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Change detection of linear features in temporally spaced remotely sensed images using edge-based grid analysis / Arati Paul in Geocarto international, vol 32 n° 6 (June 2017)  

Public [article]  inGeocarto international > vol 32 n° 6 (June 2017) . - pp 640 - 654 Titre : Change detection of linear features in temporally spaced remotely sensed images using edge-based grid analysis Type de document : Article/Communication Auteurs : Arati Paul, Auteur ; V.M. Chowdary, Auteur ; Y.K. Srivastava, Auteur ; Debsunder Dutta, Auteur ; J.R. Sharma, Auteur Année de publication : 2017 Article en page(s) : pp 640 - 654 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Calcutta [Termes IGN] densité spectrale de puissance [Termes IGN] détection de changement [Termes IGN] détection de contours [Termes IGN] Google Earth [Termes IGN] image Cartosat-1 [Termes IGN] image IRS-LISS [Termes IGN] occupation du sol [Termes IGN] seuillage d'image Résumé : (Auteur) Automatic change detection of land cover features using high-resolution satellite images, is a challenging problem in the field of intelligent remote sensing data interpretation, and is becoming more and more effective for its applications viz. urban planning and monitoring, disaster assessment etc. In the present study, a change in detection approach based on the image morphology that analyses change in the local image grids is proposed. In this approach, edges from both the images are extracted and grid wise comparison is made by probabilistic thresholding and power spectral density analysis for identifying change area. One of the advantages of the proposed methodology is that the temporal images used in the change analysis need not be radiometrically corrected as analysis is based on edge extractions. The grid-based analysis further reduces the error, which might have been introduced by image mis-registration. The proposed methodology is validated by finding the temporal changes in the linear land cover features in parts of Kolkata city, India using three different image data-sets from LISS IV, Cartosat-1 and Google earth having varied spatial resolutions of 5.8 m, 2.5 m and about 1 m, respectively. The overall accuracy in identifying changes is found to be 64.82, 73.86 and 80.93% for LISS IV, Cartosat-1 and Google earth data-set, respectively. Numéro de notice : A2017-275 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1167966 Date de publication en ligne : 01/04/2016 En ligne : http://dx.doi.org/10.1080/10106049.2016.1167966 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85304 [article]

Performance evaluation of land change simulation models using landscape metrics / Sadeq Dezhkam in Geocarto international, vol 32 n° 6 (June 2017)  

Public [article]  inGeocarto international > vol 32 n° 6 (June 2017) . - pp 655 - 677 Titre : Performance evaluation of land change simulation models using landscape metrics Type de document : Article/Communication Auteurs : Sadeq Dezhkam, Auteur ; Bahman Jabbarian Amiri, Auteur ; Ali Asghar Darvishsefat, Auteur ; Yousef Sakieh, Auteur Année de publication : 2017 Article en page(s) : pp 655 - 677 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse diachronique [Termes IGN] champ aléatoire de Markov [Termes IGN] changement d'occupation du sol [Termes IGN] changement d'utilisation du sol [Termes IGN] géovisualisation [Termes IGN] Iran [Termes IGN] modèle de simulation [Termes IGN] simulation spatiale [Termes IGN] test de performance Résumé : (Auteur) This study proposes a landscape metrics-based method for model performance evaluation of land change simulation models. To quantify model performance at both landscape and class levels, a set of composition- and configuration-based metrics including number of patches, class area, landscape shape index, mean patch area and mean Euclidean nearest neighbour distance were employed. These landscape metrics provided detailed information on simulation success of a cellular automata-Markov chain (CA-Markov) model standpoint of spatial arrangement of the simulated map versus the corresponding reference layer. As a measure of model simulation success, mean relative error (MRE) of the metrics was calculated. At both landscape and class levels, the MRE values were accounted for 22.73 and 10.2%, respectively, which are further categorised into qualitative measurements of model simulation performance for simple and quick comparison of the results. Findings of the present study depict a hierarchical and multi spatial level assessment of model performance. Numéro de notice : A2017-276 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1167967 Date de publication en ligne : 08/04/2016 En ligne : http://dx.doi.org/10.1080/10106049.2016.1167967 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85305 [article]