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Landslide susceptibility mapping using maximum entropy and support vector machine models along the highway corridor, Garhwal Himalaya / Vijendra Kumar Pandey in Geocarto international, vol 35 n° 2 ([01/02/2020])
[article]
Titre : Landslide susceptibility mapping using maximum entropy and support vector machine models along the highway corridor, Garhwal Himalaya Type de document : Article/Communication Auteurs : Vijendra Kumar Pandey, Auteur ; Hamid Reza Pourghasemi, Auteur ; Milap Chand Sharma, Auteur Année de publication : 2020 Article en page(s) : pp 168 - 187 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] autoroute
[Termes IGN] classification dirigée
[Termes IGN] effondrement de terrain
[Termes IGN] entropie maximale
[Termes IGN] Himalaya
[Termes IGN] image IRS-LISS
[Termes IGN] image Landsat-8
[Termes IGN] Linear Imaging Self-Scanning System
[Termes IGN] modèle statistique
[Termes IGN] mousson
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] séparateur à vaste marge
[Termes IGN] test statistiqueRésumé : (Auteur) The main objective of this study to produce landslide susceptibility zones using maximum entropy (MaxEnt) and support vector machine (SVM) data-driven models along the Tipari to Ghuttu highway corridors in the Garhwal Himalaya. A landslide inventory has been prepared through field surveys and LISS-IV and Landsat 8 satellite images. The datasets of 85 landslides were categorised into training and test sets. In this study 11 landslide conditioning variables were used that are; altitude, slope angle, aspect, plan curvature, topographic wetness index, normalised difference vegetation index (NDVI), land use, soil texture, distance to rivers, distance to faults, and distance to the road. The result produced using MaxEnt and SVM model were subsequently validated using receiver operating characteristics curve (ROC) with test sets of landslide dataset. Both the models have good prediction capabilities. MaxEnt has ROC value of 0.78 while SVM has the highest prediction rate of 0.85. Numéro de notice : A2020-036 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1510038 Date de publication en ligne : 20/09/2018 En ligne : https://doi.org/10.1080/10106049.2018.1510038 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94519
in Geocarto international > vol 35 n° 2 [01/02/2020] . - pp 168 - 187[article]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)
[article]
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'imageRésumé : (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
in Geocarto international > vol 32 n° 6 (June 2017) . - pp 640 - 654[article]Distributed texture-based land cover classification algorithm using hidden Markov model for multispectral data / S. Jenicka in Survey review, vol 48 n° 351 (October 2016)
[article]
Titre : Distributed texture-based land cover classification algorithm using hidden Markov model for multispectral data Type de document : Article/Communication Auteurs : S. Jenicka, Auteur ; A. Suruliandi, Auteur Année de publication : 2016 Article en page(s) : pp 430 - 437 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] image IRS-LISS
[Termes IGN] modèle de Markov caché
[Termes IGN] occupation du sol
[Termes IGN] précision de la classification
[Termes IGN] texture d'imageRésumé : (Auteur) Land cover classification is a vital application area in the satellite image processing domain. Texture is a useful feature in land cover classification. In this paper, we propose a distributed texture-based land cover classification algorithm using Hidden Markov Model (HMM). Here, HMM is used for texture-based classification of remotely sensed images. Furthermore, to enhance the performance, data-intensive remotely sensed image is segmented and distributed into parallel sessions. Experiments were conducted on IRS P6 LISS-IV data, and the results were evaluated based on the confusion matrix, classification accuracy, and Kappa statistics. These results indicate that the proposed algorithm achieves a classification accuracy of 88.75%. Numéro de notice : A2016-824 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1179/1752270615Y.0000000041 En ligne : https://doi.org/10.1179/1752270615Y.0000000041 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82640
in Survey review > vol 48 n° 351 (October 2016) . - pp 430 - 437[article]Image processing and GIS techniques applied to high resolution satellite data for lineament mapping of thermal power plant site in Allahabad district, U.P., India / Aniruddha Uniyal in Geocarto international, Vol 31 n° 9 - 10 (October - November 2016)
[article]
Titre : Image processing and GIS techniques applied to high resolution satellite data for lineament mapping of thermal power plant site in Allahabad district, U.P., India Type de document : Article/Communication Auteurs : Aniruddha Uniyal, Auteur ; P.N. Shah, Auteur ; Rajiva Mohan, Auteur Année de publication : 2016 Article en page(s) : pp 956 - 965 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes principales
[Termes IGN] centrale thermique
[Termes IGN] fusion d'images
[Termes IGN] géomorphologie locale
[Termes IGN] image IRS-LISS
[Termes IGN] Inde
[Termes IGN] linéament
[Termes IGN] système d'information géographique
[Termes IGN] transformation intensité-teinte-saturationRésumé : (auteur) The present study is based on digital analysis of IRS 1C/1D LISS-III and IRS P6 LISS-IV images for identification of lineaments in Meja Thermal Power Plant site in Allahabad district. In spite of all limitations due to anthropogenic activities of stone quarrying and criss cross unmetalled roads, almost non-existent vegetation indicators and soil moisture, the efforts were made to identify and map a number of lineaments in the study area and these were subsequently verified in the field. Most of the lineaments identified and mapped are not having any major displacement along them or are not displacing or truncating any major rock unit. Field investigations have revealed that there is no drastic change in the trend of rocks along the lineaments mapped in the study area. On the basis of digital analysis of IRS P6 LISS-IV data NE–SW and NW–SE trending lineaments have been identified and mapped. Some NNE–SSW trending lineaments have also been mapped. All the lineaments demarcated in this area still need to be correlated with the seismic data of the area by superimposing the microseismicity data over lineaments. Numéro de notice : A2016-668 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1094525 Date de publication en ligne : 02/11/2015 En ligne : http://dx.doi.org/10.1080/10106049.2015.1094525 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81900
in Geocarto international > Vol 31 n° 9 - 10 (October - November 2016) . - pp 956 - 965[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2016051 RAB Revue Centre de documentation En réserve L003 Disponible An intelligent approach towards automatic shape modelling and object extraction from satellite images using cellular automata based algorithm / P. V. Arun in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)
[article]
Titre : An intelligent approach towards automatic shape modelling and object extraction from satellite images using cellular automata based algorithm Type de document : Article/Communication Auteurs : P. V. Arun, Auteur Année de publication : 2014 Article en page(s) : pp 628-638 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] champ aléatoire de Markov
[Termes IGN] classification par réseau neuronal
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image IRS-LISS
[Termes IGN] image Landsat
[Termes IGN] interpolationRésumé : (auteur) Automatic feature extraction domain has witnessed the application of many intelligent methodologies over past decade; however detection accuracy of these approaches were limited as object geometry and contextual knowledge were not given enough consideration. In this paper, we propose a frame work for accurate detection of features along with automatic interpolation, and interpretation by modelling feature shape as well as contextual knowledge using advanced techniques such as SVRF, Cellular Neural Network, Core set, and MACA. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the CNN approach. CNN has been effective in modelling different complex features effectively and complexity of the approach has been considerably reduced using corset optimization. The system has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prologue approach. System has been also proved to be effective in providing intelligent interpolation and interpretation of random features. Numéro de notice : A2014-419 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.826738 En ligne : https://doi.org/10.1080/10106049.2013.826738 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73955
in Geocarto international > vol 29 n° 5 - 6 (August - October 2014) . - pp 628-638[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2014031 RAB Revue Centre de documentation En réserve L003 Disponible Demarcation of potential avalanche sites using remote sensing and ground observations: a case study of Gangotri glacier / Snehmani A. Bhardwaj in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)PermalinkEvaluation of the spatial changes in seagrass cover in the lagoons of Lakshadweep islands, India, using IRS LISS III satellite images / E.P. Nobi in Geocarto international, vol 27 n° 8 (December 2012)PermalinkMapping crop types, irrigated areas, and cropping intensities in heterogeneous landscapes of southern India using multi-temporal medium-resolution imagery: implications for assessing water use in agriculture / E. Heller in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 8 (August 2012)PermalinkUse of high-resolution satellite imagery for investigating acid mine drainage from artisanal coal mining in North-Eastern India / B. Blahwar in Geocarto international, vol 27 n° 3 (June 2012)PermalinkApplication of remote sensing and geographic information system in change detection of the Netravati and Gurpur river channels, Karnataka, India / A. Kumar in Geocarto international, vol 25 n° 5 (August 2010)PermalinkApplication of satellite image processing techniques for Talakadu a unique archaeological landscape in India / M.B. Rajani in Photo interprétation, European journal of applied remote sensing, vol 45 n° 4 (novembre 2009)PermalinkEstimation de l'évolution de l'artificialisation des terres à l'échelle départementale par télédétection : le cas de l'Ille et Vilaine / Rahim Aguejdad in Photo interprétation, European journal of applied remote sensing, vol 45 n° 1 (mars 2009)PermalinkAutomatde co-registration of images from multiple bands of LISS-4 camera / P. Radhadevi in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 1 (January - February 2009)PermalinkTopographic data bases in the product generation of IRS-P6 Liss-4 imagery / M.V. Jyothi in ISPRS Journal of photogrammetry and remote sensing, vol 63 n° 3 (May - June 2008)PermalinkMultisource classification using Support Vector Machines: an empirical comparison with Decision Tree and Neural Network classifiers / P. Watanachaturaporn in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 2 (February 2008)Permalink