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Gaussian mixture model of ground filtering based on hierarchical curvature constraints for airborne Lidar point clouds / Longjie Ye in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 9 (September 2021) . - pp 615 - 630 Titre : Gaussian mixture model of ground filtering based on hierarchical curvature constraints for airborne Lidar point clouds Type de document : Article/Communication Auteurs : Longjie Ye, Auteur ; Ka Zhang, Auteur ; Wen Xiao, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 615 - 630 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] algorithme de filtrage [Termes IGN] classification barycentrique [Termes IGN] courbure [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] fonction spline d'interpolation [Termes IGN] Kappa de Cohen [Termes IGN] lasergrammétrie [Termes IGN] modèle numérique de terrain [Termes IGN] processus gaussien [Termes IGN] semis de points Résumé : (Auteur) This paper proposes a Gaussian mixture model of a ground filtering method based on hierarchical curvature constraints. Firstly, the thin plate spline function is iteratively applied to interpolate the reference surface. Secondly, gradually changing grid size and curvature threshold are used to construct hierarchical constraints. Finally, an adaptive height difference classifier based on the Gaussian mixture model is proposed. Using the latent variables obtained by the expectation-maximization algorithm, the posterior probability of each point is computed. As a result, ground and objects can be marked separately according to the calculated possibility. 15 data samples provided by the International Society for Photogrammetry and Remote Sensing are used to verify the proposed method, which is also compared with eight classical filtering algorithms. Experimental results demonstrate that the average total errors and average Cohen's kappa coefficient of the proposed method are 6.91% and 80.9%, respectively. In general, it has better performance in areas with terrain discontinuities and bridges. Numéro de notice : A2021-671 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.20-00080 Date de publication en ligne : 01/09/2021 En ligne : https://doi.org/10.14358/PERS.87.20-00080 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98820 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2021091	SL	Revue	Centre de documentation	Revues en salle	Disponible

Double adaptive intensity-threshold method for uneven Lidar data to extract road markings / Chengming Ye in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 9 (September 2021) . - pp 639-648 Titre : Double adaptive intensity-threshold method for uneven Lidar data to extract road markings Type de document : Article/Communication Auteurs : Chengming Ye, Auteur ; Hongfu Li, Auteur ; Ruilong Wei, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 639-648 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction du réseau routier [Termes IGN] filtre adaptatif [Termes IGN] lidar mobile [Termes IGN] méthode robuste [Termes IGN] semis de points [Termes IGN] seuillage de points [Termes IGN] signalisation routière Résumé : (Auteur) Due to the large volume and high redundancy of point clouds, there are many dilemmas in road-marking extraction algorithms, especially from uneven lidar point clouds. To extract road markings efficiently, this study presents a novel method for handling the uneven density distribution of point clouds and the high reflection intensity of road markings. The method first segments the point-cloud data into blocks perpendicular to the vehicle trajectory. Then it applies the double adaptive intensity-threshold method to extract road markings from road surfaces. Finally, it performs an adaptive spatial density filter based on the density distribution of point-cloud data to remove false road-marking points. The average completeness, correctness, and F measure of road-marking extraction are 0.827, 0.887, and 0.854, respectively, indicating that the proposed method is efficient and robust. Numéro de notice : A2021-672 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.20-00099 Date de publication en ligne : 01/09/2021 En ligne : https://doi.org/10.14358/PERS.20-00099 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98834 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2021091	SL	Revue	Centre de documentation	Revues en salle	Disponible

Estimating regional soil moisture with synergistic use of AMSR2 and MODIS images / Majid Rahimzadegan in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 9 (September 2021) . - pp 649-660 Titre : Estimating regional soil moisture with synergistic use of AMSR2 and MODIS images Type de document : Article/Communication Auteurs : Majid Rahimzadegan, Auteur ; Arash Davari, Auteur ; Ali Sayadi, Auteur Année de publication : 2021 Article en page(s) : pp 649-660 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Advanced Microwave Scanning Radiometer [Termes IGN] coefficient de corrélation [Termes IGN] humidité du sol [Termes IGN] image Aqua-AMSR [Termes IGN] image Terra-MODIS [Termes IGN] indice d'humidité [Termes IGN] Iran [Termes IGN] polarisation [Termes IGN] réflectance du sol Résumé : (Auteur) Soil moisture content (SMC), product of Advanced Microwave Scanning Radiometer 2 (AMSR2), is not at an adequate level of accuracy on a regional scale. The aim of this study is to introduce a simple method to estimate SMC while synergistically using AMSR2 and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements with a higher accuracy on a regional scale. Two MODIS products, including daily reflectance (MYD021) and nighttime land surface temperature (LST) products were used. In 2015, 1442 in situ SMC measurements from six stations in Iran were used as ground-truth data. Twenty models were evaluated using combinations of polarization index (PI), index of soil wetness (ISW), normalized difference vegetation index (NDVI), and LST. The model revealed the best results using a quadratic combination of PI and ISW, a linear form of LST, and a constant value. The overall correlation coefficient, root-mean-square error, and mean absolute error were 0.59, 4.62%, and 3.01%, respectively. Numéro de notice : A2021-673 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.20-00085 Date de publication en ligne : 01/09/2021 En ligne : https://doi.org/10.14358/PERS.20-00085 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98835 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2021091	SL	Revue	Centre de documentation	Revues en salle	Disponible