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An exploratory analysis of usability of Flickr tags for land use/land cover attribution / Yingwei Yan in Geo-spatial Information Science, vol 22 n° 1 (March 2019)  

Public [article]  inGeo-spatial Information Science > vol 22 n° 1 (March 2019) . - pp 12 - 22 Titre : An exploratory analysis of usability of Flickr tags for land use/land cover attribution Type de document : Article/Communication Auteurs : Yingwei Yan, Auteur ; Michael Schultz, Auteur ; Alexander Zipf, Auteur Année de publication : 2019 Article en page(s) : pp 12 - 22 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] analyse sémantique [Termes descripteurs IGN] contenu généré par les utilisateurs [Termes descripteurs IGN] données issues des réseaux sociaux [Termes descripteurs IGN] étiquetage sémantique [Termes descripteurs IGN] image Flickr [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] San Diego Résumé : (Auteur) This study explored the land use/land cover (LULC) separability by the machine-generated and user-generated Flickr photo tags (i.e. the auto-tags and the user-tags, respectively), based on an authoritative LULC dataset for San Diego County in the United States. Ten types of LULCs were derived from the authoritative dataset. It was observed that certain types of the reclassified LULCs had abundant tags (e.g. the parks) or a high tag density (e.g. the commercial lands), compared with the less populated ones (e.g. the agricultural lands). Certain highly weighted terms of the tags derived based on a term frequency–inverse document frequency weighting scheme were helpful for identifying specific types of the LULCs, especially for the commercial recreation lands (e.g. the zoos). However, given the 10 sets of tags retrieved from the corresponding 10 types of LULCs, one set of tags (all the tags located at one specific type of the LULCs) could not fully delineate the corresponding LULC due to semantic overlaps, according to a latent semantic analysis. Numéro de notice : A2019-241 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2018.1560044 date de publication en ligne : 08/01/2019 En ligne : https://doi.org/10.1080/10095020.2018.1560044 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92934 [article]

Object-based image mapping of conifer tree mortality in San Diego county based on multitemporal aerial ortho-imagery / Mary Pyott Freeman in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 7 (juillet 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 7 (juillet 2016) . - pp 571 - 580 Titre : Object-based image mapping of conifer tree mortality in San Diego county based on multitemporal aerial ortho-imagery Type de document : Article/Communication Auteurs : Mary Pyott Freeman, Auteur ; Douglas A. Stow, Auteur ; Dar A. Roberts, Auteur Année de publication : 2016 Article en page(s) : pp 571 - 580 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] arbre mort [Termes descripteurs IGN] carte de la végétation [Termes descripteurs IGN] classification dirigée [Termes descripteurs IGN] classification par réseau neuronal [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] image multitemporelle [Termes descripteurs IGN] orthoimage [Termes descripteurs IGN] pinophyta [Termes descripteurs IGN] San Diego Résumé : (Auteur) Two GEOBIA approaches are compared for their effectiveness in mapping dead trees within island montane forests of Southern California: a spatial contextual approach using an artificial neural network classifier, and a segmentation and multi-pixel classification approach. Both approaches are tested with multitemporal aerial orthoimagery having varying spatial resolutions. Spectral transformation inputs are also tested. An object-based accuracy assessment is conducted. Accuracies range between 30 percent to 90 percent for the dead tree class and are significantly higher for the spatial-contextual approach. Inclusion of spectral transforms increased accuracies by 5 percent for the true object-based approach, up to 13 percent for the spatial contextual approach, and reduced commission error up to 10 percent for both approaches. Masking techniques increased accuracies of the spatial contextual approach by 20 percent. With manual editing, the most accurate maps of individual live and dead trees from the spatial contextual approach are suitable for studying spatio-temporal trends in montane conifer mortality. Numéro de notice : A2016-518 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article En ligne : http://dx.doi.org/10.14358/PERS.82.7.571 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81589 [article]

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Mapping fuels at the wildland-urban interface using colour ortho-images and Lidar data / Melissa F. Rosa in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)  

Public [article]  inGeocarto international > vol 29 n° 5 - 6 (August - October 2014) . - pp 570-588 Titre : Mapping fuels at the wildland-urban interface using colour ortho-images and Lidar data Type de document : Article/Communication Auteurs : Melissa F. Rosa, Auteur ; Douglas A. Stow, Auteur Année de publication : 2014 Article en page(s) : pp 570-588 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] biomasse (combustible) [Termes descripteurs IGN] carte thématique [Termes descripteurs IGN] classification orientée objet [Termes descripteurs IGN] combustible [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] fusion de données [Termes descripteurs IGN] incendie [Termes descripteurs IGN] orthoimage [Termes descripteurs IGN] orthoimage couleur [Termes descripteurs IGN] San Diego [Termes descripteurs IGN] simulation Résumé : (auteur) Fuel type mapping of the wildland-urban interface (WUI) in support of fire spread simulation modelling should include both natural and urban features. The objective of this study was to evaluate the utility of (1) Light Detection and Ranging (LiDAR) structural data, (2) ortho-image data and (3) a combination of both as input to an object-based classification approach for mapping fuels within two WUI areas in San Diego, California. A separability analysis was utilized to determine the surface topographical and spectral layers most influential for discriminating WUI fuels. An accuracy assessment revealed that the combination of LiDAR and ortho-image data inputs substantially increased classification accuracy by 20–30% and achieved overall accuracies > 80%. Results from the study provide knowledge on how reliable fuel types within the WUI can be mapped using high-resolution LiDAR and ortho-image data while presenting new insights into fuel type mapping. Numéro de notice : A2014-417 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://www.tandfonline.com/doi/full/10.1080/10106049.2013.819040 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73951 [article]

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Histogram curve matching approaches for object-based image classification of land cover and land use / Sory I. Toure in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 5 (May 2013)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 79 n° 5 (May 2013) . - pp 433 - 440 Titre : Histogram curve matching approaches for object-based image classification of land cover and land use Type de document : Article/Communication Auteurs : Sory I. Toure, Auteur ; Douglas A. Stow, Auteur ; John R. Weeks, Auteur ; Sunil Kumar, Auteur Année de publication : 2013 Article en page(s) : pp 433 - 440 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] appariement d'histogramme [Termes descripteurs IGN] classificateur [Termes descripteurs IGN] classification barycentrique [Termes descripteurs IGN] classification orientée objet [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] San Diego Résumé : (Auteur) The classification of image-objects is usually done using parametric statistical measures of central tendency and/or dispersion (e.g., mean or standard deviation). The objectives of this study were to analyze digital number histograms of image objects and evaluate classifications measures exploit-ing characteristic signatures of such histograms. Two histo-grams matching classifiers were evaluated and compared to the standard nearest neighbor to mean classifier. An ADS40 airborne multispectral image of San Diego, California was used for assessing the utility of curve matching classifiers in a geographic object-based image analysis (GEOBIA) approach. The classifications were performed with data sets having 0.5m, 2.5m, and 5m spatial resolutions. Results show that histograms are reliable features for characterizing classes. Also, both histogram matching classifiers consistently per-formed better than the one based on the standard nearest neighbor to mean rule. The highest classification accuracies were produced with images having 2.5m spatial resolution. Numéro de notice : A2013-281 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.79.5.433 En ligne : https://doi.org/10.14358/PERS.79.5.433 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32419 [article]

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Examining the effect of spatial resolution and texture window size on classification accuracy: an urban environment case / D. Chen in International Journal of Remote Sensing IJRS, vol 25 n° 11 (June 2004)

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 25 n° 11 (June 2004) . - pp 2177 - 2092 Titre : Examining the effect of spatial resolution and texture window size on classification accuracy: an urban environment case Type de document : Article/Communication Auteurs : D. Chen, Auteur ; D.A. Stow, Auteur ; P. Gong, Auteur Année de publication : 2004 Article en page(s) : pp 2177 - 2092 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] classification par maximum de vraisemblance [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] limite de résolution géométrique [Termes descripteurs IGN] limite de résolution spectrale [Termes descripteurs IGN] milieu urbain [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] périphérie urbaine [Termes descripteurs IGN] précision de la classification [Termes descripteurs IGN] San Diego [Termes descripteurs IGN] texture d'image Résumé : (Auteur) The purpose of this paper is to evaluate spatial resolution effects on image classification. Classification maps were generated with a maximum likelihood (ML) classifier applied to three multi-spectral bands and variance texture images. A total of eight urban land use/cover classes were obtained at six spatial resolution levels based on a series of aggregated Colour Infrared Digital Orthophoto Quarter Quadrangle (DOQQ) subsets in urban and rural fringe areas of the San Diego metropolitan area. The classification results were compared using overall and individual classification accuracies. Classification accuracies were shown to be influenced by image spatial resolution, window size used in texture extraction and differences in spatial structure within and between categories. The more heterogeneous arc the land use/cover units and the more fragmented are the landscapes, the finer the resolution required. Texture was more effective for improving the classification accuracy of land use classes at finer resolution levels. For spectrally homogeneous classes, a small window is preferable. But for spectrally heterogeneous classes, a large window size is required. Numéro de notice : A2004-230 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26757 [article]

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Strategies for integrating information from multiple resolutions into land-use/land-cover classification routines / D.M. Chen in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 11 (November 2003)

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Land-cover change monitoring with classification trees using Landsat TM and ancillary data / J. Rogan in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 7 (July 2003)

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