Vicarious Methodologies to Assess and Improve the Quality of the Optical Remote Sensing Images: A Critical Review

被引:29
|
作者
Kabir, Sakib [1 ]
Leigh, Larry [1 ]
Helder, Dennis [2 ]
机构
[1] South Dakota State Univ SDSU, Dept Elect Engn & Comp Sci, Image Proc Lab, Brookings, SD 57007 USA
[2] South Dakota State Univ, Dept Elect Engn & Comp Sci, Brookings, SD 57007 USA
关键词
radiometry; geometry; spatial; calibration; radiometric stability; signal-to-noise ratio; artifacts; modulation transfer function; registration accuracy; geodetic accuracy; ABSOLUTE RADIOMETRIC CALIBRATION; DEEP CONVECTIVE CLOUDS; ORBIT SPATIAL CHARACTERIZATION; THEMATIC MAPPER PLUS; CROSS-CALIBRATION; GEOMETRIC CALIBRATION; LUNAR CALIBRATION; DESERT SITES; TIME-SERIES; PERFORMANCE;
D O I
10.3390/rs12244029
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Over the past decade, number of optical Earth-observing satellites performing remote sensing has increased substantially, dramatically increasing the capability to monitor the Earth. The quantity of remote sensing satellite increase is primarily driven by improved technology, miniaturization of components, reduced manufacturing, and launch cost. These satellites often lack on-board calibrators that a large satellite utilizes to ensure high quality (radiometric, geometric, spatial quality, etc.) scientific measurement. To address this issue, this work presents "best" vicarious image quality assessment and improvement techniques for those kinds of optical satellites which lack an on-board calibration system. In this article, image quality categories have been explored, and essential quality parameters (absolute and relative calibration, aliasing, etc.) have been identified. For each of the parameters, appropriate characterization methods are identified along with their specifications or requirements. In cases of multiple methods, recommendations have been made based-on the strengths and weaknesses of each method. Furthermore, processing steps have been presented, including examples. Essentially, this paper provides a comprehensive study of the criteria that need to be assessed to evaluate remote sensing satellite data quality, and the best vicarious methodologies to evaluate identified quality parameters such as coherent noise and ground sample distance.
引用
收藏
页码:1 / 40
页数:40
相关论文
共 50 条
  • [1] Critical review on deep learning methodologies employed for water-body segmentation through remote sensing images
    Gautam, Swati
    Singhai, Jyoti
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 83 (1) : 1869 - 1889
  • [2] Critical review on deep learning methodologies employed for water-body segmentation through remote sensing images
    Swati Gautam
    Jyoti Singhai
    [J]. Multimedia Tools and Applications, 2024, 83 : 1869 - 1889
  • [3] The Quality of Remote Sensing Optical Images from Acquisition to Users
    Selva, Massimo
    [J]. REMOTE SENSING, 2021, 13 (07)
  • [4] Bio-optical modelling combined with remote sensing to assess water quality
    Ammenberg, P
    Flink, P
    Lindell, T
    Pierson, D
    Strömbeck, N
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2002, 23 (08) : 1621 - 1638
  • [5] Remote sensing techniques to assess water quality
    Ritchie, JC
    Zimba, PV
    Everitt, JH
    [J]. PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2003, 69 (06): : 695 - 704
  • [6] Review of remote sensing methodologies for pavement management and assessment
    Schnebele, E.
    Tanyu, B. F.
    Cervone, G.
    Waters, N.
    [J]. EUROPEAN TRANSPORT RESEARCH REVIEW, 2015, 7 (02)
  • [7] Review of remote sensing methodologies for pavement management and assessment
    E. Schnebele
    B. F. Tanyu
    G. Cervone
    N. Waters
    [J]. European Transport Research Review, 2015, 7
  • [8] Full-Reference Quality Metric Based on Neural Network to Assess the Visual Quality of Remote Sensing Images
    Ieremeiev, Oleg
    Lukin, Vladimir
    Okarma, Krzysztof
    Egiazarian, Karen
    [J]. REMOTE SENSING, 2020, 12 (15)
  • [9] Extraction of Surface Water Bodies using Optical Remote Sensing Images: A Review
    R Nagaraj
    Lakshmi Sutha Kumar
    [J]. Earth Science Informatics, 2024, 17 : 893 - 956
  • [10] Extraction of Surface Water Bodies using Optical Remote Sensing Images: A Review
    Nagaraj, R.
    Kumar, Lakshmi Sutha
    [J]. EARTH SCIENCE INFORMATICS, 2024, 17 (02) : 893 - 956