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Extraction of forest biophysical parameters using polarimetric SAR.

机译：利用极化SAR提取森林生物物理参数。

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摘要

This thesis examines the potential of high resolution fully polarimetric C-Band SAR data for forest species discrimination and forest biophysical parameter modeling. The SAR parameters that are most useful for each task are identified and the achievable model performance is determined. Factors that influence the quality of the results such as radar incident angle and forest stand species composition are also evaluated.;Polarimetric C-band SAR measurements can be used to effectively discriminate forest species into broad classes but more specific classification is not as accurate. Furthermore, it was found that radar incident angle has a significant impact on the modeling results. The extent of the impact varies depending on the nature of the SAR parameter. Species stratification is also an essential component of model development. The strongest relationships are achieved for forest basal area and volume whereas age and height produced the weakest models.
机译：本文探讨了高分辨率全极化C波段SAR数据在森林物种识别和森林生物物理参数建模中的潜力。确定对每个任务最有用的SAR参数，并确定可实现的模型性能。还评估了影响结果质量的因素，例如雷达入射角和林分物种组成。；测压C带SAR测量可用于有效地将森林物种区分为大类，但更具体的分类却不那么准确。此外，还发现雷达入射角对建模结果有重大影响。影响的程度取决于SAR参数的性质。物种分层也是模型开发的重要组成部分。森林基础面积和体积之间的关系最强，而年龄和高度则最弱。

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