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A review of accuracy assesment for object-based image analysis: from per pixel to per-polygon approaches [review article] / Su Ye in ISPRS Journal of photogrammetry and remote sensing, vol 141 (July 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 141 (July 2018) . - pp 137 - 147 Titre : A review of accuracy assesment for object-based image analysis: from per pixel to per-polygon approaches [review article] Type de document : Article/Communication Auteurs : Su Ye, Auteur ; Robert Gilmore Pontius, Auteur ; Rahul Rakshit, Auteur Année de publication : 2018 Article en page(s) : pp 137 - 147 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse d'image orientée objet [Termes IGN] classification automatique [Termes IGN] classification pixellaire [Termes IGN] échantillonnage de données [Termes IGN] estimation de précision [Termes IGN] polygone Résumé : (Editeur) Object-based image analysis (OBIA) has gained widespread popularity for creating maps from remotely sensed data. Researchers routinely claim that OBIA procedures outperform pixel-based procedures; however, it is not immediately obvious how to evaluate the degree to which an OBIA map compares to reference information in a manner that accounts for the fact that the OBIA map consists of objects that vary in size and shape. Our study reviews 209 journal articles concerning OBIA published between 2003 and 2017. We focus on the three stages of accuracy assessment: (1) sampling design, (2) response design and (3) accuracy analysis. First, we report the literature’s overall characteristics concerning OBIA accuracy assessment. Simple random sampling was the most used method among probability sampling strategies, slightly more than stratified sampling. Office interpreted remotely sensed data was the dominant reference source. The literature reported accuracies ranging from 42% to 96%, with an average of 85%. A third of the articles failed to give sufficient information concerning accuracy methodology such as sampling scheme and sample size. We found few studies that focused specifically on the accuracy of the segmentation. Second, we identify a recent increase of OBIA articles in using per-polygon approaches compared to per-pixel approaches for accuracy assessment. We clarify the impacts of the per-pixel versus the per-polygon approaches respectively on sampling, response design and accuracy analysis. Our review defines the technical and methodological needs in the current per-polygon approaches, such as polygon-based sampling, analysis of mixed polygons, matching of mapped with reference polygons and assessment of segmentation accuracy. Our review summarizes and discusses the current issues in object-based accuracy assessment to provide guidance for improved accuracy assessments for OBIA. Numéro de notice : A2018-286 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.04.002 Date de publication en ligne : 02/07/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.04.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90401 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018071	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018073	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018072	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Range of categorical associations for comparison of maps with mixed pixels / Robert Gilmore Pontius in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 8 (August 2009)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 75 n° 8 (August 2009) . - pp 963 - 969 Titre : Range of categorical associations for comparison of maps with mixed pixels Type de document : Article/Communication Auteurs : Robert Gilmore Pontius, Auteur ; J. Connors, Auteur Année de publication : 2009 Article en page(s) : pp 963 - 969 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse comparative [Termes IGN] décomposition du pixel [Termes IGN] image multi sources [Termes IGN] Massachusetts (Etats-Unis) [Termes IGN] matrice [Termes IGN] segmentation d'image [Termes IGN] segmentation multi-échelle Résumé : (Auteur) This paper presents a method to compare maps that contain pixels that have partial membership to multiple categories, i.e., mixed or soft classified pixels. The method quantifies ranges for associations among categories based upon possible variations in sub-pixel spatial allocation. The paper derives the mathematical equations for constructing the range of associations based on three types of cross-tabulation matrices, the greatest matrix, the random matrix, and the least matrix. We demonstrate how the analysis can be combined with multiple resolution map comparison to specify the resolution at which clusters exist on a single map or between two maps. The method produces a range that reflects the amount of uncertainty in the categorical associations. We illustrate the procedure with both a simple example and data from the Plum Island Ecosystems study site in Massachusetts, USA. Numéro de notice : A2009-309 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.75.8.963 En ligne : https://doi.org/10.14358/PERS.75.8.963 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29939 [article]

Can error explain map differences over time? / Robert Gilmore Pontius in Cartography and Geographic Information Science, vol 33 n° 2 (April 2006)  

Public [article]  inCartography and Geographic Information Science > vol 33 n° 2 (April 2006) Titre : Can error explain map differences over time? Type de document : Article/Communication Auteurs : Robert Gilmore Pontius, Auteur ; C.D. Lippitt, Auteur Année de publication : 2006 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie [Termes IGN] analyse de sensibilité [Termes IGN] analyse diachronique [Termes IGN] carte d'occupation du sol [Termes IGN] incertitude des données [Termes IGN] Massachusetts (Etats-Unis) [Termes IGN] matrice de confusion Résumé : (Auteur) This paper presents methods to test whether map error can explain the observed differences between two points in time among categories of land cover in maps. Such differences may be due to two reasons: error in the maps and change on the ground. Our methods use matrix algebra: (1) to determine whether error can explain specific types of observed categorical transitions between two maps, (2) to represent visually the differences between the maps that error cannot explain, and (3) to examine how the results are sensitive to possible variation in map error. The methods complement conventional accuracy assessment because they rely on standard confusion matrices that use either a random or a stratified sampling design. We illustrate the methods with maps from 1971 and 1999, which show seven land-cover categories for central Massachusetts. The methods detect four transitions from agriculture, range, forest, and barren in 1971 to built in 1999, which a 15 percent error cannot explain. Sensitivity analysis reveals that if the accuracy of the maps were less than 77 percent, then error could explain virtually all of the observed differences between the maps. The paper discusses the assumptions behind the methods and articulates priorities for future research. Copyright CaGISociety. Numéro de notice : A2006-288 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1559/152304006777681706 En ligne : https://doi.org/10.1559/152304006777681706 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28015 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
032-06021	RAB	Revue	Centre de documentation	En réserve L003	Disponible

A generalized cross-tabulation matrix to compare soft-classified maps at multiple resolutions / Robert Gilmore Pontius in International journal of geographical information science IJGIS, vol 20 n° 1 (january 2006)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 20 n° 1 (january 2006) . - pp 1 - 30 Titre : A generalized cross-tabulation matrix to compare soft-classified maps at multiple resolutions Type de document : Article/Communication Auteurs : Robert Gilmore Pontius, Auteur ; L. Cheuk, Auteur Année de publication : 2006 Article en page(s) : pp 1 - 30 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] algèbre de Boole [Termes IGN] classification pixellaire [Termes IGN] données multiéchelles [Termes IGN] matrice [Termes IGN] numérisation [Termes IGN] système d'information géographique Résumé : (Auteur) This paper addresses two grand challenges in the development of methods for Geographic Information Science (GIS). First, this paper presents techniques to compute a cross-tabulation matrix for soft-classified pixels. Second, it shows how to compute the cross-tabulation matrix at multiple scales. The traditional approach to construct the cross-tabulation matrix uses a Boolean operator to analyse pixels that are hard-classified. For soft-classified pixels, the contemporary approach uses a Multiplication operator ; the fuzzy approach uses a Minimum operator ; whereas this paper proposes a multiple-resolution approach that uses a Composite operator. There are difficulties with the traditional, contemporary, and fuzzy methods of computing the cross-tabulation matrix. The proposed multiple-resolution method resolves those difficulties. Furthermore, the proposed method facilitates multiple-resolution analysis, so it can examine how results change as a function of scale. The paper derives the equations to compute cross-tabulation matrices at multiple resolutions and connects those equations to ontological foundations of GIS. Numéro de notice : A2006-023 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/13658810500391024 En ligne : https://doi.org/10.1080/13658810500391024 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27750 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-06011	RAB	Revue	Centre de documentation	En réserve L003	Disponible
079-06012	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Comparison of the structure and accuracy of two land change models / Robert Gilmore Pontius in International journal of geographical information science IJGIS, vol 19 n° 2 (february 2005)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 19 n° 2 (february 2005) . - pp 243 - 265 Titre : Comparison of the structure and accuracy of two land change models Type de document : Article/Communication Auteurs : Robert Gilmore Pontius, Auteur ; J. Malanson, Auteur Année de publication : 2005 Article en page(s) : pp 243 - 265 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse comparative [Termes IGN] analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] chaîne de Markov [Termes IGN] changement d'occupation du sol [Termes IGN] Massachusetts (Etats-Unis) [Termes IGN] modèle de simulation [Termes IGN] occupation du sol [Termes IGN] prédiction Résumé : (Auteur) This paper compares two land change models in terms of appropriateness for various applications and predictive power. Cellular Automata Markov (CA-Markov) and Geomod are the two models, which have similar options to allow for specification of the predicted quantity and location of land categories. The most important structural difference is that CA-Markov has the ability to predict any transition among any number of categories, while Geomod predicts only a one-way transition from one category to one alternative category. To assess the predictive power, each model is run several times to predict land change in central Massachusetts, USA. The models are calibrated with information from 1971 to 1985, and then the models predict the change from 1985 to 1999. The method to measure the predictive power: 1) separates the calibration process from the validation process, 2) assesses the accuracy at multiple resolutions, and 3) compares the predictive model vis-A-vis a null model that predicts pure persistence. Among 24 model runs, the predictive models are more accurate than the null model at resolutions coarser than two kilometres, but not at resolutions finer than one kilometre. The choice of the options account for more variation in accuracy of runs than the choice of the model per se. The most accurate model runs are those that did not use spatial contiguity explicitly. For this particular study area, the added complexity of CA-Markov is of no benefit. Numéro de notice : A2005-050 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810410001713434 En ligne : https://doi.org/10.1080/13658810410001713434 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27188 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-05021	RAB	Revue	Centre de documentation	En réserve L003	Disponible
079-05022	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Statistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolutions / Robert Gilmore Pontius in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 10 (October 2002)  

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