LIDAR data filtering and DTM interpolation within GRASS

被引:4
|
作者
Brovelli, Maria A. [1 ]
Longoni, Ulisse M. [1 ]
Cannata, Massimiliano [1 ]
机构
[1] Politecnico di Milano-Campus Como, Como, Via Valleggio 11-22100, Italy
关键词
Global positioning system - Optical radar;
D O I
10.1111/j.1467-9671.2004.00173.x
中图分类号
学科分类号
摘要
LIDAR (Light Detection and Ranging) is one of the most recent technologies in surveying and mapping. LIDAR is based on the combination of three different data collection tools: A laser scanner mounted on an aircraft, a Global Positioning System (GPS) used in phase differential kinematic modality to provide the sensor position and an Inertial Navigation System (INS) to provide the orientation. The laser sends towards the ground an infrared signal, which is reflected back to the sensor. The time employed by the signal, given the aircraft position and attitude, allows computation of the earth point elevation. In standard conditions, taking into account the flight (speed 200-250 km/hour, altitude 500-2,000 m) and sensor characteristics (scan angle ± 10-20 degrees, emission rate 2,000-50,000 pulses per second), earth elevations are collected within a density of one point every 0.5-3 m. The technology allows us therefore to obtain very accurate (5-20 cm) and high resolution Digital Surface Models (DSM). For many applications, the Digital Terrain Model (DTM) is needed: we have to automatically detect and discard from the previous DSM all the features (buildings, trees, etc.) present on the terrain. This paper describes a procedure that has been implemented within GRASS to construct DTMs from LIDAR source data. © Blackwell Publishing Ltd. 2004.
引用
收藏
页码:155 / 174
相关论文
共 50 条
  • [1] LiDAR Data Filtering and DTM Generation Using Empirical Mode Decomposition
    Ozcan, Abdullah H.
    Unsalan, Cem
    [J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2017, 10 (01) : 360 - 371
  • [2] Investigating performance of Airborne LiDAR data filtering algorithms for DTM generation
    Polat, Nizar
    Uysal, Murat
    [J]. MEASUREMENT, 2015, 63 : 61 - 68
  • [3] Parameter-free ground filtering of LiDAR data for automatic DTM generation
    Mongus, Domen
    Zalik, Borut
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2012, 67 : 1 - 12
  • [4] Application of Intelligent Interpolation Methods for DTM Generation of Forest Areas Based on LiDAR Data
    Masoomeh Gomroki
    Marzieh Jafari
    Saeed Sadeghian
    Zahra Azizi
    [J]. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 2017, 85 : 227 - 241
  • [5] Comparison of various algorithms for DTM interpolation from LIDAR data in dense mountain forests
    Sterenczak, Krzysztof
    Ciesielski, Mariusz
    Balazy, Radomir
    Zawila-Niedzwiecki, Tomasz
    [J]. EUROPEAN JOURNAL OF REMOTE SENSING, 2016, 49 : 599 - 621
  • [6] Application of Intelligent Interpolation Methods for DTM Generation of Forest Areas Based on LiDAR Data
    Gomroki, Masoomeh
    Jafari, Marzieh
    Sadeghian, Saeed
    Azizi, Zahra
    [J]. PFG-JOURNAL OF PHOTOGRAMMETRY REMOTE SENSING AND GEOINFORMATION SCIENCE, 2017, 85 (04): : 227 - 241
  • [7] A new hierarchical moving curve-fitting algorithm for filtering lidar data for automatic DTM generation
    Su, Wei
    Sun, Zhongping
    Zhong, Ruofei
    Huang, Jianxi
    Li, Menglin
    Zhu, Jingguo
    Zhang, Keshu
    Wu, Honggan
    Zhu, Dehai
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2015, 36 (14) : 3616 - 3635
  • [8] Adaptive Slope Filtering of Airborne LiDAR Data in Urban Areas for Digital Terrain Model (DTM) Generation
    Susaki, Junichi
    [J]. REMOTE SENSING, 2012, 4 (06): : 1804 - 1819
  • [9] An Object-Based Ground Filtering of Airborne LiDAR Data for Large-Area DTM Generation
    Song, Hunsoo
    Jung, Jinha
    [J]. REMOTE SENSING, 2023, 15 (16)
  • [10] Adaptive algorithm for large scale dtm interpolation from lidar data for forestry applications in steep forested terrain
    Maguya, Almasi S.
    Junttila, Virpi
    Kauranne, Tuomo
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2013, 85 : 74 - 83