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Comparative assessment of the measures of thematic classification accuracy / C. Liu in Remote sensing of environment, vol 107 n° 4 (30/04/2007)
[article]
Titre : Comparative assessment of the measures of thematic classification accuracy Type de document : Article/Communication Auteurs : C. Liu, Auteur ; P. Frazier, Auteur ; L. Kumar, Auteur Année de publication : 2007 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] cartographie thématique
[Termes IGN] classificateur
[Termes IGN] coefficient de corrélation
[Termes IGN] cohérence des données
[Termes IGN] niveau d'analyse
[Termes IGN] précision de la classification
[Termes IGN] précision des données
[Termes IGN] producteur
[Termes IGN] utilisateurRésumé : (Auteur) Accuracy assessment of classified imagery is an important task in remote sensing. Various measures have been developed to describe and compare the accuracy of maps and the performance of different classifiers, but the extent to which these measures are consistent with each other is largely unknown. In this paper the consistency of fourteen category-level and twenty map-level accuracy measures was tested on 595 published error matrices using nonparametric correlation coefficients (Spearman's rho and Kendall's tau-b) as well as the probability of concordance. The results show that four groups can be identified for the category-level measures and three groups for map-level measures. The consistency among the measures within a group is generally higher than that among the measures from different groups though all the measures at the same level are highly consistent with each other. We recommend that user's accuracy and producer's accuracy and the overall accuracy should be provided as primary accuracy measures and the two relative entropy change measures and the mutual information normalized by the arithmetic mean of the entropies on map and ground truthing be provided as supplementary measures. The chance-corrected, error matrix-normalized and user's and producer's accuracy-combined measures were found to contain estimation and interpretation problems at both category- and map-levels and are therefore not recommended for general use. Copyright Elsevier Numéro de notice : A2007-158 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.10.010 En ligne : https://doi.org/10.1016/j.rse.2006.10.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28521
in Remote sensing of environment > vol 107 n° 4 (30/04/2007)[article]Modelling and mapping potential hooded warbler (Wilsonia citrina) habitat using remotely sensed imagery / J. Pasher in Remote sensing of environment, vol 107 n° 3 (12 April 2007)
[article]
Titre : Modelling and mapping potential hooded warbler (Wilsonia citrina) habitat using remotely sensed imagery Type de document : Article/Communication Auteurs : J. Pasher, Auteur ; Dominique King, Auteur ; K. Lindsay, Auteur Année de publication : 2007 Article en page(s) : pp 471 - 483 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Aves
[Termes IGN] carte thématique
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] habitat animal
[Termes IGN] image Ikonos
[Termes IGN] image Landsat
[Termes IGN] luminance lumineuse
[Termes IGN] Ontario (Canada)
[Termes IGN] photo-interprétation
[Termes IGN] précision de la classification
[Termes IGN] régression logistiqueRésumé : (Auteur) Modelling and mapping of hooded warbler (Wilsonia citrina) nesting habitat in forests of southern Ontario were conducted using Ikonos and Landsat data. The study began with an analysis of skyward hemispherical photography to determine canopy characteristics associated with nest sites. It showed that nest sites had significantly less overhead canopy cover and larger maximum gap size than in non-nest areas. These findings led to the hypothesis that brightness variability in high to moderate resolution remotely sensed imagery may be greater at nest sites than in non-nest areas due to larger shadows and greater shadow variability related to these gap characteristics. This was confirmed when, in addition to some spectral band brightness variables, several image texture and spectrally unmixed fraction (shadow, bare soil) variables were found to be significantly different for nest and non-nest sites in Ikonos and Landsat imagery. These significantly different variables were used in maximum likelihood classification (MLC) and logistic regression (LR) to produce maps of potential nesting habitat. Mapping was conducted with Ikonos and Landsat in a local area where most known nest sites occur, and regionally using Landsat data for almost all of the hooded warbler range in southern Ontario. For the local area mapping using Ikonos data, a posteriori probabilities for both the MLC and LR methods showed that about 62% of the nest sites set aside for validation had been classified with high probability (p > 0.70) in the nest class. MLC mapping accuracy was 70% for the validation nest sites and 87% of validation nest sites were within 10 m of classified nesting habitat, a distance approximately equivalent to expected positional error in the data. LR accuracy was slightly lower. Nest site MLC mapping accuracy in the local area using Landsat data was 87% but the map was much coarser due to the larger pixel size. Regional mapping with Landsat imagery produced lower classification accuracy due to high errors of commission for the habitat class. This resulted from a poor spatial distribution and low number of observations of nest sites throughout the region compared to the local area, while the non-nest site data distribution was too narrow, having been defined and assessed (using standard accepted methods) as areas with no ground shrubs. If either of these problems can be ameliorated, regional mapping accuracy may improve. Copyright Elsevier Numéro de notice : A2007-139 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.09.022 En ligne : https://doi.org/10.1016/j.rse.2006.09.022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28502
in Remote sensing of environment > vol 107 n° 3 (12 April 2007) . - pp 471 - 483[article]Atmospheric correction algorithm for MERIS above case-2 waters / Th. Schroeder in International Journal of Remote Sensing IJRS, vol 28 n°7-8 (April 2007)
[article]
Titre : Atmospheric correction algorithm for MERIS above case-2 waters Type de document : Article/Communication Auteurs : Th. Schroeder, Auteur ; I. Behnert, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 1469 - 1486 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] aérosol
[Termes IGN] classification par réseau neuronal
[Termes IGN] correction atmosphérique
[Termes IGN] image Envisat-MERIS
[Termes IGN] modèle de transfert radiatif
[Termes IGN] réflectanceRésumé : (Auteur) The development and validation of an atmospheric correction algorithm designed for the Medium Resolution Imaging Spectrometer (MERIS) with special emphasis on case-2 waters is described. The algorithm is based on inverse modelling of radiative transfer (RT) calculations using artificial neural network (ANN) techniques. The presented correction scheme is implemented as a direct inversion of spectral top-of-atmosphere (TOA) radiances into spectral remote sensing reflectances at the bottom-of-atmosphere (BOA), with additional output of the aerosol optical thickness (AOT) at four wavelengths for validation purposes. The inversion algorithm was applied to 13 MERIS Level 1b data tracks of 2002-2003, covering the optically complex waters of the North and Baltic Sea region. A validation of the retrieved AOTs was performed with coincident in situ automatic sun-sky scanning radiometer measurements of the Aerosol Robotic Network (AERONET) from Helgoland Island located in the German Bight. The accuracy of the derived reflectances was validated with concurrent ship-borne reflectance measurements of the SIMBADA hand-held field radiometer. Compared to the MERIS Level2 standard reflectance product generated by the processor versions 3.55, 4.06 and 6.3, the results of the proposed algorithm show a significant improvement in accuracy, especially in the blue part of the spectrum, where the MERIS Level 2 reflectances result in errors up to 122% compared to only 19% with the proposed algorithm. The overall mean errors within the spectral range of 412.5-708.75 nm are calculated to be 46.2% and 18.9% for the MERIS Level2 product and the presented algorithm, respectively. Copyright Taylor & Francis Numéro de notice : A2007-176 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600962574 En ligne : https://doi.org/10.1080/01431160600962574 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28539
in International Journal of Remote Sensing IJRS > vol 28 n°7-8 (April 2007) . - pp 1469 - 1486[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-07041 RAB Revue Centre de documentation En réserve L003 Disponible Improving land-cover classification using recognition threshold neural networks / M.J. Aitkenhead in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 4 (April 2007)
[article]
Titre : Improving land-cover classification using recognition threshold neural networks Type de document : Article/Communication Auteurs : M.J. Aitkenhead, Auteur ; R. Dyer, Auteur Année de publication : 2007 Article en page(s) : pp 413 - 421 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] image Landsat
[Termes IGN] Philippines
[Termes IGN] seuillage d'image
[Termes IGN] surface cultivéeRésumé : (Auteur) The use of neural networks to classify land-cover from remote sensing imagery relies on the ability to determine a winner from the candidate land-cover types based on the imagery information available. In the case of a “winner- takes-all” scenario, this does not allow us a measure of how much the prediction of each pixel’s land-cover can be trusted. We present a three-stage method where only winning candidates which are given a clear lead over the other land-cover types are accepted, with a neighborhood relationship and the application of mixed pixels being used to provide full classification. This method allows us to place more faith in the resulting map than simply taking the winner, and results in a higher accuracy of classification. The method is applied to Landsat imagery of an area of the Philippines where natural, urban, and cultivated land-cover types exist. Copyright ASPRS Numéro de notice : A2007-143 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.4.413 En ligne : https://doi.org/10.14358/PERS.73.4.413 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28506
in Photogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 4 (April 2007) . - pp 413 - 421[article]Mapping land cover from detailed aerial photography data using textural and neural network analysis / R. Cots-Folch in International Journal of Remote Sensing IJRS, vol 28 n°7-8 (April 2007)
[article]
Titre : Mapping land cover from detailed aerial photography data using textural and neural network analysis Type de document : Article/Communication Auteurs : R. Cots-Folch, Auteur ; M.J. Aitkenhead, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 1625 - 1642 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse texturale
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par réseau neuronal
[Termes IGN] image aérienne
[Termes IGN] paysage agricole
[Termes IGN] photographie panchromatique
[Termes IGN] utilisation du solRésumé : (Auteur) Automated mapping of land cover using black and white aerial photographs, as an alternative method to traditional photo-interpretation, requires using methods other than spectral analysis classification. To this end, textural measurements have been shown to be useful indicators of land cover. In this work, a neural network model is proposed and tested to map historical land use/land cover (LUC) from very detailed panchromatic aerial photographs (5m resolution) using textural measurements. The method is used to identify different land use and management types (e.g. traditional versus mechanized vineyard systems). These have been tested with known ground reference data. The results show the potential of the methodology to obtain automatic, historic, and very detailed cartography information from a complex landscape such as the mountainous and Mediterranean region to which it is applied here, and the advantages that this method has over traditional methods. Copyright Taylor & Francis Numéro de notice : A2007-177 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600887722 En ligne : https://doi.org/10.1080/01431160600887722 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28540
in International Journal of Remote Sensing IJRS > vol 28 n°7-8 (April 2007) . - pp 1625 - 1642[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-07041 RAB Revue Centre de documentation En réserve L003 Disponible An operational MISR pixel classifier using support vector machines / D. Mazzoni in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)PermalinkA data-mining approach to associating MISR smoke plume heights with MODIS fire measurements / D. Mazzoni in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)PermalinkSupport vector machines for recognition of semi-arid vegetation types using MISR multi-angle imagery / L. Su in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)PermalinkSupport vector machines regression for retrieval of leaf area index from multiangle imaging spectroradiometer / S. Durbha in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)PermalinkComparison between several feature extraction/classification methods for mapping complicated agricultural land use patches using airborne hyperspectral data / S. Lu in International Journal of Remote Sensing IJRS, vol 28 n°5-6 (March 2007)PermalinkExtended Hausdorff distance for spatial objects in GIS / D. Min in International journal of geographical information science IJGIS, vol 21 n° 3-4 (march - april 2007)PermalinkFeature extractions for small sample size classification problem / B.C. Kuo in IEEE Transactions on geoscience and remote sensing, vol 45 n° 3 (March 2007)PermalinkMERIS-FR potential for land use-land cover mapping / S. Garcia-Gigorro in International Journal of Remote Sensing IJRS, vol 28 n°5-6 (March 2007)PermalinkOil spill detection in Radarsat and Envisat SAR images / A.H. Solberg in IEEE Transactions on geoscience and remote sensing, vol 45 n° 3 (March 2007)PermalinkTerrestrial and submerged aquatic vegetation mapping in Fire Island national seashore using high spatial resolution remote sensing data / Y. Wang in Marine geodesy, vol 30 n° 1-2 (March - June 2007)Permalink