An approach to integrating the remotely sensed, geological, and geophysical data using the Dempster–Shafer mathematical theory

Popov, Mykhailo; Stankevich, Sergey; Topolnitsky, M.V.; Sedlerova, O.V.

doi:10.15407/dopovidi2015.04.094

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…Advantages of mentioned methods are objectivity, logic consistency, easy algorithmization, wide possibilities of re-analysis. In particular, we have already proposed and implemented several approaches to remote and geophysical data fusion, which are based on similar models (Popov et al, 2015;Popov et al, 2017). Data fusion and geospatial analysis can be put in practice as object-oriented middleware, augmented by rule-based inference expert system for smart city support.…”

Section: High-level Geospatial Analysis Based On Data Fusion For Smarmentioning

confidence: 99%

Remote Sensing Technologies and Geospatial Modelling Hierarchy for Smart City Support

Popov¹,

Fedorovsky²,

Stankevich³

et al. 2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The approach to implementing the remote sensing technologies and geospatial modelling for smart city support is presented. The hierarchical structure and basic components of the smart city information support subsystem are considered. Some of the already available useful practical developments are described. These include city land use planning, urban vegetation analysis, thermal condition forecasting, geohazard detection, flooding risk assessment. Remote sensing data fusion approach for comprehensive geospatial analysis is discussed. Long-term city development forecasting by Forrester -Graham system dynamics model is provided over Kiev urban area.

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Section: High-level Geospatial Analysis Based On Data Fusion For Smarmentioning

confidence: 99%

Remote Sensing Technologies and Geospatial Modelling Hierarchy for Smart City Support

Popov¹,

Fedorovsky²,

Stankevich³

et al. 2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Method for Oil and Gas Estimates of Exploration Sites via Geological, Parametric and Satellite Information

Popov,

Тopolnytskyi,

Titarenko

et al. 2022

VKNUGEOL

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The article is devoted to the search and exploration of hydrocarbons deposits, which is a crucial and complicated geological task and requires the large bulk of initial data and significant intellectual efforts of geologists. In this regard, the urgent problem is to ease the working conditions of experts and improve the accuracy of forecasting the oil and gas potential of subsoil areas through the use of novel digital methods of heterogeneous data integration and interpretation. The paper proposes a new method to form predictive estimates of the oil and gas content of subsoil areas via combining geological, ground-based parametric, and satellite information. As the mathematical basis of the method, the means of Dempster-Shafer's theory of evidence are used, which makes it possible to combine data from different sources, proceed with incomplete and inaccurate data, etc. Most of the procedures that make up the body of the method are presented in the form of algorithms, which simplifies its technologization. The final information product of the proposed method is a map with the distribution of probabilistic estimates of oil and gas prospects of subsoil areas within a given study area. The developed method is implemented in software and tested at the Vostochno-Rogintsovskoye oil field. The test results indicated its fairly high efficiency.

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An approach to integrating the remotely sensed, geological, and geophysical data using the Dempster–Shafer mathematical theory

Cited by 2 publications

References 3 publications

Remote Sensing Technologies and Geospatial Modelling Hierarchy for Smart City Support

Remote Sensing Technologies and Geospatial Modelling Hierarchy for Smart City Support

Method for Oil and Gas Estimates of Exploration Sites via Geological, Parametric and Satellite Information

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