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Exploring the Addition of Airborne Lidar-DEM and Derived TPI for Urban Land Cover and Land Use Classification and Mapping

Photogrammetric Engineering and Remote Sensing, ISSN: 0099-1112, Vol: 89, Issue: 1, Page: 19-26
2023
  • 3
    Citations
  • 0
    Usage
  • 14
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    3
  • Captures
    14
  • Mentions
    1
    • News Mentions
      1
      • News
        1

Most Recent News

Tennessee State University Researcher Broadens Understanding of Photogrammetric Engineering Remote Sensing (Exploring the Addition of Airborne Lidar-DEM and Derived TPI for Urban Land Cover and Land Use Classification and Mapping)

2023 JAN 13 (NewsRx) -- By a News Reporter-Staff News Editor at Engineering Daily News -- Fresh data on photogrammetric engineering remote sensing are presented

Article Description

The classification and mapping accuracy of urban land cover and land use has always been a critical topic and several auxiliary data have been used to improve the classification accuracy. However, to the best of our knowledge, there is limited knowledge of the addition of airborne Light Detection and Ranging (lidar)-Digital Elevation Model (DEM) and Topographic Position Index (TPI) for urban land cover and land use classification and mapping. The aim of this study was to explore the addition of airborne lidar-DEM and derived TPI to reflect data of Landsat Operational Land Imager (OLI) in improving the classification accuracy of urban land cover and land use mapping. Specifically, this study explored the mapping accuracies of urban land cover and land use classifications derived using: 1) standalone Landsat OLI satellite data; 2) Landsat OLI with acquired airborne lidar-DEM; 3) Landsat OLI with TPI; and 4) Landsat OLI with airborne lidar-DEM and derived TPI. The results showed that the addition of airborne lidar-DEM and TPI yielded the best overall urban land cover and land use classification accuracy of about 88%. The findings in this study demonstrated that both lidar-DEM and TPI had a positive impact in improving urban land cover and land use classification.

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