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Development of Forest Information Measurement System by Multi-Wavelength and Multi-Polarization High-Resolution Synthetic Aperture Radar

Development of Forest Information Measurement System by Multi-Wavelength and Multi-Polarization High-Resolution Synthetic Aperture Radar
多波长多偏振高分辨率合成孔径雷达森林信息测量系统研制
批准号:
17360194
负责人:
TAKAGI Masataka
金额:
$6.46万
依托单位国家:
日本
项目类别:
Grant-in-Aid for Scientific Research (B)
财政年份:
2005
资助国家:
日本
项目状态:
已结题
起止时间:
2005 至 2006

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中文摘要
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英文摘要
The purpose of this research is to develop techniques to extract forest information from the high-resolution multi-wavelength and multi-polarization synthetic aperture radar, Pi-SAR, developed jointly by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT). The test site is the coniferous forests in Tomakomai, Hokkaido. First, regression analyses are carried out between the Pi-SAR images acquired in November 2002, and the forest data measured simultaneously on the ground and the forest data measured in August 2003. Using the conventional technique that utilizes the radar cross section (RCS), it is found that there is no significant correlation between the X-band RCS and forest parameters at all polarizations. The L-band RCS, however, is found to increase with increasing forest biomass up to approximately 40 tons/ha. These trends are similar to those already reported by several researchers. Next, because the high-re … More solution SAR images appear to show the structures of the forests, the relation between the image texture and forest information is sought. As a result, the image amplitudes are found to obey the K-distributed probability density function; and that strong correlation exists between the order parameter of the K-distribution in the cross-polarized images and the forest biomass. Further, it is found that the order parameter increases with increasing biomass up to around 100 tons/ha which is well beyond the saturation limit of the conventional RCS method. From the regression curve, the biomass values of unknown forests is estimated and compared with those measured on the ground in 2005-2006. The comparison yields the model accuracy of 86%. Finally, the regression model is updated using all biomass data measured on the ground. This model is considered to be effective for estimating the biomass of coniferous forests on flat ground in the entire areas of Hokkaido; and the accuracy of estimating the forest biomass can be improved to much higher levels by combining the conventional RCS technique and the texture analysis developed in this study. Less
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On the accuracy of empirical relation between forest biomass and order parameter of K-distribution in Pi-SAR images
论Pi-SAR图像中森林生物量与K分布序参数经验关系的准确性
DOI: --
发表时间: 2006
期刊: IEICE Tech. Rep. (WSANE 2006, X' an, China) 2006-21
影响因子: --
作者: [H.Wang, et al.]
通讯作者: et al.
On the accuracy of the empirical model for estimating forest biomass from K-distributed SAR images
K分布SAR影像估算森林生物量经验模型的准确性研究
DOI: --
发表时间: 2006
期刊: 技術研究報告(電子情報通信学会) SANE2006-57
影响因子: --
作者: [H.Wang, K.Ouchi, M.Watanabe, M.Shimada]
通讯作者: M.Shimada
DOI: 10.1109/lgrs.2006.878299
发表时间: 2006-10
期刊: IEEE Geoscience and Remote Sensing Letters
影响因子: 4.8
作者: [Haipeng Wang;K. Ouchi;Manabu Watanabe;M. Shimada;T. Tadono;A. Rosenqvist;S. Romshoo;M. Matsuoka;T. Moriyama;S. Uratsuka]
通讯作者: Haipeng Wang;K. Ouchi;Manabu Watanabe;M. Shimada;T. Tadono;A. Rosenqvist;S. Romshoo;M. Matsuoka;T. Moriyama;S. Uratsuka
DOI: --
发表时间: 2006
期刊: Proc. SAR Workshop 2006(Sendai, Japan) (CD-ROM)
影响因子: --
作者: [H.Wang, et al.]
通讯作者: et al.
9
    Integrated Voxel Modeling for Agro-Forestry
    • 批准号:
      17H01933
    • 项目类别:
      Grant-in-Aid for Scientific Research (B)
    • 资助金额:
      $10.32万
    • 财政年份:
      2017
    • 负责人:
      TAKAGI Masataka
    • 依托单位:
    Evaluation and Estimation of Important Plant Resource for new Agroforestry
    • 批准号:
      26281063
    • 项目类别:
      Grant-in-Aid for Scientific Research (B)
    • 资助金额:
      $11.15万
    • 财政年份:
      2014
    • 负责人:
      TAKAGI Masataka
    • 依托单位:
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    海外基金
    Identification and quantification of primary phytoplankton functional types in the global oceans from hyperspectral ocean color remote sensing
    • 批准号:
      --
    • 项目类别:
      --
    • 资助金额:
      160万元
    • 批准年份:
      2022
    • 负责人:
      李忠平
    • 依托单位: