Spatial data analysis and integration for regional-scale geothermal potential mapping, West Java, Indonesia

Carranza, Emmanuel John M.; Wibowo, Hendro; Barritt, S.D.; Sumintadireja, Prihadi

doi:10.1016/j.geothermics.2008.03.003

Cited by 82 publications

(25 citation statements)

References 50 publications

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“…Likewise, Fry analysis has only been used recently by to study landslide controls, but it has been employed extensively to deduce trends of structures controlling mineralization (e.g. Vearncombe and Vearncombe 1999;Carranza 2009Carranza , 2011Carranza et al 2009;Carranza and Sadeghi 2010) and geothermal fields (Carranza et al 2008b) as well as to infer post-mineralization deformation (Carranza and Sadeghi 2014). As shown by , distance distribution analysis and Fry analysis are complementary and supplementary methods that can be used in conjunction with one another to investigate certain controls on landsliding.…”

Section: Representation Of Fault Control On Susceptibility To Landslimentioning

confidence: 99%

Control of style-of-faulting on spatial pattern of earthquake-triggered landslides

Görüm

Carranza

2015

Int. J. Environ. Sci. Technol.

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Predictive mapping of susceptibility to earthquake-triggered landslides (ETLs) commonly uses distance to fault as spatial predictor, regardless of style-of-faulting. Here, we examined the hypothesis that the spatial pattern of ETLs is influenced by style-of-faulting based on distance distribution analysis and Fry analysis. The YingxiuBeichuan fault (YBF) in China and a huge number of landslides that ruptured and occurred, respectively, during the 2008 Wenchuan earthquake permitted this study because the style-of-faulting along the YBF varied from its southern to northern parts (i.e. mainly thrust-slip in the southern part, oblique-slip in the central part and mainly strike-slip in the northern part). On the YBF hanging-wall, ETLs at 4.4-4.7 and 10.3-11.5 km from the YBF are likely associated with strike-and thrust-slips, respectively. On the southern and central parts of the hanging-wall, ETLs at 7.5-8 km from the YBF are likely associated with obliqueslips. These findings indicate that the spatial pattern of ETLs is influenced by style-of-faulting. Based on knowledge about the style-of-faulting and by using evidential belief functions to create a predictor map based on proximity to faults, we obtained higher landslide prediction accuracy than by using unclassified faults. When distance from unclassified parts of the YBF is used as predictor, the prediction accuracy is 80 %; when distance from parts of the YBF, classified according to style-of-faulting, is used as predictor, the prediction accuracy is 93 %. Therefore, mapping and classification of faults and proper spatial representation of fault control on occurrence of ETLs are important in predictive mapping of susceptibility to ETLs.

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Section: Representation Of Fault Control On Susceptibility To Landslimentioning

confidence: 99%

Control of style-of-faulting on spatial pattern of earthquake-triggered landslides

Görüm

Carranza

2015

Int. J. Environ. Sci. Technol.

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“…Carranza et al (2008) focuses on the analysis of spatial distribution of geothermal prospects and thermal springs (evidences), and their spatial association with geological features (resources), highlighting their strong positive correlation. As a result, the mapping of high geothermal potential is presented.…”

Section: Data Integration For Targeting Promising Areas and Well Sitesmentioning

confidence: 99%

Methods and tools to evaluate the availability of renewable energy sources

Angelis-Dimakis

Biberacher

Bravo

et al. 2011

Renewable and Sustainable Energy Reviews

353

132

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The recent statements of both the European Union and the US Presidency pushed in the direction of using renewable forms of energy, in order to act against climate changes induced by the growing concentration of carbon dioxide in the atmosphere. In this paper, a survey regarding methods and tools presently available to determine potential and exploitable energy in the most important renewable sectors (i.e., solar, wind, wave, biomass and geothermal energy) is presented. Moreover, challenges for each renewable resource are highlighted as well as the available tools that can help in evaluating the use of a mix of different sources.

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“…Various MPM approaches are available which can be categorized into data-and knowledge-driven ones (Pan and Harris, 2000;Carranza, 2008). In data-driven techniques, the known mineral deposits are used as 'training points' to establish spatial relationships between the known deposits and particular geological, geochemical and geophysical features (Carranza et al, 2008a(Carranza et al, ,2008b. The relationships between evidential maps and the training points are quantified and used to establish the importance of each evidence map (Carranza and Hale, 2002a) and are finally integrated into a single MPM (Nykänen and Salmirinne, 2007).…”

Section: Introductionmentioning

confidence: 99%

Data Envelopment Analysis: A knowledge-driven method for mineral prospectivity mapping

Hosseini

Abedi

2015

Computers & Geosciences

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Spatial data analysis and integration for regional-scale geothermal potential mapping, West Java, Indonesia

Cited by 82 publications

References 50 publications

Control of style-of-faulting on spatial pattern of earthquake-triggered landslides

Control of style-of-faulting on spatial pattern of earthquake-triggered landslides

Methods and tools to evaluate the availability of renewable energy sources

Data Envelopment Analysis: A knowledge-driven method for mineral prospectivity mapping

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