Harnessing earth observation (EO) capabilities in hydrogeology: an Indian perspective

Bandyopadhyay, Samir Kumar; Srivastava, Shuchita; Jha, Madan K.; Hegde, V. S.; Jayaraman, V.

doi:10.1007/s10040-006-0122-4

Cited by 24 publications

(2 citation statements)

References 10 publications

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“…The satellite was mainly designed for terrain modeling and large-scale mapping [ 3 , 10 - 16 ]. Nevertheless, in previous studies Cartosat-1 data have been also used in different fields, such as natural hazards assessment [ 4 , 5 ], archaeological exploration [ 6 ], estimation of hydrological parameters [ 7 , 8 ] or estimation of atmospheric aerosols [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Cartosat-1 Multi-Scale Digital Surface Modelling Over France

Gianinetto

2009

Sensors

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On 5 May 2005, the Indian Space Research Organization launched Cartosat-1, the eleventh satellite of its constellation, dedicated to the stereo viewing of the Earth's surface for terrain modeling and large-scale mapping, from the Satish Dhawan Space Centre (India). In early 2006, the Indian Space Research Organization started the Cartosat-1 Scientific Assessment Programme, jointly established with the International Society for Photogrammetry and Remote Sensing. Within this framework, this study evaluated the capabilities of digital surface modeling from Cartosat-1 stereo data for the French test sites of Mausanne les Alpilles and Salon de Provence. The investigation pointed out that for hilly territories it is possible to produce high-resolution digital surface models with a root mean square error less than 7.1 m and a linear error at 90% confidence level less than 9.5 m. The accuracy of the generated digital surface models also fulfilled the requirements of the French Reference 3D®, so Cartosat-1 data may be used to produce or update such kinds of products.

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Section: Introductionmentioning

confidence: 99%

Evaluation of Cartosat-1 Multi-Scale Digital Surface Modelling Over France

Gianinetto

2009

Sensors

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“…There are various statistical methods that were adopted by various authors for groundwater potential mapping elsewhere such as: frequency ratio (Guru et al 2017;Al-Zuhairy et al 2017;Razandi et al 2015), Analytical hierarchical process Chowdhury et al 2009;Razandi et al 2015), binary logistic regression method (Ozdemir 2011a), weight of evidence model (Ghorbani et al 2017;Tahmassebipoor et al 2016;Ozdemir 2011b), k-nearest neighbor (Naghibi and Dashtpagerdi 2017), Demster-Shafer model , machine learning model/artificial neural network (Lee et al 2012), boosted regression tree BRT (Naghibi and Pourghasemi 2015;Naghibi et al 2016), multivariate adaptive regression spline (Zabihi et al 2016), maximum, entropy model ), generalized adaptive model (Falah et al 2016), random forest model (Rahmati et al 2018), and other GIS-based models such as earth observation and entropy weighted linear aggregate novel approach (Bandyopadhyay et al 2007;Al-Abadi et al 2016). In the above studies, themes such as vegetation, land use/land cover, hydrogeomorphology, drainage, lithology, subsurface lithology, structure, and slope were interpreted to infer groundwater potential.…”

Section: Introductionmentioning

confidence: 99%

GIS-based model of groundwater occurrence using geological and hydrogeological data in Precambrian Oban Massif southeastern Nigeria

Sikakwe¹

2018

Appl Water Sci

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This researchmodeled geological and hydrogeological controls on groundwater occurrence in Oban Massif and environs southeastern Nigeria. Topographical, hydrogeological, and structural maps, including lithology samples from drilled bores, well completion, and pumping test data in the study area were procured. Collection of coordinates of rock sample locations and structural data on strike and dip of rock exposures was collected. Geological and structural information collected was overlaid on the topographical, hydrogeological and structural map and digitized to produce the geological map of the study area. Thematic map on geological groundwater prospect map of the study was prepared using multicriteria evaluation. Relative weights were assigned to various rock types based on their relative contribution to groundwater occurrence and the map was reclassified using geographic information system (ArcGIS10.1) analysis. Depth ranges of the various lithologic units from drilled boreholes were used to construct lithologic correlation section of the boreholes across the study area using RockWorks16 Program software. Hydrogeological parameters such as storativity, specific capacity, transmissivity, drawdown, pumping rate, static water level, total depth, and well yield were computed from well completion reports and aquifer test. Results shows that the geologic groundwater prospect map was categorized into very good (28. Aquifer test parameters obtained from boreholes across the study indicate better correspondence with zones identified as good water prospect in the study. It was evident that well yield is not a very reliable aquifer performance indicator, because it depends largely on the efficiency of the pump installed. Therefore, other aquifer parameters must be employed in aquifer performance assessment. The geologic formation is paramount in determining aquifer performance. The result of this groundwater occurrence is useful as a guide for groundwater developers, which engineers in water resource management and land-use planners to select suitable areas to implement development schemes and also government agencies.

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Potential of Geospatial Technologies for Mitigating Land and Water Related Disasters

Bandyopadhyay

Jha

2010

Natural and Anthropogenic Disasters

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Harnessing earth observation (EO) capabilities in hydrogeology: an Indian perspective

Cited by 24 publications

References 10 publications

Evaluation of Cartosat-1 Multi-Scale Digital Surface Modelling Over France

Evaluation of Cartosat-1 Multi-Scale Digital Surface Modelling Over France

GIS-based model of groundwater occurrence using geological and hydrogeological data in Precambrian Oban Massif southeastern Nigeria

Potential of Geospatial Technologies for Mitigating Land and Water Related Disasters

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