Absolute Radiometric Calibration of ALS Intensity Data: Effects on Accuracy and Target Classification

被引:38
|
作者
Kaasalainen, Sanna [1 ]
Pyysalo, Ulla [2 ]
Krooks, Anssi [1 ]
Vain, Ants [1 ,3 ]
Kukko, Antero [1 ]
Hyyppa, Juha [1 ]
Kaasalainen, Mikko [4 ]
机构
[1] Finnish Geodet Inst, Dept Remote Sensing & Photogrammetry, Masala 02431, Finland
[2] Finnish Geodet Inst, Dept Geoinformat & Cartog, Masala 02431, Finland
[3] Estonian Univ Life Sci, EE-51014 Tartu, Estonia
[4] Tampere Univ Technol, Dept Math, FIN-33101 Tampere, Finland
来源
SENSORS | 2011年 / 11卷 / 11期
基金
芬兰科学院;
关键词
LiDAR; 42.68.Wt; 42.79.Qx calibration; 06.20.fb remote sensing; 07.07.Df 07.07.Df sensors; remote sensing; TERRESTRIAL LASER SCANNER; LIDAR HEIGHT; AIRBORNE;
D O I
10.3390/s111110586
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Radiometric calibration of airborne laser scanning (ALS) intensity data aims at retrieving a value related to the target scattering properties, which is independent on the instrument or flight parameters. The aim of a calibration procedure is also to be able to compare results from different flights and instruments, but practical applications are sparsely available, and the performance of calibration methods for this purpose needs to be further assessed. We have studied the radiometric calibration with data from three separate flights and two different instruments using external calibration targets. We find that the intensity data from different flights and instruments can be compared to each other only after a radiometric calibration process using separate calibration targets carefully selected for each flight. The calibration is also necessary for target classification purposes, such as separating vegetation from sand using intensity data from different flights. The classification results are meaningful only for calibrated intensity data.
引用
收藏
页码:10586 / 10602
页数:17
相关论文
共 45 条
  • [32] The Effects of Point or Polygon Based Training Data on RandomForest Classification Accuracy of Wetlands
    Corcoran, Jennifer
    Knight, Joseph
    Pelletier, Keith
    Rampi, Lian
    Wang, Yan
    REMOTE SENSING, 2015, 7 (04) : 4002 - 4025
  • [33] Effects of input data accuracy, catchment threshold areas and calibration algorithms on model uncertainty reduction
    Wu, Lei
    Xu, Yonghong
    Li, Ruizhi
    EUROPEAN JOURNAL OF SOIL SCIENCE, 2024, 75 (04)
  • [34] Calibration of full-waveform LIDAR data by range between sensor and target and its impact for landscape classification
    Xu, Guangcai
    Pang, Yong
    Li, Zengyuan
    INTERNATIONAL SYMPOSIUM ON LIDAR AND RADAR MAPPING 2011: TECHNOLOGIES AND APPLICATIONS, 2011, 8286
  • [35] Investigating the Effects of Satellite Data Fusion on the Accuracy of Forest Type Classification in Mazandaran Province
    Oladi, Jafar
    Bozornia, Delavar
    Rashidi, Farahnaz
    Jalilvand, Hamid
    NETWORKING THE WORLD WITH REMOTE SENSING, 2010, 38 : 647 - 651
  • [36] Hyperspectral and Lidar Intensity Data Fusion: A Framework for the Rigorous Correction of Illumination, Anisotropic Effects, and Cross Calibration
    Brell, Maximilian
    Segl, Karl
    Guanter, Luis
    Bookhagen, Bodo
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2017, 55 (05): : 2799 - 2810
  • [37] The Effects of Calibration Target, Screen Location, and Movement Type on Infant Eye-Tracking Data Quality
    Schlegelmilch, Karola
    Wertz, Annie E.
    INFANCY, 2019, 24 (04) : 636 - 662
  • [38] The effects of multidimensional data clustering on the accuracy of virtual in-situ calibration in the photovoltaic/Thermal heat pump system
    Li, Jiteng
    Wang, Peng
    Zhao, Tianyi
    Yoon, Sungmin
    Wang, Jiaqiang
    JOURNAL OF BUILDING ENGINEERING, 2022, 45
  • [39] Immediate Post-Concussion and Cognitive Testing (ImPACT): Effects of Data Integration Strategies on Classification Accuracy
    Gaudet, Charles E.
    JOURNAL OF HEAD TRAUMA REHABILITATION, 2022, 37 (05) : E319 - E326
  • [40] Scaling of classification systems—effects of class precision on detection accuracy from medium resolution multispectral data
    Daniel Gann
    Jennifer Richards
    Landscape Ecology, 2023, 38 : 659 - 687