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Electrical resistivity, remote sensing and geographic information system approach for mapping groundwater potential zones in coastal aquifers of Gurpur watershed / H.S. Virupaksha in Geocarto international, vol 36 n° 8 ([01/05/2021])  

Public [article]  inGeocarto international > vol 36 n° 8 [01/05/2021] . - pp 888 - 902 Titre : Electrical resistivity, remote sensing and geographic information system approach for mapping groundwater potential zones in coastal aquifers of Gurpur watershed Type de document : Article/Communication Auteurs : H.S. Virupaksha, Auteur ; K.N. Lokesh, Auteur Année de publication : 2021 Article en page(s) : pp 888 - 902 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] aquifère [Termes IGN] bassin hydrographique [Termes IGN] carte des pentes [Termes IGN] carte hydrogéologique [Termes IGN] eau souterraine [Termes IGN] géomorphologie locale [Termes IGN] Karnataka (Inde) [Termes IGN] lithologie [Termes IGN] occupation du sol [Termes IGN] potentiel hydrogène [Termes IGN] précipitation [Termes IGN] résistivité [Termes IGN] système d'information géographique [Termes IGN] utilisation du sol Résumé : (auteur) Electrical resistivity method and RS & GIS techniques are very much useful in identification of potential aquifer zones for exploitation, management and recharge of groundwater. Vertical Electrical Soundings are conducted at 35 locations in Gurpur watershed using Schlumberger array. The thematic layers like porosity, transmissivity and hydraulic conductivity are prepared using electrical resistivity data. Total of 13 thematic layers are used for vector integration and identification of Groundwater Potential Zones (GWPZ). The numerical weights and ranks are assigned to the themes based on their relationship with groundwater. The findings shows that the depth to bedrock varies from 9.1 to 44.4 m and most of the mid land and low land region shows moderate to high depths of about 25–44 m. The GWPZ are classified into five classes namely, Very Good (≈21.02 km2), Good (≈231.35 km2), Moderate (≈420.76 km2), Poor (≈185.05 km2) and Very Poor (≈19.56 km2). The Good and Moderate categories cover ≈75% of total area. Numéro de notice : A2021-483 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1624986 Date de publication en ligne : 11/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1624986 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97442 [article]

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)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 8 (August 2012) . - pp 815 - 827 Titre : 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 Type de document : Article/Communication Auteurs : E. Heller, Auteur ; J. Rhemtulla, Auteur ; S. Lele, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 815 - 827 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte agricole [Termes IGN] classification dirigée [Termes IGN] cultures [Termes IGN] cultures irriguées [Termes IGN] image à moyenne résolution [Termes IGN] image IRS-LISS [Termes IGN] Inde [Termes IGN] Karnataka (Inde) [Termes IGN] ressources en eau [Termes IGN] rizière [Termes IGN] Saccharum officinarum Résumé : (Auteur) In regions of water scarcity, mapping individual crops, cropping intensities and irrigation can contribute significantly to understanding agricultural water use. But such mapping is challenging in landscapes dominated by small-scale traditional agricultural land holdings with high spatial and temporal heterogeneity. Here, we assessed the benefit of using multi-temporal 24 m resolution LISS-III imagery to characterize cropping systems in the Malaprabha basin of southern India. We used hierarchical stacked supervised classification to create three increasingly detailed maps showing: (a) single rainfed paddy rice versus continuously irrigated sugarcane, (b) irrigated versus rainfed areas, and (c) multiple cropping. Although increasing detail was accompanied by decreasing overall accuracies (89 percent, 74.6 percent and 60.1 percent respectively), using multi-temporal imagery out-performed single imagery alone in all cases. Results also led to higher estimates of total (69.8 percent) and irrigated (34.7 percent) cropland than previous single-imagery studies and census data, revealing the high uncertainty in crop estimates in this region. Numéro de notice : A2012-429 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.78.8.815 En ligne : https://doi.org/10.14358/PERS.78.8.815 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31875 [article]

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