Spoofing in Geography: Can We Trust Artificial Intelligence to Manage Geospatial Data?

2020 ◽  
pp. 325-338
Author(s):  
Bo Zhao ◽  
Shaozeng Zhang ◽  
Chunxu Xu ◽  
Xiaobai Liu
Keyword(s):  
Artificial Intelligence ◽  
Geospatial Data

scholarly journals Geospatial data and artificial intelligence technologies as innovative communication tools for quality education and lifelong learning

2020 ◽  
Vol 7 (1-2) ◽  
pp. 50-71
Author(s):  
Chidinma Henrietta Onwubere
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
Lifelong Learning ◽  
Current Trend ◽  
Learning Curves ◽  
Geospatial Data ◽  
Quality Education ◽  
Fake News ◽  
Communication Education ◽  
Time Space

The uniqueness of open and distance learning (ODL) lies in its wide reach to a large audience simultaneously in different locations. No better system than geospatial data and artificial intelligence technologies (GDAITs) can achieve this. Globally, the current trend is to use GDAITs to improve the quality of life and productivity. Education is important for any country’s economy as it enhances the overall life expectancy. Application of GDAITs in educational sector, through broadcast digitization, publishing technologies will record greater achievements in the standard of learning and the literacy of populations. At certain ages in life, people develop apathy towards learning, thus, they are cut off from additional education that could provide them with lifelong learning. With GDAITs, they can be reached with quality education anywhere. Students have constraints of time, space, and finance, for acquisition of study materials. GDAITs are able to create and deploy seamless applications which can collapse these constraints and improve the learning curves of learners. This study investigates the exposure of youths to GDAITs and the influence on their learning patterns. Gerbner’s cultivation theory serves as the theoretical framework. A survey of 200 undergraduate Nigerian students was conducted, using random sampling technique. Findings show that Nigerian youths are highly exposed to GDAITs. THw paper concludes that GDAITs contribute positively and negatively to development in diverse human activities. However, it is highly effective in fostering communication education and research in Nigeria. It recommended that information and communication technology should be taught at all levels of education, so that Nigerians can develop critical minds to distinguish what GDAITs can and cannot do. Media houses should continue to establish platforms to check fake news emanating from social media. Also, attention needs to be focused on media content to ensure that there are enough programmes that would enhance communication education in Nigeria, without fake news parasitism. Keywords: GDAITs, Communication education, Learning processes, Social media, Digitization

Deep fake geography? When geospatial data encounter Artificial Intelligence

2021 ◽  
pp. 1-15
Author(s):  
Bo Zhao ◽  
Shaozeng Zhang ◽  
Chunxue Xu ◽  
Yifan Sun ◽  
Chengbin Deng
Keyword(s):  
Artificial Intelligence ◽  
Geospatial Data

scholarly journals PROSPECTS FOR USING GEOINFORMATION TECHNOLOGIES IN UKRAIN AIRPORTS FOR ADMINISTRATIVE AND ECONOMIC MANAGEMENT

2020 ◽  
pp. 247-257
Author(s):  
Olena Boiko ◽  
Keyword(s):  
Artificial Intelligence ◽  
Information Technologies ◽  
Mixed Reality ◽  
Smart Cities ◽  
Geographic Information ◽  
Geospatial Data ◽  
Economic Management ◽  
Geographic Information Technologies ◽  
Cloud Technologies ◽  
The Internet Of Things

The urgency of the research. In recent years, world's airports are actively implementing cloud technologies for collecting, processing and visualizing geospatial data: laser and lidar scanning, integration of BIM / GIS models, the use of artificial intelligence, virtual and augmented reality technologies, digital duplicates and «smart» cities. For Ukraine, which is actively following the path of digitalization and implementation of modern geographic information technologies in many areas of ac-tivity, the development of new methods and approaches for administrative and economic management of airport complexes is a relevant and promising area. Target settings.This study examines the possibilities of modern geographic information and cloud technologies and pro-spects for their use for administrative and economic management of an airport. The study is related to the implementation of the State Target Program for Airport Development until 2023 and the Aviation Transport Strategy of Ukraine until 2030, which aims to develop the aviation industry in Ukraine, bringing airport infrastructure to the requirements of the European Union. The Law of Ukraine «On the National Infrastructure of Geospatial Data» and «Consolidated Concept of VIM Implementation in Ukraine» has a great influence on the formation of geospatial data of airports.Actual scientific researches and issues analysis. The paper analyzes and summarizes publications on methods of obtain-ing geospatial data, implementation of geographic information technologies, virtual, augmented and mixed reality technolo-gies, artificial intelligence and the concept of «smart» city for administrative and economic management of airports.Uninvestigated parts of general matters defining. Analysis of recent research and publications has shown that the pro-spects for the introduction of geographic information technology for administrative and economic asset management of Ukrain-ian airports need further research, as these issues are very important and relevant, given the rapid growth of digital society, environment and infrastructure.The research objective. The purpose of this study is to analyze the possibilities and prospects for the introduction of modern technologies for processing and visualization of geospatial data for administrative and economic management of the airport and the development of a conceptual model. The task of the research is to analyze the methods of obtaining geospatial data of the airport, the use of geographic information systems in airports, artificial intelligence technologies, virtual, aug-mented and mixed reality, the Internet of Things, digital duplicates, implementation of the concept of «smart» city, etc.The statement of basic materials. Geospatial data is created digitally using modern information and cloud technologies that offer a wide range of equipment, software, methods and technologies for working with geospatial information. Every year, new technologies that are used in the administrative and economic management of airports appear: cloud data acquisition methods, geographic information systems, artificial intelligence technologies, virtual reality, the Internet of Things, digital counterparts, «smart» cities, and more. Successful integration and use of existing capabilities for the collection, storage, pro-cessing and visualization of geospatial data of airports will ensure their effective management and economic growth.Conclusions. Based on the analysis of the possibilities of using virtual, augmented and mixed reality technologies, artifi-cial intelligence, digital duplicates and the concept of «smart» cities in airports,a conceptual model of prospects for using geospatial data of the airport to address administrative and economic management of the property complex was developed.

scholarly journals Artificial Intelligence

2019 ◽  
pp. 357-385
Author(s):  
Eric Guérin ◽  
Orhun Aydin ◽  
Ali Mahdavi-Amiri
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Virtual Reality ◽  
Data Analysis ◽  
Generative Models ◽  
Geospatial Data ◽  
Great Promise ◽  
Data Sets ◽  
Digital Earth ◽  
Data Analysis Methods

Abstract In this chapter, we provide an overview of different artificial intelligence (AI) and machine learning (ML) techniques and discuss how these techniques have been employed in managing geospatial data sets as they pertain to Digital Earth. We introduce statistical ML methods that are frequently used in spatial problems and their applications. We discuss generative models, one of the hottest topics in ML, to illustrate the possibility of generating new data sets that can be used to train data analysis methods or to create new possibilities for Digital Earth such as virtual reality or augmented reality. We finish the chapter with a discussion of deep learning methods that have high predictive power and have shown great promise in data analysis of geospatial data sets provided by Digital Earth.

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