A STUDY ON VERSATILITY IMPROVEMENT OF SATELLITE SAR SOIL MOISTURE ESTIMATION ALGORITHM USING LONG-TERM SOIL MOISTURE OBSERVATION DATA IN MONGOLIA

DOI Web Site 7 References
  • AIDA Kentaro
    土木研究所 水災害リスクマネジメント国際センター
  • KUBOTA Keijiro
    土木研究所 水災害リスクマネジメント国際センター
  • ASANUMA Jun
    筑波大学 放射線・アイソトープ地球システム研究センター
  • KAIHOTSU Ichirow
    広島大学
  • KOIKE Toshio
    土木研究所 水災害リスクマネジメント国際センター

Bibliographic Information

Other Title
  • モンゴル長期土壌水分観測データを用いた衛星SAR土壌水分推定アルゴリズムの汎用性向上のための検討

Abstract

<p> In this research, the authors studied how to improve the versatility of the existing soil moisture estimation algorithm developed on the premise of using ALOS/PALSAR. We first showed that the existing algorithm, though originally set to assume that the incident angle is constant, can use the ALOS2/PALSAR2 multi-polarized wave data by adapting it to process changes in the incident angle. The problem is that multi-polarized wave mode observation is highly infrequent. However, with multiple SAR observations and estimated soil moisture maps created based on them, it is technically possible to estimate the ground surface roughness by performing in-verse estimation using the microwave scattering model. Therefore, with the creation of such datasets in mind, we experimentally estimated soil moisture from the Sentinel-1/C-SAR data using the random forest method, a machine learning approach.</p>

Journal

References(7)*help

See more

Keywords

Details 詳細情報について

Report a problem

Back to top