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Related Concept Videos

Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

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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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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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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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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)...
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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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Profile leveling and cross-sections are surveying methods used to determine and document terrain elevations for infrastructure projects such as highways, railroads, canals, and pipelines. These methods provide data for earthwork planning and alignment of proposed routes.  Profile leveling involves measuring elevations along a fixed line to create a vertical terrain profile. A surveyor sets up a leveling instrument at the benchmark (BM) and records a backsight (BS) to determine the...
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Trajectory Data Analyses for Pedestrian Space-time Activity Study
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Pedestrian-Accessible Infrastructure Inventory: Enabling and Assessing Zero-Shot Segmentation on Multi-Mode

Jiahao Xia1, Gavin Gong2, Jiawei Liu3

  • 1Department of Civil and Environmental Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.

Journal of Imaging
|March 27, 2024
PubMed
Summary

This study introduces a Segment Anything Model (SAM) workflow for segmenting pedestrian infrastructure from LiDAR and satellite data. The method efficiently creates accessible infrastructure inventories, benefiting city planners and individuals with disabilities.

Keywords:
computer visiondeep learninggeospatial datamulti-sourcedpedestrian infrastructurevisually impairedzero-shot method

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Area of Science:

  • Geospatial Science
  • Computer Vision
  • Urban Planning

Background:

  • Traditional pedestrian infrastructure inventories often omit accessibility-critical street furniture.
  • Mobile LiDAR and satellite imagery offer rich data for infrastructure mapping.
  • The Segment Anything Model (SAM) shows promise for zero-shot segmentation tasks.

Purpose of the Study:

  • To develop and optimize a SAM-based workflow for segmenting pedestrian infrastructure from multi-source geospatial data.
  • To investigate the use of mobile LiDAR and street-view imagery for comprehensive inventory creation.
  • To evaluate SAM's performance in segmenting diverse pedestrian infrastructure assets.

Main Methods:

  • Designed and optimized a Segment Anything Model (SAM) workflow for geospatial data.
  • Utilized mobile LiDAR point-cloud data to generate street-view images.
  • Integrated street-view images with satellite imagery for multi-modal input.
  • Employed zero-shot segmentation to identify pedestrian infrastructure and street furniture.

Main Results:

  • The SAM-based approach efficiently segments pedestrian infrastructure from combined LiDAR-derived street-view and satellite imagery.
  • Street-view images from mobile LiDAR, when paired with satellite data, facilitate effective zero-shot segmentation.
  • The method successfully expands the definition of pedestrian infrastructure to include accessibility features.

Conclusions:

  • The proposed workflow offers a scalable and efficient method for creating comprehensive pedestrian-accessible infrastructure inventories.
  • This approach provides immediate benefits for GIS professionals, city managers, and transportation planners.
  • The findings particularly support improved accessibility for individuals with travel-limiting disabilities.