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Related Concept Videos

Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

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The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
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Design Example: Measuring Distance Between Two Points with Obstructions01:10

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When measuring distances in areas with physical obstructions, such as a lake in a field, surveyors must employ techniques to calculate accurate lengths without direct line measurements. One effective method is the offset technique, which allows for precise distance estimation over inaccessible stretches.In this scenario, a surveyor must measure a side of an area that crosses a lake. Since the measuring tape cannot span the lake, the surveyor begins by establishing a baseline that aligns with...
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Levels of Use of a GIS01:29

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

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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...
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Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
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Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function
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Vector-based pedestrian navigation in cities.

Christian Bongiorno1,2, Yulun Zhou1,3, Marta Kryven4

  • 1Senseable City Lab, Massachusetts Institute of Technology, Cambridge, MA, USA.

Nature Computational Science
|January 13, 2024
PubMed
Summary
This summary is machine-generated.

Pedestrians deviate from shortest routes as distances grow, with path direction significantly influencing choices. A new vector-based navigation model better predicts human path planning in urban environments.

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Area of Science:

  • Urban planning
  • Human mobility
  • Computational social science

Background:

  • Understanding pedestrian navigation in urban environments is crucial for city planning and transportation.
  • Previous research relied on controlled experiments, lacking real-world mobility data insights.

Purpose of the Study:

  • To analyze human path planning in city street networks using real-world GPS data.
  • To identify key factors influencing pedestrian route selection beyond shortest distance.

Main Methods:

  • Statistical analysis of a large dataset of GPS traces from two major US cities.
  • Development and testing of a novel vector-based navigation model ('pointiest paths').

Main Results:

  • Pedestrians increasingly deviate from the shortest path as origin-destination distance increases.
  • Path choices differ significantly when origin and destination are reversed.
  • The 'pointiest paths' model statistically outperforms shortest-path models with stochastic effects.

Conclusions:

  • Direction to the goal is a primary driver in human path planning.
  • Vector-based navigation appears to be a universal property of human path planning across different urban networks.