Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Introduction to GIS01:28

Introduction to GIS

54
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...
54
Levels of Use of a GIS01:29

Levels of Use of a GIS

41
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...
41
Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

25
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...
25
GIS Software, Hardware, and Sources of GIS Data01:23

GIS Software, Hardware, and Sources of GIS Data

40
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...
40
Manipulation and Analysis01:21

Manipulation and Analysis

18
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
18
Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

36
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...
36

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Wayne Landis: Evolution of Ecological Risk Assessment.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same author

Reducing Risk Misinformation and Miscommunication: A Sheaf-Theoretic Perspective.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same author

Necessary conditions for valid causal inference from observational data.

Critical reviews in toxicology·2026
Same author

Integrating Fragmented Risk Knowledge: Sheaf Theory for Risk Analysts.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same author

Combining Diverse Expert Opinions in Risk Analysis Using Relative Causal Knowledge.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same author

Improving the design of epidemiology studies that use biomonitoring for exposure assessment: a SciPinion panel recommendation.

BMC medical research methodology·2026
Same journal

Trust-Building Communication for Extreme Heat Preparedness.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

Spring Broken: A Risk Analysis of Fatal and Nonfatal Traffic Injuries in Florida.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

Global Sensitivity Analysis of Societal Resilience Using Shapley Values and Polynomial Chaos Expansion.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

Assessing How Fact-Checks Influence Accuracy and Consensus Judgments: Evidence From the Olympics.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

Applying the Bow Tie Method to Evaluate Emerging Risk: The Case of Carbon Capture and Water Stress.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

Quantitative Microbial Risk Assessment of Human H5N1 Infection From Consumption of Fluid Cow's Milk.

Risk analysis : an official publication of the Society for Risk Analysis·2026
See all related articles

Related Experiment Video

Updated: May 3, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

13.4K

The use of public spatial databases in risk analysis: A US-oriented tutorial.

Michael R Greenberg1, Dona Schneider1, Louis Anthony Cox2

  • 1Edward J. Bloustein School of Planning and Public Policy Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USA.

Risk Analysis : an Official Publication of the Society for Risk Analysis
|January 18, 2025
PubMed
Summary
This summary is machine-generated.

This tutorial explores using US federal spatial databases for risk-informed policy. It highlights opportunities and challenges like data accuracy and spatial autocorrelation for hazard and risk assessment.

Keywords:
accuracydatabasesenvironmental justiceriskscale/shape

More Related Videos

Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

7.7K
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.3K

Related Experiment Videos

Last Updated: May 3, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

13.4K
Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

7.7K
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.3K

Area of Science:

  • Environmental Science
  • Geospatial Data Analysis
  • Public Policy Research

Background:

  • Six large, publicly accessible spatial databases from US federal agencies are available.
  • These databases integrate community, demographic, economic, social, and hazard data.
  • Spatial data offers opportunities for risk-informed policy and decision-making.

Purpose of the Study:

  • To review opportunities and challenges in utilizing recent US federal spatial databases.
  • To inform researchers and decision-makers on effective and cautious use of spatial data.
  • To identify limitations and propose improvements for spatial dataset application.

Main Methods:

  • Review of six major spatial databases from US federal agencies.
  • Analysis of data accuracy, cell variations, and spatial autocorrelation issues.
  • Examination of agency utilization, data limitations, and surrounding debates.

Main Results:

  • Spatial databases offer significant potential for risk assessment and policy.
  • Key challenges include data accuracy, spatial autocorrelation, and data cell variations.
  • Ignoring these limitations can lead to misleading research findings.

Conclusions:

  • Effective use of spatial databases requires acknowledging and addressing data limitations.
  • A checklist is provided to guide users in accessing and utilizing spatial datasets.
  • Cautious application of these resources can answer critical hazard and risk questions.