Centre de documentation
scientifique

Open source geospatial tools / Daniel McInerney (2015)

Public Titre : Open source geospatial tools : applications in Earth observation Type de document : Monographie Auteurs : Daniel McInerney, Éditeur scientifique ; Pieter Kempeneers, Éditeur scientifique Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2015 Collection : Earth systems data and models Importance : 358 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-319-01823-2 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes IGN] analyse de données [Termes IGN] classification multibande [Termes IGN] données localisées 3D [Termes IGN] données maillées [Termes IGN] données vectorielles [Termes IGN] Geospatial data abstraction library [Termes IGN] interface de programmation [Termes IGN] lasergrammétrie [Termes IGN] logiciel libre [Termes IGN] Orfeo Tool Box [Termes IGN] outil logiciel [Termes IGN] traitement d'image [Termes IGN] traitement de données localisées Index. décimale : 37.35 Logiciels SIG Résumé : (Editeur) This book focuses on the use of open source software for geospatial analysis. It demonstrates the effectiveness of the command line interface for handling both vector, raster and 3D geospatial data. Appropriate open-source tools for data processing are clearly explained and discusses how they can be used to solve everyday tasks. A series of fully worked case studies are presented including vector spatial analysis, remote sensing data analysis, landcover classification and LiDAR processing. A hands-on introduction to the application programming interface (API) of GDAL/OGR in Python/C++ is provided for readers who want to extend existing tools and/or develop their own software. Note de contenu : Part - I Geospatial Data Processing with GDAL/OGR 1. Introduction 2. Vector Data Processing 3. Raster Data Explained 4. Introduction to GDAL Utilities 5. Manipulating Raster Data 6. Indexed Color Images 7. Image Overviews, Tiling and Pyramids 8. Image (Re-)projections and Merging 9. Raster Meets Vector Data 10. Raster Meets Point Data 11. Virtual Rasters and Raster Calculations Part - II Third Party Open Source Geospatial Utilities 12. Pktools 13. Orfeo Toolbox 14. Write Your Own Geospatial Utilities 15. 3D Point Cloud Data Processing Part - III Case Studies 16. Case Study on Vector Spatial Analysis 17. Case Study on Multispectral Land Cover Classification 18. Case Study on Point Data 19. Conclusions and Future Outlook Appendix A: Data Covered in the Book Appendix B: Installation of Software Glossary Numéro de notice : 22219 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Recueil / ouvrage collectif Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75218

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
22219-01	37.35	Livre	Centre de documentation	Géomatique	Disponible

Increasing robustness of postclassification change detection using time series of land cover maps / Pieter Kempeneers in IEEE Transactions on geoscience and remote sensing, vol 50 n° 9 (October 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 9 (October 2012) . - pp 3327 - 3339 Titre : Increasing robustness of postclassification change detection using time series of land cover maps Type de document : Article/Communication Auteurs : Pieter Kempeneers, Auteur ; F. Sedano, Auteur ; Peter Strobl, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 3327 - 3339 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] carte d'occupation du sol [Termes IGN] détection de changement [Termes IGN] Europe (géographie politique) [Termes IGN] image Terra-MODIS [Termes IGN] incendie de forêt [Termes IGN] méthode robuste [Termes IGN] occupation du sol [Termes IGN] risque naturel [Termes IGN] série temporelle [Termes IGN] surveillance de la végétation Résumé : (Auteur) The monitoring of land cover requires that stable land cover classes be distinguished from changes over time. Within this paper, a postclassification method is presented that provides land cover change information, based on a time series of land cover maps. The method applies a kernel filter to sequential land cover maps. Under some basic assumptions, it shows robustness against classification errors. Despite seasonality, land cover changes often occur at a low temporal frequency (e.g., maximum once every 5-10 years). If land cover maps are available more frequently, some of the information will become redundant (oversampling). The proposed method uses this redundancy for tolerating (nonsystematic) misclassifications. In order to demonstrate the benefits and limitations of the proposed method, analytical expressions have been derived. When compared to a simple postclassification comparison, one of the key strengths of the proposed approach is that it is able to improve both the overall and user's accuracy of change, while also maintaining the same level of producer's accuracy. As a case study, MODerate Resolution Imaging Spectroradiometer remote sensing data from 2006-2010 were classified into forest (F)/nonforest (NF) at pan-European scale. Promising results were obtained for detecting forest loss due to natural disasters. Quality was assessed using burnt area maps in southern Europe and a forest damage report after a windstorm in France. Results indicated a considerable reduction of change detection errors, confirming the theoretical results. Numéro de notice : A2012-448 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2181854 Date de publication en ligne : 21/02/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2181854 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31894 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2012091	RAB	Revue	Centre de documentation	En réserve L003	Exclu du prêt

Superresolution enhancement of hyperspectral CHRIS/Proba images with a thin-plate spline nonrigid transform model / J. Chan in IEEE Transactions on geoscience and remote sensing, vol 48 n° 6 (June 2010)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 48 n° 6 (June 2010) . - pp 2669 - 2579 Titre : Superresolution enhancement of hyperspectral CHRIS/Proba images with a thin-plate spline nonrigid transform model Type de document : Article/Communication Auteurs : J. Chan, Auteur ; J. Ma, Auteur ; Pieter Kempeneers, Auteur ; Frank Canters, Auteur Année de publication : 2010 Article en page(s) : pp 2669 - 2579 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] accentuation d'image [Termes IGN] fonction spline [Termes IGN] image hyperspectrale [Termes IGN] image PROBA-CHRIS [Termes IGN] itération [Termes IGN] point d'appui [Termes IGN] reconstruction d'image Résumé : (Auteur) Given the hyperspectral-oriented waveband configuration of multiangular CHRIS/Proba imagery, the scope of its application could widen if the present 18-m resolution would be improved. The multiangular images of CHRIS could be used as input for superresolution (SR) image reconstruction. A critical procedure in SR is an accurate registration of the low-resolution images. Conventional methods based on affine transformation may not be effective given the local geometric distortion in high off-nadir angular images. This paper examines the use of a nonrigid transform to improve the result of a nonuniform interpolation and deconvolution SR method. A scale-invariant feature transform is used to collect control points (CPs). To ensure the quality of CPs, a rigorous screening procedure is designed: 1) an ambiguity test; 2) the m-estimator sample consensus method; and 3) an iterative method using statistical characteristics of the distribution of random errors. A thin-plate spline (TPS) nonrigid transform is then used for the registration. The proposed registration method is examined with a Delaunay triangulation-based nonuniform interpolation and reconstruction SR method. Our results show that the TPS nonrigid transform allows accurate registration of angular images. SR results obtained from simulated LR images are evaluated using three quantitative measures, namely, relative mean-square error, structural similarity, and edge stability. Compared to the SR methods that use an affine transform, our proposed method performs better with all three evaluation measures. With a higher level of spatial detail, SR-enhanced CHRIS images might be more effective than the original data in various applications. Numéro de notice : A2010-192 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2009.2039797 En ligne : https://doi.org/10.1109/TGRS.2009.2039797 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30386 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2010061	RAB	Revue	Centre de documentation	En réserve L003	Disponible
065-2010062	RAB	Revue	Centre de documentation	En réserve L003	Disponible