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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Multi-temporal JERS SAR data in boreal forest biomass mapping
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Multi-temporal JERS SAR data in boreal forest biomass mapping

机译：北方森林生物量测绘中的多时间JERS SAR数据

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摘要

Multi-temporal JERS SAR data were studied for forest biomass mapping. The study site was located in South-eastern Finland in Ruokolahti. Pre-processing of JERS SAR data included ortho-rectification and radiometric normalization of topographic effects.In single-date regression analysis between backscatter amplitude and stem volume, summer scenes from July to October produced correlation coefficients (r) between 0.63 and 0.81. Backscatter level and the slope of the (linear) regression line were stable from scene to scene. Winter scenes acquired in very cold and dry winter conditions had a very low correlation. One winter scene acquired in Conditions where snow is not completely frozen produced a correlation coefficient similar to summer scenes.Multivariate regression analysis with a 6-date JERS SAR dataset produced correlation coefficient of 0.85. A combined JERS-optical regression analysis improved the correlation coefficient to 0.89 and also alleviated the saturation, which affects both SAR and optical data.The stability of the regression results in summer scenes suggests that a simple constant model could be used in wide-area forest biomass mapping if accuracy requirements are low and if biomass estimates are aggregated to large areal units. (C) 2005 Elsevier Inc. All rights reserved.
机译：研究了多时间JERS SAR数据用于森林生物量测绘。研究地点位于芬兰东南部的Ruokolahti。 JERS SAR数据的预处理包括地形影响的正射校正和辐射归一化。在反向散射振幅与茎体积之间的单日回归分析中，7月至10月的夏季场景产生的相关系数（r）在0.63至0.81之间。场景之间的反向散射水平和（线性）回归线的斜率是稳定的。在非常寒冷和干燥的冬季条件下获得的冬季景物的相关性很低。在雪未完全冻结的条件下获得的一个冬季场景产生的相关系数与夏季场景相似.6天JERS SAR数据集的多元回归分析得出的相关系数为0.85。结合JERS-光学回归分析可以将相关系数提高到0.89，并且可以降低饱和度，从而影响SAR和光学数据。夏季场景中回归结果的稳定性表明，可以在广域森林中使用简单的常数模型如果精度要求较低且生物量估算值汇总到较大的面积单位，则进行生物量制图。 （C）2005 Elsevier Inc.保留所有权利。

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