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Aspects of generating precise digital terrain models in the Wadden Sea from lidar-water classification and structure line extraction / A. Brzank in ISPRS Journal of photogrammetry and remote sensing, vol 63 n° 5 (September - October 2008)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 63 n° 5 (September - October 2008) . - pp 510 - 528 Titre : Aspects of generating precise digital terrain models in the Wadden Sea from lidar-water classification and structure line extraction Type de document : Article/Communication Auteurs : A. Brzank, Auteur ; Christian Heipke, Auteur ; J. Goepfert, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 510 - 528 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] extraction de traits caractéristiques [Termes IGN] lasergrammétrie [Termes IGN] littoral [Termes IGN] modèle numérique de terrain [Termes IGN] Pays-Bas [Termes IGN] semis de points [Termes IGN] Wadden, mer des Résumé : (Auteur) The Wadden Sea is a unique habitat formed by the strong influence of tidal currents. Twice a day the area is flooded and falls dry afterwards. Due to the force of tidal streams, strong morphologic changes occur frequently. In order to monitor these changes, high precision digital terrain models (DTMs) are required. Lidar proved to be an adequate technique to deliver highly accurate 3D mass points of the surface and dense spacing. However, water often remains within tidal channels and depressions even at low tide, and near infrared lidar is not able to penetrate the water leading to a point cloud which contains surface and water points. Thus, the standard processing workflow for DTM generation from lidar is not suited for the Wadden Sea. In this article, a new workflow is proposed for DTM generation from lidar data in the Wadden Sea. Two major building blocks of this workflow, namely classification of the water points and structure line detection, are presented in detail. For both tasks suitable algorithms were developed tailored to meet special requirements of mudflat. Lidar measurements from water surfaces are detected by a supervised fuzzy classification using the features height, intensity, and 2D point density. Structure lines are derived through a piecewise reconstruction of the surface from the lidar data with a hyperbolic tangent function. The obtained results show that both methods considerably improve the accuracy of DTMs from lidar data. Copyright ISPRS Numéro de notice : A2008-386 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2008.02.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2008.02.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29379 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-08051	SL	Revue	Centre de documentation	Revues en salle	Disponible

Detection, measurement and prediction of shoreline recession in Accra, Ghana / K. Appeaning Addo in ISPRS Journal of photogrammetry and remote sensing, vol 63 n° 5 (September - October 2008)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 63 n° 5 (September - October 2008) . - pp 543 - 558 Titre : Detection, measurement and prediction of shoreline recession in Accra, Ghana Type de document : Article/Communication Auteurs : K. Appeaning Addo, Auteur ; M. Walkden, Auteur ; Jon P. Mills, Auteur Année de publication : 2008 Article en page(s) : pp 543 - 558 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse diachronique [Termes IGN] données de terrain [Termes IGN] érosion côtière [Termes IGN] Ghana [Termes IGN] incertitude des données [Termes IGN] littoral [Termes IGN] modèle de simulation [Termes IGN] montée du niveau de la mer [Termes IGN] trait de côte Résumé : (Auteur) Coastal mapping, using various data capture and feature extraction techniques, has furthered understanding of trends in shoreline evolution by allowing calculation of accurate historic rates of change that subsequently enable the prediction of future shoreline positions through different modelling procedures. The results have helped influence coastal policy formulation and promoted the development of sustainable management practices in coastal regions throughout the developed world. However, sustainable coastal management is rarely practiced in developing countries, one of the fundamental reasons for this being a general lack of reliable and accurate historic data on shoreline position. Previous studies on the Ghanaian coastal region of Accra, where accurate and reliable geospatial data for analysis is scarce, have reported erosion rates of anything between two and eight metres per year. This high level of inconsistency in reported rates has hindered effective and sustainable coastal management. The research reported in this paper addresses this issue, using mapping data from 1904, 1974, 1996 and 2002 to estimate, by linear regression, shoreline recession in the Accra region. Predictions for the next 250 yr were then undertaken using a variety of techniques ranging from a process-based numerical model, SCAPE, to geometric approaches including historical trend analysis, the modified Bruun model and Sunamura’s shore platform model. Uncertainties in the various input data were accounted for, including historic recession rates, rock strength, sediment content and, importantly, future sea-level rise under different climate change scenarios. The mean historic rate of erosion in the Accra region was found to be 1.13 m/yr(10.17 m/yr), significantly less than previously reported, though still very high. Subsequent predictions were used to identify a series of significant economic, ecological and social features at risk, and to estimate when they will most likely be lost to erosion if left unprotected. The case study illustrates that, provided suitable predictive models are selected and the uncertainties involved in working with limited data sets are dealt with appropriately, it is possible to provide statistical information in support of sustainable coastal management for developing countries in the face of a changing climate. Copyright ISPRS Numéro de notice : A2008-387 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2008.04.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2008.04.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29380 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-08051	SL	Revue	Centre de documentation	Revues en salle	Disponible