding fractional abundances. Recently, various methods have been proposed to incorporate sparse constraints into hyperspectral unmixing and achieve advanced performance. However, most of them ignore the complex distribution of substances in hyperspectral data so that they are only effective in limited cases. In this paper, the concept of substance dependence is introduced to help hyperspectral unmixing. Generally, substance dependence can be considered in a local region by K-nearest neighbors method. However, since substances of hyperspectral images are complicatedly distributed, number K of the most similar substances to each substance is difficult to decide. In this case, substance dependence should be considered in the whole data space, and the number of the K most similar substances to each substance can be adaptively determined by searching from the whole space. Through maintaining the substance dependence during unmixing, the abundances resulted from the proposed method are closer to the real fractions, which lead to better unmixing performance. The following contributions can be summarized. 1) The concept of substance dependence is proposed to describe the complicated relationship between substances in the hyperspectral image. 2) We propose substance dependence constrained sparse nonnegative matrix factorization (SDSNMF) for hyperspectral unmixing. Using SDSNMF, we meet or exceed state-of-the-art unmixing performance. 3) Adequate experiments on both synthetic and real hyperspectral data have been tested. Compared with the state-of-the-art methods, the experimental results prove the superiority of the proposed method. Numéro de notice : A2015-280 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2365953 Date de publication en ligne : 13/01/2015 En ligne : https://doi.org/10.1109/TGRS.2014.2365953 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76391 [article]

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Extension of the linear chromodynamics model for spectral change detection in the presence of residual spatial misregistration / Karmon Vongsy in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 6 (June 2015) . - pp 3005 - 3021 Titre : Extension of the linear chromodynamics model for spectral change detection in the presence of residual spatial misregistration Type de document : Article/Communication Auteurs : Karmon Vongsy, Auteur ; Michael T. Eismann, Auteur ; Michael J. Mendenhall, Auteur Année de publication : 2015 Article en page(s) : pp 3005 - 3021 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] approximation [Termes IGN] détection de changement [Termes IGN] distribution de Gauss [Termes IGN] image hyperspectrale [Termes IGN] modèle linéaire [Termes IGN] résidu Résumé : (Auteur) A generalized likelihood ratio test (GLRT) statistic for spectral change detection based on the linear chromodynamics model is extended to accommodate unknown residual misregistration between imagery described by a prior probability density function for the spatial misregistration. Using a normal prior distribution leads to a fourth-order polynomial that can be numerically minimized over the unknown misregistration parameters. A more computationally efficient closed-form solution is developed based on a quadratic approximation and provides comparable results to the numerical minimization for the investigated test cases while running 30 times faster. The results applying the method to hyperspectral imagery indicate up to an order of magnitude reduction in false alarms at the same detection rate relative to baseline change detection methods for synthetically misregistered test data particularly in image regions containing edges and fine spatial features. Sensitivity to model parameters is assessed, and the method is compared with a previously published misregistration compensation approach yielding comparable results. Although the GLRT approach appears to exhibit comparable change detection performance, it offers the possibility of tailoring the algorithm to a priori knowledge of expected misregistration errors or to compensate structured misregistration as would occur due to parallax errors due to perspective variations (e.g., image parallax). Numéro de notice : A2015-281 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2367471 Date de publication en ligne : 18/12/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2367471 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76398 [article]

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MTF-adjusted pansharpening approach based on coupled multiresolution decompositions / Abdelaziz Kallel in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 6 (June 2015) . - pp 3124 - 3145 Titre : MTF-adjusted pansharpening approach based on coupled multiresolution decompositions Type de document : Article/Communication Auteurs : Abdelaziz Kallel, Auteur Année de publication : 2015 Article en page(s) : pp 3124 - 3145 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse multirésolution [Termes IGN] décomposition d'image [Termes IGN] fonction de transfert de modulation [Termes IGN] image Geoeye [Termes IGN] image multibande [Termes IGN] image Pléiades-HR [Termes IGN] image SPOT 6 [Termes IGN] pansharpening (fusion d'images) [Termes IGN] transformation en ondelettes Résumé : (Auteur) Among others, the wavelet-based pansharpening approach tries to enhance the resolution of the multispectral (MS) image by injection of spatial details extracted from the high-resolution panchromatic (PAN) image. The problem is presented as follows, the inputs are a coarse-resolution MS image and a high-resolution detail image provided from the PAN image; therefore, one would think that the wavelet reconstruction allows combining approximations and details to construct the high-resolution MS image. However, the wavelet transform (WT) assumes that details and approximations are calculated using the same wavelet decomposition. Now, in the pansharpening case, the MS low-resolution image is assumed to be aliased and blurred due to the imaging system modulation transfer function (MTF) that is approximated as a specific low-pass filter. Meanwhile, there are no constraints about details that can be extracted from PAN using discrete WT (DWT). Approximation and details are not any more orthogonal as needed in the reconstruct of the MS high-resolution image based on DWT. For that, we propose in this paper a new fusion schema [coupled multiresolution decomposition model (CMD)] allowing the reconstruction of a high-resolution MS given its approximation and details obtained by MTF-tailored downsampling and wavelet decomposition, respectively. For validation, CMD is applied to Pléiades, GeoEye-1, and SPOT 6 images. Compared to other approaches [i.e., Gram-Schmidt (GS) adaptive, GS mode 2 (GS2), “À trous' WT (AWT), generalized Laplacian pyramid (GLP), DWT, and PCI Geomatics software algorithm], our method performs generally better. Numéro de notice : A2015-282 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2369056 Date de publication en ligne : 19/12/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2369056 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76399 [article]

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Object detection in optical remote sensing images based on weakly supervised learning and high-level feature learning / Junwei Han in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 6 (June 2015) . - pp 3325 - 3337 Titre : Object detection in optical remote sensing images based on weakly supervised learning and high-level feature learning Type de document : Article/Communication Auteurs : Junwei Han, Auteur ; Dingwen Zhang, Auteur ; Gong Cheng, Auteur Année de publication : 2015 Article en page(s) : pp 3325 - 3337 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage semi-dirigé [Termes IGN] détection d'objet [Termes IGN] estimation bayesienne [Termes IGN] état de l'art [Termes IGN] moteur d'inférence Résumé : (Auteur) The abundant spatial and contextual information provided by the advanced remote sensing technology has facilitated subsequent automatic interpretation of the optical remote sensing images (RSIs). In this paper, a novel and effective geospatial object detection framework is proposed by combining the weakly supervised learning (WSL) and high-level feature learning. First, deep Boltzmann machine is adopted to infer the spatial and structural information encoded in the low-level and middle-level features to effectively describe objects in optical RSIs. Then, a novel WSL approach is presented to object detection where the training sets require only binary labels indicating whether an image contains the target object or not. Based on the learnt high-level features, it jointly integrates saliency, intraclass compactness, and interclass separability in a Bayesian framework to initialize a set of training examples from weakly labeled images and start iterative learning of the object detector. A novel evaluation criterion is also developed to detect model drift and cease the iterative learning. Comprehensive experiments on three optical RSI data sets have demonstrated the efficacy of the proposed approach in benchmarking with several state-of-the-art supervised-learning-based object detection approaches. Numéro de notice : A2015 - 283 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2374218 Date de publication en ligne : 18/12/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2374218 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76400 [article]

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Retrieval of significant wave height and mean sea surface level using the GNSS-R interference pattern technique : results from a three-month field campaign / Alberto Alonso-Arroyo in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 6 (June 2015) . - pp 3198 - 3209 Titre : Retrieval of significant wave height and mean sea surface level using the GNSS-R interference pattern technique : results from a three-month field campaign Type de document : Article/Communication Auteurs : Alberto Alonso-Arroyo, Auteur ; Adriano Camps, Auteur ; Hyuk Park, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 3198 - 3209 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] Espagne [Termes IGN] hauteurs de mer [Termes IGN] interférence [Termes IGN] niveau moyen des mers [Termes IGN] océanographie spatiale [Termes IGN] positionnement par GNSS [Termes IGN] réflectométrie par GNSS [Termes IGN] vague Résumé : (Auteur) Since 1993, when the European Space Agency (ESA) proposed the use of Global Navigation Satellite Systems reflected signals for sea mesoscale altimetry, a wide range of applications have appeared. This paper focuses on the retrieval of significant wave height (SWH) and the mean sea surface level (MSSL) from a ground-based experiment using the interference pattern technique (IPT). Two different observables on the IPT are analyzed: the oscillation frequency and the angle where coherency is lost. The point where coherency in the reflection process is lost can be related to the Rayleigh criterion for smooth surfaces and helps to determine the SWH. Spectral analysis on the interference pattern helps to determine the MSSL. A three-month field campaign was performed on the “Pont del Petroli” pier, Badalona, Spain, to see how the reflected GNSS signals were affected by coastal sea state and check previous assumptions. Results from this field experiment are shown, confirming that the SWH can be retrieved with accuracy of 6 cm and the MSSL with 4 cm. Estimations of both parameters are obtained every 30 min approximately. Numéro de notice : A2015-284 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2374218 Date de publication en ligne : 18/12/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2374218 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76401 [article]

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