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

Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

234
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...
234
Manipulation and Analysis01:21

Manipulation and Analysis

265
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...
265
Levels of Use of a GIS01:29

Levels of Use of a GIS

292
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...
292
Introduction to GIS01:28

Introduction to GIS

456
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...
456
Thematic Layering in GIS01:30

Thematic Layering in GIS

286
In the past, planning projects such as schools or public facilities required extensive manual effort to gather and compile data. Information such as property boundaries, soil characteristics, road networks, zoning regulations, and flood zones had to be sourced individually from courthouses, utility providers, and registry offices. Assembling these datasets into a coherent format often took several months, delaying project timelines.The introduction of Geographic Information Systems (GIS)...
286
Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

343
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...
343

You might also read

Related Articles

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

Sort by
Same author

A careful examination of large behavior models for multitask dexterous manipulation.

Science robotics·2026
Same author

Oxygen-15 Labeled Water Positron Emission Tomography During External Trigeminal Nerve Stimulation.

Neuromodulation : journal of the International Neuromodulation Society·2025
Same author

Dive-by-dive variation in the diving respiratory air volume of southern elephant seals (Mirounga leonina).

The Journal of experimental biology·2025
Same author

Expanding the binding space of argonaute-2: incorporation of either <i>E</i> or <i>Z</i> isomers of 6'-vinylphosphonate at the 5' end of the antisense strand improves RNAi activity.

Chemical communications (Cambridge, England)·2025
Same author

In vivo expansion of gene-targeted hepatocytes through transient inhibition of an essential gene.

Science translational medicine·2025
Same author

Further explorations into the complexities of femininity and masculinity.

The International journal of psycho-analysis·2025

Related Experiment Video

Updated: Jan 5, 2026

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

9.5K

Understanding an Urban Park through Big Data.

Jisoo Sim1, Patrick Miller2

  • 1Landscape Architecture Program, College of Architecture and Urban Studies, Virginia Tech, 800 Drillfield Dr., Blacksburg, VA 24060, USA. jisoosim@vt.edu.

International Journal of Environmental Research and Public Health
|October 30, 2019
PubMed
Summary
This summary is machine-generated.

Urban park planners can use big data analytics alongside traditional surveys to understand user preferences and park satisfaction. This combined approach offers valuable insights for park design and planning.

Keywords:
big dataonsite surveysentiment analysissocial media analyticsurban parkuser analysis

More Related Videos

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

14.0K
Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

398

Related Experiment Videos

Last Updated: Jan 5, 2026

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

9.5K
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

14.0K
Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

398

Area of Science:

  • Urban Planning
  • Data Science
  • Environmental Psychology

Background:

  • Understanding park user needs is crucial for effective urban park planning and design.
  • Big data presents a novel data source for informing these planning and design decisions.
  • However, the utility of big data analytics in this field is not yet widely accepted due to a lack of understanding.

Purpose of the Study:

  • To explore the application of big data analytics in urban park planning and design.
  • To identify user activity preferences and satisfaction levels within a park setting.
  • To compare the strengths and weaknesses of big data analytics against traditional survey methods.

Main Methods:

  • A mixed-methods approach was employed, combining onsite surveys with social media data analysis (Twitter).
  • Data was collected from Gyeongui Line Forest Park, an urban park developed on an abandoned railway.
  • Surveys gathered user activity preferences and satisfaction (n=177), while social media data provided qualitative insights (n=3703 tweets).

Main Results:

  • Survey data indicated that common activities like walking and resting were most preferred by park users.
  • Social media analytics revealed positive sentiment regarding the park's transformation from a railway and negative concerns about potential diseases.
  • The study highlights the complementary nature of traditional surveys and big data analytics.

Conclusions:

  • Big data analytics, particularly social media data, can offer unique insights into user perceptions and concerns in urban parks.
  • Combining big data with traditional methods like surveys provides a more comprehensive understanding for park planning and design.
  • This integrated approach can lead to more responsive and effective park development that meets user needs.