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Levels of Use of a GIS01:29

Levels of Use of a GIS

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Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
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Selected Data About Geographic Locations01:25

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Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
93
GIS Software, Hardware, and Sources of GIS Data01:23

GIS Software, Hardware, and Sources of GIS Data

273
A Geographic Information System (GIS) combines specialized software and hardware to effectively manage, analyze, and present spatial and related data. GIS software includes critical functionalities such as a user interface for easy navigation, database management tools for handling spatial and attribute data, and data retrieval features for efficient access. Analytical tools transform raw data into insights, while display functions produce maps and reports in various formats for effective...
273
Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

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193
Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
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Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

205
Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
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Introduction to GIS01:28

Introduction to GIS

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Geographic Information Systems (GIS) are tools for storing, analyzing, and displaying spatial data alongside related attributes. Unlike traditional information systems that address general queries, GIS incorporates spatial components, enabling users to answer "where" and "how far." For example, GIS can process housing data linked to geographic locations like zip codes, allowing insights into population density or housing distribution through thematic maps.GIS integrates technologies such as...
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Assessing internet and web services based webdom and virtual web-data-centric geographical study.

Abhay Sankar Sahu1

  • 1Department of Geography, University of Kalyani, Kalyani, Nadia, West Bengal 741235 India.

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Summary

Traditional geography is shifting to virtual, web-data-centric approaches using big data and machine learning for spatio-temporal analysis. This study assesses the scope of this evolving field, integrating geographical big data, machine learning, and WebGIS.

Keywords:
Artificial IntelligenceGeographical BigdataGeographical Machine LearningGeographical StudyWebGISWebdom

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Area of Science:

  • Geography
  • Geoinformatics
  • Data Science

Background:

  • The field of geography has evolved from traditional methods to a virtual, web-data-centric paradigm, particularly over the last three decades.
  • This shift is driven by advancements in remote sensing, digitization, data storage, and artificial intelligence (AI), leading to the generation of geographical big data.
  • The proliferation of internet services, increased internet users, and GPS-enabled smartphones have accelerated the creation and accessibility of vast amounts of geographical data.

Purpose of the Study:

  • To assess the current landscape and understand the scope of contemporary virtual web-data-centric geographical studies.
  • To explore the integration of geographical big data, machine learning, and WebGIS in modern geographical research.
  • To examine the potential and challenges of utilizing big data for geographical analysis in the age of the 'webdom'.

Main Methods:

  • Analysis of geographical big data characterized by geospatial attributes.
  • Application of machine learning algorithms for spatio-temporal analysis, prediction, and thematic mapping.
  • Utilization of WebGIS (Web Geographic Information System) for data visualization and analysis.

Main Results:

  • Geographical big data, geographical machine learning, and WebGIS are identified as the three core components of virtual web-data-centric geographical study.
  • AI and machine learning are increasingly employed in geography for phenomenon prediction, mirroring trends in other scientific disciplines.
  • The accessibility of online geographical data is unprecedented, enabling analysis from anywhere at any time.

Conclusions:

  • Virtual web-data-centric geography leverages big data and machine learning for advanced spatio-temporal analysis and prediction.
  • The integration of AI and WebGIS is transforming geographical research and applications.
  • Challenges remain regarding data reliability and the necessity of traditional field verification for web-sourced geographical data.