The Effectiveness of Texture Features for Higher-Accuracy Satellite Monitoring of Shallow Water

DOI
  • KANNO Ariyo
    東京大学大学院新領域創成化学研究科社会文化環境学専攻
  • KOIBUCHI Yukio
    東京大学大学院新領域創成化学研究科社会文化環境学専攻
  • ISOBE Masahiko
    東京大学大学院新領域創成化学研究科社会文化環境学専攻

Bibliographic Information

Other Title
  • 浅水域衛星モニタリング高精度化のためのテクスチャ特徴量の利用可能性

Abstract

Satellite images of shallow water have a potential of enabling high-resolution spatial-temporal monitoring of water depth and bottom feature.However, traditional methods based solely on the spectral information cannot estimate them simultaneously without hyperspectral sensors or additional information on bottom reflectivity.In this paper, the effectiveness of utilizing the textural information (texture features derived from Gray Level Co-occurrence Matrix) as well as spectral information is examined through depth estimation and bottom classification experiments with a Quick Bird image. As a result, textural information is found to be effective in enhancing the accuracy.

Journal

Keywords

Details 詳細情報について

  • CRID
    1390282679527397760
  • NII Article ID
    130003992217
  • DOI
    10.2208/proce1989.55.1461
  • ISSN
    18848222
    09167897
  • Data Source
    • JaLC
    • Crossref
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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