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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])  

Public [article]  inGeocarto international > vol 35 n° 2 [01/02/2020] . - pp 168 - 187 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 statistique Résumé : (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 [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)  

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]

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)  

Public [article]  inSurvey review > vol 48 n° 351 (October 2016) . - pp 430 - 437 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'image Résumé : (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 [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)  

Public [article]  inGeocarto international > Vol 31 n° 9 - 10 (October - November 2016) . - pp 956 - 965 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-saturation Résumé : (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 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2016051	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Distinctive order based self-similarity descriptor for multi-sensor remote sensing image matching / Amin Sedaghat in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 62 – 71 Titre : Distinctive order based self-similarity descriptor for multi-sensor remote sensing image matching Type de document : Article/Communication Auteurs : Amin Sedaghat, Auteur ; Hamid Ebadi, Auteur Année de publication : 2015 Article en page(s) : pp 62 – 71 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement d'images [Termes IGN] extraction automatique [Termes IGN] image Geoeye [Termes IGN] image IRS [Termes IGN] image Landsat-ETM+ [Termes IGN] image multicapteur [Termes IGN] image Quickbird [Termes IGN] image SPOT 4 [Termes IGN] image SPOT 5 [Termes IGN] image SPOT 6 [Termes IGN] image Terra-ASTER [Termes IGN] image Worldview [Termes IGN] invariant [Termes IGN] SIFT (algorithme) Résumé : (auteur) Robust, well-distributed and accurate feature matching in multi-sensor remote sensing image is a difficult task duo to significant geometric and illumination differences. In this paper, a robust and effective image matching approach is presented for multi-sensor remote sensing images. The proposed approach consists of three main steps. In the first step, UR-SIFT (Uniform robust scale invariant feature transform) algorithm is applied for uniform and dense local feature extraction. In the second step, a novel descriptor namely Distinctive Order Based Self Similarity descriptor, DOBSS descriptor, is computed for each extracted feature. Finally, a cross matching process followed by a consistency check in the projective transformation model is performed for feature correspondence and mismatch elimination. The proposed method was successfully applied for matching various multi-sensor satellite images as: ETM+, SPOT 4, SPOT 5, ASTER, IRS, SPOT 6, QuickBird, GeoEye and Worldview sensors, and the results demonstrate its robustness and capability compared to common image matching techniques such as SIFT, PIIFD, GLOH, LIOP and LSS. Numéro de notice : A2015-852 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.06.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79222 [article]

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)  

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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)  

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Evaluation 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)  

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Mapping 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)  

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Dynamics of coastal landform features along the southern Tamil Nadu of India by using remote sensing and Geographic Information System / P. Mujabar in Geocarto international, vol 27 n° 4 (July 2012)  

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Use 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)  

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Efficient parallel algorithm for pixel classification in remote sensing imagery / U. Maulik in Geoinformatica, vol 16 n° 2 (April 2012)  

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A longitudinal study of malaria associated with deforestation in Sonitpur district of Assam, India / M. Nath in Geocarto international, vol 27 n° 1 (February 2012)  

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Use of geo-spatial information and technologies for analyzing morphological changes in the Greater Visakhapatnal coastal region east coast of India / P. Latha in Geocarto international, vol 26 n° 5 (August 2011)  

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Epipolar arrangement of satellite imagery by projection trajectory simplification / M. Wang in Photogrammetric record, vol 25 n° 132 (December 2010 - February 2011)  

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