A Regression Model Based on Second Intensity Moment for Estimating Coniferous Tree Biomass from High-Resolution L-band Crosss-Polarized Pi-SAR Date(WSANE 2008 (Workshop for Space, Aeronautical and Navigational Electronics))
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概要
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Results are described on the regression analysis between the coniferous tree biomass and the second intensity moment of the L-band high-resolution cross-polarized synthetic aperture radar (SAR) images. From the regression analysis, the moment-based model for estimating tree biomass was developed and its accuracy was tested. The SAR data were acquired by the airborne polarimetric interferometric SAR (Pi-SAR) developed jointly by the National Institute of Information and Communications Technology (NICT) and the Japan Aerospace Exploration Agency (JAXA) over the Tomakomai national forests in Hokkaido, Japan. The comparison of the tree biomass values estimated by the model function and those measured by the field survey showed the average measurement accuracy of 85% for individual forest stands, which is similar to the accuracy (86%) of the previous K-distribution model. The moment model is robust and does not require any specific probability density function (PDF) that fits to the image texture.
- 社団法人電子情報通信学会の論文
- 2008-11-17
著者
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Ouchi Kazuo
Department Of Computer Science National Defense Academy
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Wang Haipeng
Key Laboratory Of Wave Scattering And Remote Sensing Department Of Communication Science And Enginee
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Wang Haipeng
Key Laboratory Of Wave Scattering And Remote Sensing Department Of Communication Science And Enginee
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Ouchi Kazuo
Department Of Computer Science School Of Electrical And Computer Engineering National Defense Academ
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