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Mapping urban growth of the capital city of Honduras from Landsat data using the impervious surface fraction algorithm / Nguyen-Thanh Son in Geocarto international, vol 31 n° 3 - 4 (March - April 2016)
[article]
Titre : Mapping urban growth of the capital city of Honduras from Landsat data using the impervious surface fraction algorithm Type de document : Article/Communication Auteurs : Nguyen-Thanh Son, Auteur ; Chi-Farn Chen, Auteur ; Cheng-Ru Chen, Auteur ; Shou-Hao Chiang, Auteur Année de publication : 2016 Article en page(s) : pp 328 - 341 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] croissance urbaine
[Termes IGN] Honduras
[Termes IGN] image Landsat
[Termes IGN] surface imperméable
[Termes IGN] surveillance de l'urbanisation
[Termes IGN] urbanisationRésumé : (Auteur) This study developed an impervious surface fraction algorithm (ISFA) for automatic mapping of urban areas from Landsat data. We processed the data for 2001 and 2014 to trace the urbanization of Tegucigalpa, the capital city of Honduras, using a four-step procedure: (1) data pre-processing to perform image reflectance normalization, (2) quantification of impervious surface area (ISA) using ISFA, (3) accuracy assessment of mapping results and (4) change analysis of urban growth. The mapping results compared with the ground reference data confirmed the validity of ISFA for automatic delineation of ISA in the study region. The overall accuracy and Kappa coefficient achieved for 2001 were 92.8% and 0.86, while the values for 2014 were 91.8% and 0.84, respectively. The results of change detection between the classification maps indicated that ISA increased approximately 1956.7 ha from 2001 to 2014, mainly attributing to the increase of the city’s population. Numéro de notice : A2016-153 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1047469 Date de publication en ligne : 22/05/2015 En ligne : http://www.tandfonline.com/doi/full/10.1080/10106049.2015.1047469 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80390
in Geocarto international > vol 31 n° 3 - 4 (March - April 2016) . - pp 328 - 341[article]Réservation
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Titre : 3D watertight mesh generation with uncertainties from ubiquitous data Type de document : Article/Communication Auteurs : Laurent Caraffa , Auteur ; Mathieu Brédif , Auteur ; Bruno Vallet , Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2016 Collection : Lecture notes in Computer Science, ISSN 0302-9743 num. 10114 Projets : IQmulus / Métral, Claudine Conférence : ACCV 2016, 13th Asian Conference on Computer Vision 20/11/2016 24/11/2016 Taipei Taiwan Proceedings Springer Importance : pp 377 - 391 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algorithme Graph-Cut
[Termes IGN] carte de confiance
[Termes IGN] distance de Hausdorff
[Termes IGN] incertitude géométrique
[Termes IGN] maille triangulaire
[Termes IGN] reconstruction d'objet
[Termes IGN] semis de points
[Termes IGN] seuillage
[Termes IGN] surface imperméable
[Termes IGN] théorie de Dempster-ShaferRésumé : (auteur) In this paper, we propose a generic framework for watertight mesh generation with uncertainties that provides a confidence measure on each reconstructed mesh triangle. Its input is a set of vision-based or Lidar-based 3D measurements which are converted to a set of mass functions that characterize the level of confidence on the occupancy of the scene as occupied, empty or unknown based on Dempster-Shafer Theory. The output is a multi-label segmentation of the ambient 3D space expressing the confidence for each resulting volume element to be occupied or empty. While existing methods either sacrifice watertightness (local methods) or need to introduce a smoothness prior (global methods), we derive a per-triangle confidence measure that is able to gradually characterize when the resulting surface patches are certain due to dense and coherent measurements and when these patches are more uncertain and are mainly present to ensure smoothness and/or watertightness. The surface mesh reconstruction is formulated as a global energy minimization problem efficiently optimized with the α-expansion algorithm. We claim that the resulting confidence measure is a good estimate of the local lack of sufficiently dense and coherent input measurements, which would be a valuable input for the next-best-view scheduling of a complementary acquisition.
Beside the new formulation, the proposed approach achieves state-of-the-art results on surface reconstruction benchmark. It is robust to noise, manages high scale disparity and produces a watertight surface with a small Hausdorff distance in uncertainty area thanks to the multi-label formulation. By simply thresholding the result, the method shows a good reconstruction quality compared to local algorithms on high density data. This is demonstrated on a large scale reconstruction combining real-world datasets from airborne and terrestrial Lidar and on an indoor scene reconstructed from images.Numéro de notice : C2016-024 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-319-54190-7_23 Date de publication en ligne : 12/03/2017 En ligne : http://doi.org/10.1007/978-3-319-54190-7_23 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84627 Documents numériques
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3D watertight mesh generation ... - pdf auteurAdobe Acrobat PDF Spatial analysis of high-resolution urban thermal patterns in Vojvodina, Serbia / Dusan Jovanovic in Geocarto international, vol 30 n° 5 - 6 (May - July 2015)
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Titre : Spatial analysis of high-resolution urban thermal patterns in Vojvodina, Serbia Type de document : Article/Communication Auteurs : Dusan Jovanovic, Auteur ; Miro Govedarica, Auteur ; Filip Sabo, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 483 - 505 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] couvert végétal
[Termes IGN] DMC
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] image Worldview
[Termes IGN] occupation du sol
[Termes IGN] régression linéaire
[Termes IGN] Serbie
[Termes IGN] surface imperméable
[Termes IGN] température au solRésumé : (auteur) Main objective of this study was to establish a relationship between land cover and land surface temperature (LST) in urban and rural areas. The research was conducted using Landsat, WorldView-2 (WV-2) and Digital Mapping Camera. Normalised difference vegetation index and normalised difference built-up index were used for establishing the relation between built-up area, vegetation cover and LST for spatial resolution of 30 m. Impervious surface and vegetation area generated from Digital Mapping Camera from Intergraph and WV-2 were used to establish the relation between built-up area, vegetation cover and LST for spatial resolutions of 0.1, 0.5 and 30 m. Linear regression models were used to determine the relationship between LST and indicators. Main contribution of this research is to establish the use of combining remote sensing sensors with different spectral and spatial resolution for two typical settlements in Vojvodina. Correlation coefficients between LST and LST indicators ranged from 0.602 to 0.768. Numéro de notice : A2015-293 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2014.985747#abstract Date de publication en ligne : 11/12/2014 En ligne : http://www.tandfonline.com/doi/full/10.1080/10106049.2014.985747#abstract Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76441
in Geocarto international > vol 30 n° 5 - 6 (May - July 2015) . - pp 483 - 505[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2015031 RAB Revue Centre de documentation En réserve L003 Disponible Data-driven feature learning for high resolution urban land-cover classification / Piotr Andrzej Tokarczyk (2015)
Titre : Data-driven feature learning for high resolution urban land-cover classification Type de document : Thèse/HDR Auteurs : Piotr Andrzej Tokarczyk, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2015 Collection : Dissertationen ETH num. 22544 Format : 21 x 30 cm Note générale : bibliographie
A thesis submitted to attain the degree of doctor of sciences of ETH ZurichLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse en composantes principales
[Termes IGN] classification dirigée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] environnement de développement
[Termes IGN] image à très haute résolution
[Termes IGN] image à ultra haute résolution
[Termes IGN] milieu urbain
[Termes IGN] occupation du sol
[Termes IGN] prise en compte du contexte
[Termes IGN] ruissellement
[Termes IGN] surface imperméable
[Termes IGN] théorie de Dempster-ShaferRésumé : (auteur) Automated classification of aerial and satellite images is one of the fundamental challenges in remote sensing research. Over the last 30 years, researchers have tried to overcome the tedious and time consuming manual interpretation of images. With the advent of digital technologies, classification approaches facilitating image interpretation have emerged. They were quickly embraced, and nowadays classification of remote sensing imagery is a mature field with many well-established methods. However, a major yet largely unsolved problem is the design and selection of features, that would be appropriate for a specific classification task. Usually, it is not known in advance which image features would help separating object classes in an optimal way and manual feature by trial and error is still a common practice. In the last decade rapid development of remote sensing sensors gave the end-user access to very high resolution imagery. At a ground sampling distance below a meter, small objects and ne-grained texture of larger objects emerge. Thus, to properly exploit the information that these images contain, additional contextual and textural properties of objects should be extracted. Unfortunately, classification of such images is often performed using features tailored to low- and medium resolution sensors: raw pixel values, usually augmented with either simple band ratios (e.g. in form of vegetation indices), or specific texture filter banks (e.g. Gabor filters).
In this thesis, we consider the problem of feature design and selection for classification of urban land-cover from very high resolution (VHR) remote sensing images. To appropriately capture characteristic object patterns, we propose a set of simple and efficient features, called random quasi-exhaustive (RQE) feature bank. It consists of a multitude of multiscale texture features computed efficiently via integral images inside a sliding window. At the same time, we propose to sidestep manual feature selection, and let a boosting classifier choose only those features from a RQE feature bank that are able to efficiently discriminate between different object classes in a specific classification task. We believe that the proposed feature set is fairly generic to many urban remote sensing datasets, such that the features selected by the classifier can be adapted to the characteristics of a certain image: different lighting or different scene structures.
We start with presenting the developed framework for supervised classification of land-cover in urban environments. We demonstrate the efficiency of a boosting classifier used in conjunction with the RQE feature databank on five different very high resolution remote sensing datasets. Next, we move from supervised feature learning to unsupervised methods. Using random forest classifier, we investigate the performance of features extracted using data-driven methods, such as principal component analysis (PCA) or Deep Belief Networks (DBN). We show that, at least in our study, complex unsupervised and non-linear feature learning did not improve classification accuracy over standard linear baseline methods. Finally, we use the developed supervised classification framework for an application in the field of urban hydrology. We produce imperviousness maps, which are then used to model rainfall-runoff processes in urban catchments. We show that the proposed method yields results superior over state-of-the-art methods in the field of urban hydrology. Furthermore, we perform an end-to-end comparison, in which different image data sources produced using different classification methods are used as an input for a hydraulic sewer model.Numéro de notice : 17202 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : Doctoral thesis : Sciences : ETH Zurich : 2015 En ligne : http://dx.doi.org/10.3929/ethz-a-010414770 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81178 Monitoring agricultural soil sealing in peri-urban areas using remote sensing / Shiliang Su in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 4 (April 2014)
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Titre : Monitoring agricultural soil sealing in peri-urban areas using remote sensing Type de document : Article/Communication Auteurs : Shiliang Su, Auteur ; Rui Xiao, Auteur ; Yuan Zhang, Auteur Année de publication : 2014 Article en page(s) : pp 367 - 372 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] croissance urbaine
[Termes IGN] image aérienne
[Termes IGN] impact sur l'environnement
[Termes IGN] occupation du sol
[Termes IGN] périphérie urbaine
[Termes IGN] revêtement
[Termes IGN] Shanghai (Chine)
[Termes IGN] surface cultivée
[Termes IGN] surface imperméable
[Termes IGN] surveillance agricole
[Termes IGN] urbanisationRésumé : (Auteur) Soil degradation by expansion-driven sealing increases at an unexpected rate globally, but the dynamics of agricultural soil sealing in peri-urban areas remain poorly understood. This study used aerial photographs to monitor patterns of built-up land expansion and subsequent agricultural soil sealing between 1994 and 2006 in peri-urban areas of Shanghai, China. Results indicated that a total of 152,706.5 ha of agricultural soils were sealed. In particular, residential land and industrial land were the major contributors. Buffer analysis demonstrated that agricultural soils with high proximity to roads and urban centers are more vulnerable to be sealed. Percentage of sealed agricultural soils of total agricultural soils had linear relationships with population growth and economic development. These results quantitatively document the impacts of urbanization on agricultural soil sealing. From a management perspective, we argue that the protection of agricultural soils should be integrated with urban planning efforts in China. Numéro de notice : A2014-211 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.80.4.367 En ligne : https://doi.org/10.14358/PERS.80.4.367 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33114
in Photogrammetric Engineering & Remote Sensing, PERS > vol 80 n° 4 (April 2014) . - pp 367 - 372[article]Synergetic use of optical and polSAR imagery for urban impervious surface estimation / Huadong Guo in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 1 (January 2014)PermalinkThe use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques / Chengbin Deng in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)PermalinkMapping and assessing of urban impervious areas using multiple endmember spectral mixture analysis: a case study in the city of Tampa, Florida / Fenqing Weng in Geocarto international, vol 28 n° 7-8 (November - December 2013)PermalinkPermalinkQuantifying urban land cover change between 2001 and 2006 in the Gulf of Mexico region / George Xian in Geocarto international, vol 27 n° 6 (October 2012)PermalinkMultiple endmember unmixing of CHRIS/Proba imagery for mapping impervious surfaces in urban and suburban environments / Luca Demarchi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 9 (October 2012)PermalinkMapping impervious surfaces from superresolution enhanced CHRIS/Proba imagery using multiple endmember unmixing / Luca Demarchi in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)PermalinkTemporal mixture analysis for estimating impervious surface area from multi-temporal MODIS NDVI data in Japan / F. Yang in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)PermalinkApplication of time series Landsat images to examining land-use / land-cover dynamic change / Dong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 7 (July 2012)PermalinkApplication of time series Landsat images to examining land-use/land-cover dynamic change / Dong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 7 (July 2012)PermalinkImpervious surface area extraction from IKONOS imagery using an object-based fuzzy method / Xuefei Hu in Geocarto international, vol 26 n° 1 (February 2011)PermalinkDelineation of impervious surface from multispectral imagery and lidar incorporating knowledge based expert system rules / K. Germaine in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 1 (January 2011)PermalinkA pre-screened and normalized multiple endmember spectral mixture analysis [MESMA] for mapping impervious surface area in Lake Kasumigaura Basin, Japan / F. Yang in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 5 (September - October 2010)PermalinkTopographie et climatologie urbaine / G. Najjar in XYZ, n° 123 (juin - août 2010)PermalinkDeveloping collaborative classifiers using an Expert-based Model / Giorgos Mountrakis in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 7 (July 2009)PermalinkSubpixel urban land cover estimation: comparing cubist, random forests, and support vector regression / J. Walton in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 10 (October 2008)PermalinkImproving National Land Cover Database estimates of road network impervious cover using vector road networks in GIS / K. Thomas in SaLIS Surveying and land information science, vol 68 n° 1 (March 2008)PermalinkLand-cover change and environmental impact analysis in the Greater Mankato area of Minnesota using remote sensing and GIS modelling / F. Yuan in International Journal of Remote Sensing IJRS, vol 29 n°3-4 (February 2008)PermalinkSeasonal sensitivity analysis of impervious surface estimation with satellite imagery / C. Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 12 (December 2007)PermalinkMapping urban land cover using Quickbird NDVI and GIS spatial modeling for runoff coefficient determination / P. Thanapura in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 1 (January 2007)Permalink