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首页> 外文期刊>Remote Sensing >The Penetration Depth Derived from the Synthesis of ALOS/PALSAR InSAR Data and ASTER GDEM for the Mapping of Forest Biomass
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The Penetration Depth Derived from the Synthesis of ALOS/PALSAR InSAR Data and ASTER GDEM for the Mapping of Forest Biomass

机译:ALOS / PALSAR InSAR数据和ASTER GDEM合成的穿透深度用于森林生物量测绘

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摘要

The Global Digital Elevation Model produced from stereo images of Advanced Spaceborne Thermal Emission and Reflection Radiometer data (ASTER GDEM) covers land surfaces between latitudes of 83°N and 83°S. The Phased Array type L-band Synthetic Aperture Radar (PALSAR) onboard Advanced Land Observing Satellite (ALOS) collected many SAR images since it was launched on 24 January 2006. The combination of ALOS/PALSAR interferometric data and ASTER GDEM should provide the penetration depth of SAR data assuming ASTER GDEM was the elevation of vegetation canopy top. It would be correlated with forest biomass because penetration depth could be affected by forest density and forest canopy height. Their combination held great promises for the forest biomass mapping over large area. The feasibility of forest biomass mapping through the data synthesis of ALOS/PALSAR InSAR data and ASTER GDEM was investigated in this study. A procedure for the extraction of penetration depth was firstly proposed. Then three models were built for biomass estimation: (I) model only using backscattering coefficients of ALOS/PALSAR data; (II) model only using penetration depth; (III) model using both of them. The biomass estimated from Lidar data was taken as reference data to evaluate the three different models. The results showed that the combination of backscattering coefficients and penetration depth gave the best accuracy. The forest disturbance has to be considered in forest biomass estimation because of the long time span of ASTER data for generating ASTER GDEM. The spatial homogeneity could be used to improve estimation accuracy.
机译:由先进的星载热发射和反射辐射计数据(ASTER GDEM)的立体图像生成的全球数字高程模型覆盖了北纬83°S至83°S之间的陆地表面。自2006年1月24日发射以来,高级陆地观测卫星(ALOS)上的相控阵型L波段合成孔径雷达(PALSAR)收集了许多SAR图像。ALOS/ PALSAR干涉测量数据与ASTER GDEM的结合应提供穿透深度SAR数据假设ASTER GDEM是植被冠层顶部的高程。它与森林生物量相关,因为渗透深度可能受森林密度和林冠层高度的影响。他们的结合为大面积森林生物量测绘提供了广阔的前景。通过对ALOS / PALSAR InSAR数据和ASTER GDEM数据综合进行森林生物量作图的可行性进行了研究。首先提出了一种穿透深度的提取方法。然后建立了三种用于生物量估计的模型:(I)仅使用ALOS / PALSAR数据的反向散射系数的模型; (II)仅使用穿透深度进行建模; (III)同时使用两者进行建模。根据激光雷达数据估算的生物量用作参考数据,以评估三种不同的模型。结果表明,反向散射系数和穿透深度的组合提供了最佳精度。由于用于生成ASTER GDEM的ASTER数据的时间跨度较长,因此在森林生物量估算中必须考虑森林干扰。空间均匀性可用于提高估计精度。

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