Spatial data-sets for geographical referencing

2002 ◽  
Keyword(s):  
Spatial Data ◽  
Data Sets ◽  
Spatial Data Sets

scholarly journals An ABC-optimized fuzzy ELECTRE approach for assessing petroleum potential at the petroleum system level

2020 ◽  
Vol 12 (1) ◽  
pp. 580-597
Author(s):  
Mohamad Hamzeh ◽  
Farid Karimipour
Keyword(s):  
Spatial Data ◽  
Spatial Models ◽  
Model Performance ◽  
Essential Elements ◽  
Petroleum System ◽  
Petroleum Exploration ◽  
System Level ◽  
Data Sets ◽  
Petroleum Potential ◽  
Spatial Data Sets

AbstractAn inevitable aspect of modern petroleum exploration is the simultaneous consideration of large, complex, and disparate spatial data sets. In this context, the present article proposes the optimized fuzzy ELECTRE (OFE) approach based on combining the artificial bee colony (ABC) optimization algorithm, fuzzy logic, and an outranking method to assess petroleum potential at the petroleum system level in a spatial framework using experts’ knowledge and the information available in the discovered petroleum accumulations simultaneously. It uses the characteristics of the essential elements of a petroleum system as key criteria. To demonstrate the approach, a case study was conducted on the Red River petroleum system of the Williston Basin. Having completed the assorted preprocessing steps, eight spatial data sets associated with the criteria were integrated using the OFE to produce a map that makes it possible to delineate the areas with the highest petroleum potential and the lowest risk for further exploratory investigations. The success and prediction rate curves were used to measure the performance of the model. Both success and prediction accuracies lie in the range of 80–90%, indicating an excellent model performance. Considering the five-class petroleum potential, the proposed approach outperforms the spatial models used in the previous studies. In addition, comparing the results of the FE and OFE indicated that the optimization of the weights by the ABC algorithm has improved accuracy by approximately 15%, namely, a relatively higher success rate and lower risk in petroleum exploration.

scholarly journals Mining Co-Location Patterns with Rare Events from Spatial Data Sets

2006 ◽  
Vol 10 (3) ◽  
pp. 239-260 ◽  
Author(s):  
Yan Huang ◽  
Jian Pei ◽  
Hui Xiong
Keyword(s):  
Spatial Data ◽  
Rare Events ◽  
Data Sets ◽  
Location Patterns ◽  
Spatial Data Sets

scholarly journals Refinement Algoritm of Hypotheses Testing Research Based on Geochronological Tracking

2020 ◽  
Vol 6 (1) ◽  
pp. 86-93
Author(s):  
R. Ivakin ◽  
Y. Ivakin ◽  
S. Potapichev
Keyword(s):  
Spatial Data ◽  
Optimization Problem ◽  
Retrospective Studies ◽  
Subject Area ◽  
Statistical Testing ◽  
Time Interval ◽  
Data Sets ◽  
Hypotheses Testing ◽  
Practical Application ◽  
Spatial Data Sets

Geochronological tracking is an effective information technology for digital cartographic spatial data sets processing. It is widely known in retrospective patterns research about geographic relocation of figures, or any other units for a given time interval. Software component of geochronological tracking is becoming one the most popular GIS-integrated applications. The article presents the basic provisions for the algorithmization of the geochronological tracking procedure for statistical testing of retrospective studies hypotheses. We can observe the results of solving this optimization problem in a general form and in a number of the most typical variants. The obtained results of solving the optimization problem are interpreted in terms of the retrospective studies subject area. There are shown the ways of further practical application of the optimized algorithm in the tasks of modern logistics, data mining and formalized knowledge.

Understanding Accessibility

2016 ◽  
pp. 223-257
Author(s):  
Kivanc Ertugay ◽  
Sebnem H. Duzgun
Keyword(s):  
Spatial Data ◽  
Catchment Area ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Data Sets ◽  
Location Allocation ◽  
Modeling Process ◽  
Key Variables ◽  
Spatial Data Sets ◽  
Significant Support

Accessibility measures are generally concerned with equity and a better distribution of services in a territory and can be accepted as key variables for supporting supply/demand, location/allocation and service/catchment area related planning policies and strategies at national, regional, and local levels. Since accessibility measures need organization of huge and complex spatial data sets, accessibility modeling often lends itself to Geographical Information Systems (GIS) for analysis and presentation. Since numerous accessibility measures and modeling techniques ranging from simple to sophisticated can be found in the literature, this work aim to provide an overview of the theoretical framework and relevant background about GIS-based accessibility modeling process. The results could provide a significant support for the decision makers who are supposed to deal with transportation planning, accessibility modeling, location/allocation and service/catchment area related issues.

Understanding Accessibility

2018 ◽  
pp. 576-608
Author(s):  
Kivanc Ertugay ◽  
Sebnem H. Duzgun
Keyword(s):  
Spatial Data ◽  
Catchment Area ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Data Sets ◽  
Location Allocation ◽  
Modeling Process ◽  
Key Variables ◽  
Spatial Data Sets ◽  
Significant Support

Accessibility measures are generally concerned with equity and a better distribution of services in a territory and can be accepted as key variables for supporting supply/demand, location/allocation and service/catchment area related planning policies and strategies at national, regional, and local levels. Since accessibility measures need organization of huge and complex spatial data sets, accessibility modeling often lends itself to Geographical Information Systems (GIS) for analysis and presentation. Since numerous accessibility measures and modeling techniques ranging from simple to sophisticated can be found in the literature, this work aim to provide an overview of the theoretical framework and relevant background about GIS-based accessibility modeling process. The results could provide a significant support for the decision makers who are supposed to deal with transportation planning, accessibility modeling, location/allocation and service/catchment area related issues.

From CAD to GIS to the Geoweb: A Natural Evolution

2010 ◽  
Author(s):  
Steve Adam
Keyword(s):  
Decision Making ◽  
Spatial Data ◽  
Oil And Gas ◽  
Spatial Information ◽  
Digital Data ◽  
Computer Hardware ◽  
Disruptive Technology ◽  
Data Sets ◽  
Spatial Data Sets ◽  
Pipeline Design

Computer hardware and software have played a significant role in supporting the design and maintenance of pipeline systems. CAD systems allowed designers and drafters to compile drawings and make edits at a pace unmatched by manual pen drawings. Although CAD continues to provide the environment for a lot of pipeline design, Geographic Information Systems (GIS) are also innovating pipeline design through routines such as automated alignment sheet generation. What we have seen over the past two or three decades is an evolution in how we manage the data and information required for decision making in pipeline design and system operation. CAD provided designers and engineers a rapid electronic method for capturing information in a drawing, editing it, and sharing it. As the amount of digital data available to users grows rapidly, CAD has been unable to adequately exploit data’s abundance and managing change in a CAD environment is cumbersome. GIS and spatial data management have proven to be the next evolution in situations where engineering, integrity, environmental, and other spatial data sets dominate the information required for design and operational decision making. It is conceivable that GIS too will crumble under the weight of its own data usage as centralized databases become larger and larger. The Geoweb is likely to emerge as the geospatial world’s evolution. The Geoweb implies the merging of spatial information with the abstract information that currently dominates the Internet. This paper and presentation will discuss this fascinating innovation, it’s force as a disruptive technology, and oil and gas applications.

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