scholarly journals Machine learning and geographic information systems for large-scale wind energy potential estimation in rural areas

2019 ◽  
Vol 1343 ◽  
pp. 012036
Author(s):  
Dan Assouline ◽  
Nahid Mohajeri ◽  
Dasaraden Mauree ◽  
Jean-Louis Scartezzini
Keyword(s):  
Machine Learning ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Wind Energy ◽  
Rural Areas ◽  
Large Scale ◽  
Geographic Information ◽  
Energy Potential ◽  
Wind Energy Potential

scholarly journals Fully Automated Pose Estimation of Historical Images in the Context of 4D Geographic Information Systems Utilizing Machine Learning Methods

2021 ◽  
Vol 10 (11) ◽  
pp. 748
Author(s):  
Ferdinand Maiwald ◽  
Christoph Lehmann ◽  
Taras Lazariv
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Image Retrieval ◽  
Pose Estimation ◽  
Large Scale ◽  
Feature Matching ◽  
Geographic Information ◽  
Content Based Image Retrieval ◽  
Matching Methods ◽  
Historical Images

The idea of virtual time machines in digital environments like hand-held virtual reality or four-dimensional (4D) geographic information systems requires an accurate positioning and orientation of urban historical images. The browsing of large repositories to retrieve historical images and their subsequent precise pose estimation is still a manual and time-consuming process in the field of Cultural Heritage. This contribution presents an end-to-end pipeline from finding relevant images with utilization of content-based image retrieval to photogrammetric pose estimation of large historical terrestrial image datasets. Image retrieval as well as pose estimation are challenging tasks and are subjects of current research. Thereby, research has a strong focus on contemporary images but the methods are not considered for a use on historical image material. The first part of the pipeline comprises the precise selection of many relevant historical images based on a few example images (so called query images) by using content-based image retrieval. Therefore, two different retrieval approaches based on convolutional neural networks (CNN) are tested, evaluated, and compared with conventional metadata search in repositories. Results show that image retrieval approaches outperform the metadata search and are a valuable strategy for finding images of interest. The second part of the pipeline uses techniques of photogrammetry to derive the camera position and orientation of the historical images identified by the image retrieval. Multiple feature matching methods are used on four different datasets, the scene is reconstructed in the Structure-from-Motion software COLMAP, and all experiments are evaluated on a newly generated historical benchmark dataset. A large number of oriented images, as well as low error measures for most of the datasets, show that the workflow can be successfully applied. Finally, the combination of a CNN-based image retrieval and the feature matching methods SuperGlue and DISK show very promising results to realize a fully automated workflow. Such an automated workflow of selection and pose estimation of historical terrestrial images enables the creation of large-scale 4D models.

scholarly journals Challenges of Testing COVID-19 Cases in Bangladesh

2020 ◽  
Vol 17 (18) ◽  
pp. 6439 ◽  
Author(s):  
Khan Rubayet Rahaman ◽  
Md. Sultan Mahmud ◽  
Bishawjit Mallick
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Rural Areas ◽  
Local Level ◽  
Geographic Information ◽  
Dynamic Nature ◽  
To Receive ◽  
Testing Range

Keeping the dynamic nature of Coronaviruses (COVID-19) pandemic in mind, we have opted to explore the importance of the decentralization of COVID-19 testing centers across the country of Bangladesh in order to combat the pandemic. In doing so, we considered quantitative, qualitative, and geographic information systems (GIS) datasets to identify the location of existing COVID-19 testing centers. Moreover, we attempted to collect data from the existing centers in order to demonstrate testing times at the divisional level of the country. Results show that the number of testing centers is not enough to cater to the vast population of the country. Additionally, we found that the number of days it takes to receive the results from the COVID-19 testing centers is not optimal at divisional cities, let alone the remote rural areas. Finally, we propose a set of recommendations in order to enhance the existing system to assist more people under a testing range of COVID-19 viruses at the local level.

The impact of atmospheric circulation on wind energy resource using self-organizing maps

2021 ◽  
Author(s):  
Kostas Philippopoulos ◽  
Chris G. Tzanis
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Synoptic Climatology ◽  
Energy Potential ◽  
Self Organizing Maps ◽  
Wind Energy Potential ◽  
The Impact ◽  
Self Organizing

<p>The sensitivity of wind to the Earth’s energy budget and the changes it causes in the climate system has a significant impact on the wind energy sector. The scope of this work is to examine the association of atmospheric circulation with the wind speed distribution characteristics on different timescales over Greece. Emphasis is given to the effect of specific regimes on the wind speed distributions at different locations. The work is based on using synoptic climatology as a tool for providing information regarding wind variability. This approach allows a more detailed description of the effect of changes in large-scale atmospheric circulation on wind energy potential. The atmospheric classification methodology, upon the selection of relevant atmospheric variables and domains, includes a Principal Components Analysis for dimension reduction purposes and subsequently, the classification is performed using an artificial neural network and in particular self-organizing maps. In the resulting feature map, the neighboring nodes are inter-connected and each one is associated with the composites of the selected large-scale variables. Upon the assignment and the characterization of each day in one of the resulting patterns, a daily catalog is constructed and frequency analysis is performed. In the context of estimating wind energy potential variability for each atmospheric pattern, the fit of multiple probability functions to the surface wind speed frequency distributions is performed. The most suitable function is selected based on a set of difference and correlation statistical measures, along with the use of goodness-of-fit statistical tests. The study employs the ERA5 reanalysis dataset with a 0.25° spatial resolution from 1979/01/01 up to 2019/12/31 and the wind field data are extracted at the 10m and the 100m levels. The approach could be valuable to the wind energy industry and can provide the required scientific understanding for the optimal siting of Wind Energy Conversion Systems considering the atmospheric circulation and the electricity interconnection infrastructure in the region. Considering the emerging issue of energy safety, accurate wind energy production estimates can contribute towards the establishment of wind as the primary energy source and in meeting the increasing energy demand.</p>

Geographic Information Systems for Tracking Bridge Component Inspection and Repairs

1997 ◽  
Vol 1575 (1) ◽  
pp. 60-65
Author(s):  
Raymond D. Thierrin
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Computer Aided Design ◽  
Large Scale ◽  
Geographic Information ◽  
Digital Information ◽  
Bridge Rehabilitation ◽  
Digital Format ◽  
Management Procedures ◽  
Available Technology

Bridge component inspection and repair information has been traditionally collected on paper forms by field personnel and stored in project files. Because of the industrywide use of computer-aided design and drafting technology in bridge rehabilitation design, digital information for bridge components is often available as a by-product of the design process. In addition, projects are becoming more sophisticated and, as a result, the construction field office is becoming more automated. It is now possible to automate field data collection and management procedures so that information can be captured in a digital format in the field and used throughout the construction documentation process. The available technology includes pen-based computers, pen-enabled database software, and digital color cameras, all of which can be integrated into systems that are easily used by field inspection personnel. By using databases and geographic information systems, inspectors and engineers can readily review component information and track the progress of repairs for large-scale rehabilitation projects.

Developing geographic information systems platforms for multijurisdictional transportation analyses: framework and techniques for spatial data sharing

2003 ◽  
Vol 30 (5) ◽  
pp. 807-818 ◽  
Author(s):  
Kai Han ◽  
Scott Minty ◽  
Alan Clayton
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Data Sharing ◽  
Spatial Data ◽  
Rural Areas ◽  
Geographic Information ◽  
Data Sets ◽  
Data Interoperability ◽  
Urban And Rural Areas ◽  
Integration Data

Geographic information systems (GISs) have been presented as a powerful analysing tool for civil engineers to help their decision-making processes. Building GIS platforms for transportation analysis involving multiple jurisdictions has been challenging, however, because of the complexity and difficulty associated with conducting data sharing and ensuring spatial data interoperability among GISs for transportation (GIS-T) data sets. In the context of western Canadian urban and rural areas, this paper investigates the issues related to GIS-T data sharing, establishes a conceptual framework, develops techniques supporting the framework by solving recurring data-sharing problems, and constructs a number of GIS-T platforms facilitating comprehensive multijurisdictional transportation analyses. In addition, based on the knowledge gained through solving real-world problems, the authors propose an open GIS-T platform consisting of a series of customized base maps, each being tailored to suit the needs of individual application and, as a whole, linked together by interoperability to better support transportation applications.Key words: transportation engineering analysis, GIS, GIS-T, spatial data, interoperability, integration, data sharing.

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