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Real time monitoring ground motion using GPS with real time corrections / R. Tu in Survey review, vol 48 n° 347 (March 2016)  

Public [article]  inSurvey review > vol 48 n° 347 (March 2016) . - pp 79 – 85 Titre : Real time monitoring ground motion using GPS with real time corrections Type de document : Article/Communication Auteurs : R. Tu, Auteur ; L. Wang, Auteur ; Z. Liu, Auteur Année de publication : 2016 Article en page(s) : pp 79 – 85 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] modèle d'erreur [Termes IGN] mouvement de terrain [Termes IGN] positionnement par GPS [Termes IGN] résidu [Termes IGN] station GPS [Termes IGN] surveillance géologique [Termes IGN] vitesse Résumé : (auteur) The high rate GPS velocity determination technology which is based on the broadcast ephemeris and epoch differenced model can retrieve displacement of ground motion with the precision of a few centimetres to decimetres in real time. Moreover, the precision of the recovered displacement can be improved if the un-modelled errors such as broadcast ephemeris residuals, atmospheric residuals, multipath effects and high frequency noise are tackled more accurately. In this paper, we propose a method to improve the precision of the recovered displacement by appropriately making use of reference station corrections. For the reference stations, the coordinates are highly constrained to extract the error corrections that are to be broadcast via a communication link to the rover. After correcting the rover’s observations, some errors such as ephemeris residuals and atmospheric residuals are effectively eliminated or at least reduced. This improves the accuracy of the observations and thus enhances the reliability of the velocity estimation. The displacement can be recovered by integrating the estimated velocity after de-trending using a linear trend that is caused by the un-corrected residuals. The series of validation results in the experiment have shown that the displacement of the simulated motion can be real time recovered with a precision of 1–2 cm, and is thus applicable for real time monitoring of the ground motion. Numéro de notice : A2016-047 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1179/1752270614Y.0000000141 En ligne : https://doi.org/10.1179/1752270614Y.0000000141 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79641 [article]

Semi-supervised classification for hyperspectral imagery based on spatial-spectral Label Propagation / L. Wang in ISPRS Journal of photogrammetry and remote sensing, vol 97 (November 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 97 (November 2014) . - pp 123 – 137 Titre : Semi-supervised classification for hyperspectral imagery based on spatial-spectral Label Propagation Type de document : Article/Communication Auteurs : L. Wang, Auteur ; Siyuan Hao, Auteur ; Q. Wang, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 123 – 137 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification semi-dirigée [Termes IGN] filtre de Gabor [Termes IGN] graphe [Termes IGN] image hyperspectrale Résumé : (Auteur) Graph-based classification algorithms have gained increasing attention in semi-supervised classification. Nevertheless, the graph cannot fully represent the inherent spatial distribution of the data. In this paper, a new classification methodology based on the spatial-spectral Label Propagation is proposed for semi-supervised classification of hyperspectral imagery. The spatial information was used in two aspects: on the one hand, the spatial features extracted by a 2-D Gabor filter were stacked with spectral features; on the other hand, the width of the Gaussian function, which was used to construct graph, was determined with an adaptive method. Subsequently, the unlabeled samples from the spatial neighbors of the labeled samples were selected and the spatial graph was constructed based on spatial smoothness. Finally, labels were propagated from labeled samples to unlabeled samples with spatial-spectral graph to update the training set for a basic classifier (e.g., Support Vector Machine, SVM). Experiments on four hyperspectral datasets show that the proposed Spatial-Spectral Label Propagation based on the SVM (SS-LPSVM) can effectively represent the spatial information in the framework of semi-supervised learning and consistently produces greater classification accuracy than the standard SVM, the Laplacian Support Vector Machine (LapSVM), Transductive Support Vector Machine (TSVM) and the Spatial-Contextual Semi-Supervised Support Vector Machine (SCS3VM). Numéro de notice : A2014-527 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.08.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.08.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74140 [article]

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Computer-based synthetic data to assess the tree delineation algorithm from airborne LiDAR survey / L. Wang in Geoinformatica, vol 17 n° 1 (January 2013)  

Public [article]  inGeoinformatica > vol 17 n° 1 (January 2013) . - pp 35 - 61 Titre : Computer-based synthetic data to assess the tree delineation algorithm from airborne LiDAR survey Type de document : Article/Communication Auteurs : L. Wang, Auteur ; A. Birt, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 35 - 61 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre (flore) [Termes IGN] détection de contours [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] modèle géométrique [Termes IGN] Pinophyta [Termes IGN] Pinus taeda [Termes IGN] segmentation Résumé : (Auteur) Small Footprint LiDAR (Light Detection And Ranging) has been proposed as an effective tool for measuring detailed biophysical characteristics of forests over broad spatial scales. However, by itself LiDAR yields only a sample of the true 3D structure of a forest. In order to extract useful forestry relevant information, this data must be interpreted using mathematical models and computer algorithms that infer or estimate specific forest metrics. For these outputs to be useful, algorithms must be validated and/or calibrated using a sub-sample of ‘known’ metrics measured using more detailed, reliable methods such as field sampling. In this paper, we describe a novel method for delineating and deriving metrics of individual trees from LiDAR data based on watershed segmentation. Because of the costs involved with collecting both LiDAR data and field samples for validation, we use synthetic LiDAR data to validate and assess the accuracy of our algorithm. This synthetic LiDAR data is generated using a simple geometric model of Loblolly pine (Pinus taeda) trees and a simulation of LiDAR sampling. Our results suggest that point densities greater than 2 and preferably greater than 4 points per m2 are necessary to obtain accurate forest inventory data from Loblolly pine stands. However the results also demonstrate that the detection errors (i.e. the accuracy and biases of the algorithm) are intrinsically related to the structural characteristics of the forest being measured. We argue that experiments with synthetic data are directly useful to forest managers to guide the design of operational forest inventory studies. In addition, we argue that the development of LiDAR simulation models and experiments with the data they generate represents a fundamental and useful approach to designing, improving and exploring the accuracy and efficiency of LiDAR algorithms. Numéro de notice : A2013-046 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s10707-011-0148-1 Date de publication en ligne : 29/11/2011 En ligne : https://doi.org/10.1007/s10707-011-0148-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32184 [article]

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ICESat GLAS data for urban environment monitoring / P. Gong in IEEE Transactions on geoscience and remote sensing, vol 49 n° 3 (March 2011)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 49 n° 3 (March 2011) . - pp 1158 - 1172 Titre : ICESat GLAS data for urban environment monitoring Type de document : Article/Communication Auteurs : P. Gong, Auteur ; Z. Li, Auteur ; H. Huang, Auteur ; G. Sun, Auteur ; L. Wang, Auteur Année de publication : 2011 Article en page(s) : pp 1158 - 1172 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] altimètre laser [Termes IGN] Chine [Termes IGN] Geoscience Laser Altimeter System [Termes IGN] hauteur du bâti [Termes IGN] Pékin (Chine) [Termes IGN] surveillance [Termes IGN] traitement de données [Termes IGN] urbanisation Résumé : (Auteur) Although the Geoscience Laser Altimeter System (GLAS) onboard the NASA Ice, Cloud and Land Elevation Satellite was not designed for urban applications, its 3-D measurement capability over the globe makes it a nice feature for consideration in monitoring urban heights. However, this has not been previously done. In this paper, we report some preliminary assessment of the GLAS data for building height and density estimation in a suburb of Beijing, China. Building heights can be directly calculated from a GLAS data product (GLA14). Because GLA14 limits height levels to six in each ground footprint, we developed a new method to remove this restriction by processing the raw GLAS data. The maximum heights measured in the field at selected GLAS footprints were used to validate the GLAS measurement results. By assuming a constant incident energy and surface reflectance within a GLAS footprint, the building density can be estimated from GLA14 or from our newly processed GLAS data. The building density determined from high-resolution images in Google Earth was used to validate the GLAS estimation results. The results indicate that the newly developed method can produce more accurate building height estimation within each GLAS footprint (R2 = 0.937, rmse = 6.4 m, and n = 26) than the GLA14 data product (R2 = 0.808, rmse = 11.5 m, and n = 26). However, satisfactory estimation results on building density cannot be obtained from the GLAS data with the methods investigated in this paper. Forest cover could be a challenge to building height and density estimation from the GLAS data. It should be addressed in future research. Numéro de notice : A2011-069 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2010.2070514 Date de publication en ligne : 11/10/2010 En ligne : https://doi.org/10.1109/TGRS.2010.2070514 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30850 [article]

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vol 31 n° 21 - November 2010 - Population estimation using remote sensing and GIS technologies (Bulletin de International Journal of Remote Sensing IJRS) / L. Wang

Public [n° ou bulletin]  est un bulletin de International Journal of Remote Sensing IJRS / Remote sensing and photogrammetry society (1980 -)   Titre : vol 31 n° 21 - November 2010 - Population estimation using remote sensing and GIS technologies Type de document : Périodique Auteurs : L. Wang, Éditeur scientifique ; C. Wu, Éditeur scientifique ; Remote sensing and photogrammetry society, Auteur Année de publication : 2010 Importance : 404 p. Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] démographie [Termes IGN] population [Termes IGN] répartition géographique [Termes IGN] système d'information géographique [Termes IGN] télédétection Numéro de notice : 080-201013 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Numéro de périodique Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=13733 [n° ou bulletin]

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An object-based conceptual framework and computational method for representing and analyzing coastal morphological changes / H. Liu in International journal of geographical information science IJGIS, vol 24 n°7-8 (july 2010)  

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Morphology-based building detection from airborne Lidar data / X. Meng in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 4 (April 2009)  

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Representing geographical objects with scale-induced indeterminate boundaries: a neural network-based data model / José L. Silvan-Cardenas in International journal of geographical information science IJGIS, vol 23 n°3-4 (march - april 2009)  

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A multi-directional ground filtering algorithm for airborne LIDAR / X. Meng in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 1 (January - February 2009)  

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ISRV: an improved synthetic variable ratio method for image fusion / L. Wang in Geocarto international, vol 23 n° 2 (April - May 2008)  

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Spatio-temporal urban landscape change analysis using the Markov chain model and a modified genetic algorithm / J. Tang in International Journal of Remote Sensing IJRS, vol 28 n°15-16 (August 2007)  

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A multi-resolution approach for filtering LiDAR altimetry data / José L. Silvan-Cardenas in ISPRS Journal of photogrammetry and remote sensing, vol 61 n° 1 (October 2006)  

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Urban land-use classification using variogram-based analysis with an aerial photograph / S.S. Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 7 (July 2006)  

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An efficient method for identifying and filling surface depressions in digital elevation models for hydrologic analysis and modelling / L. Wang in International journal of geographical information science IJGIS, vol 20 n° 2 (february 2006)  

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An artificial-neural-network-based, constrained CA model for simulating urban growth / Q. Guan in Cartography and Geographic Information Science, vol 32 n° 4 (October 2005)  

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