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Application of catastrophe theory to spatial analysis of groundwater potential in a sub-humid tropical region: a hybrid approach / Laishram Kanta Singh in Geocarto international, vol 37 n° 3 ([01/02/2022])  

Public [article]  inGeocarto international > vol 37 n° 3 [01/02/2022] . - pp 700 - 719 Titre : Application of catastrophe theory to spatial analysis of groundwater potential in a sub-humid tropical region: a hybrid approach Type de document : Article/Communication Auteurs : Laishram Kanta Singh, Auteur ; Madan K. Jha, Auteur ; V.M. Chowdary, Auteur Année de publication : 2022 Article en page(s) : pp 700 - 719 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse multicritère [Termes IGN] analyse spatiale [Termes IGN] couche thématique [Termes IGN] drainage [Termes IGN] eau souterraine [Termes IGN] gestion de l'eau [Termes IGN] Inde [Termes IGN] pondération [Termes IGN] processus de hiérarchisation analytique [Termes IGN] zone tropicale humide Résumé : (auteur) Geospatial techniques and Multi-Criteria Decision Analysis (MCDA) play a crucial role in the planning and management of land and water resources. GIS-based MCDA technique "Catastrophe theory" has been recently proposed for evaluating groundwater potential. However, the major limitation of "Catastrophe theory" is that only quantitative factors/thematic layers can be used for assessing groundwater potential, though qualitative factors are equally important. To overcome this inherent limitation, a novel GIS-based MCDA approach named "Hybrid Catastrophe" technique is proposed in this study. The "Hybrid Catastrophe" technique integrates the original "Catastrophe theory" with the "Analytic Hierarchy Process (AHP)" to take into account both qualitative and quantitative thematic layers for assessing groundwater potential, thereby improving the reliability and versatility of the original Catastrophe technique. The applicability of "Hybrid Catastrophe" technique is demonstrated through a case study wherein 8 influential thematic layers (both quantitative and qualitative) were considered for assessing groundwater potential. The four quantitative layers were assigned weights based on the "Catastrophe theory" and the remaining four qualitative layers were assigned weights based on the "AHP theory". These thematic layers were integrated in GIS to delineate groundwater potential zones. The "Hybrid Catastrophe" technique yields four groundwater potential zones in the study area: (i) "very good" (covering 16% of the study area), (ii) "good" (54%), (iii) "moderate" (29%) and (iv) "poor" (1%) and its accuracy was found to be 77% that is reasonably high. The proposed "Hybrid Catastrophe" technique is versatile and it can be successfully applied to other parts of the world for evaluating groundwater potential at diverse spatial scales irrespective of agro-climatic, hydrologic and hydrogeologic conditions. Numéro de notice : A2022-343 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1737970 Date de publication en ligne : 11/03/2020 En ligne : https://doi.org/10.1080/10106049.2020.1737970 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100524 [article]

Wavelet and non-parametric statistical based approach for long term land cover trend analysis using time series EVI data / Niraj Priyadarshi in Geocarto international, vol 35 n° 5 ([01/04/2020])  

Public [article]  inGeocarto international > vol 35 n° 5 [01/04/2020] . - pp 512 - 534 Titre : Wavelet and non-parametric statistical based approach for long term land cover trend analysis using time series EVI data Type de document : Article/Communication Auteurs : Niraj Priyadarshi, Auteur ; V.M. Chowdary, Auteur ; Iswar Chandra Das, Auteur ; Jeganathan Chockalingam, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 512 - 534 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse spatio-temporelle [Termes IGN] changement d'occupation du sol [Termes IGN] Enhanced vegetation index [Termes IGN] filtrage du bruit [Termes IGN] série temporelle [Termes IGN] transformation en ondelettes Résumé : (auteur) Land cover change analysis was carried out using Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) time series data for the period 2005–2014. MODIS EVI data coupled with Quality Assessment Science Data Sets (QASDS) was de-noised with Savitzky–Golay filter while enhancing quality and preserving the temporal profile of EVI. Wavelet transform (WT) based approach along with Sen slope’s method was used for land cover change and trend analysis. The WT based approach is useful for studying multiscale and non-stationary processes. Mann–Kendall test was performed to confirm the significance of the identified trends. Proposed approach identified 358 locations as change points, where 285 (79.6%) and 73 (20.4%) locations were detected as ‘Change’ and ‘False Change’ with respect to high resolution images. The proposed approach is useful for monitoring land cover changes that provide vital inputs for sustainable management of land resources. Numéro de notice : A2020-143 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1520925 Date de publication en ligne : 24/10/2018 En ligne : https://doi.org/10.1080/10106049.2018.1520925 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94769 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2020051	RAB	Revue	Centre de documentation	En réserve L003	Disponible

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]