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Modeling and Verification of Microwave Scattering Characteristics of Typical Global Tropical Rainforests
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摘要: 使用大面积且均匀的自然目标进行微波散射计的定标检验, 有助于客观评价微波遥感的观测精度。热带雨林具有相对稳定的植被覆盖条件, 可减小地表异质性对仪器测量的影响, 是微波仪器定标评价的常用目标。利用2019年1月1日—2021年12月31日MetOp-B(the second meteorological operational satellite)卫星ASCAT(advanced scatterometer)散射计的观测数据, 提出平均值、标准差与相对标准差联合的雨林目标稳定区优选算法, 确定亚马逊雨林、刚果雨林和东南亚雨林的稳定区域, 对稳定区内目标的自身特性开展包括季节、入射角和方位角影响建模。建模时综合考虑模型误差和时序变化, 将目标特性与仪器波动导致的后向散射系数变化分离。结果表明:亚马逊雨林和刚果雨林稳定区的白天数据具有较低的模型误差和波动较小的变化趋势, 适用于多星散射计的定标稳定性检验。基于亚马逊雨林和刚果雨林稳定区的白天数据模型, 对MetOp-C卫星的ASCAT观测数据进行定标稳定性检验和分析, 检验结果表明:MetOp-C卫星ASCAT散射计的观测数据略有波动, 但变化幅度小于0.05 dB, 定标稳定性较好。Abstract: To ensure the microwave scatterometer is accurately calibrated, natural targets with stability, homogeneity, and isotropy are selected as references. The broad and continuous spatial distribution of the tropical rainforest, along with its relatively consistent vegetation cover, makes it an ideal choice.A tropical rainforest optimal stable area selection algorithm, combining mean, standard deviation, and relative standard deviation, is proposed using measurements from the advanced scatterometer (ASCAT) onboard the second Meteorological Operational satellite (MetOp-B) from 2019 to 2021. It is used to identify stable areas within the Amazon, Congo, and Southeast Asian rainforests. Results show that the Amazon rainforest has a larger stable area compared to the Congo and Southeast Asian rainforests, indicating more consistent backscatter across space. However, the Southeast Asian rainforest exhibits scattered stable areas and unstable backscatter properties.To accurately model the intrinsic characteristics of targets within stable areas, influences of seasonal variations, incidence angles and azimuth angles are comprehensively considered. The scatterometer, as an independently measured remote sensing instrument, is not affected by seasonal variations on the earth and experiences minimal temperature-related fluctuations. Therefore, seasonal characteristics of backscatter coefficients in rainforests can be modeled to reduce their impact. Different incidence and azimuth angles can cause variations in the backscatter coefficient. To address this issue, responses to these aspects are also modeled. It is observed that daytime data, with lower model errors, shows greater stability in the stable areas of the Amazon and Congo rainforests. Therefore, daytime data from these areas should be selected to assess instrument stability.A stability verification of ASCAT measurements from the stable areas of the Amazon and Congo rainforest on MetOp-C, covering the period from 1 July 2019 to 31 October 2023, is carried out based on model coefficients derived from the continuous three-year data of ASCAT on MetOp-B. The calibration stability verification quantifies the magnitude of variations in ASCAT measurements over different periods. Through analysis, it's found that measurements from the ASCAT on MetOp-C shows regular fluctuations of about 0.05 dB, indicating relatively stable characteristics.
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图 2 稳定区域后向散射系数月平均值时序图 (升轨为夜间，降轨为白天)
Fig. 2 Monthly average time series of backscatter coefficient in stable areas (ascending orbits occur at night, while descending orbits occur in the daytime)
图 3 经时间修正后稳定区域后向散射系数月平均值时序图
Fig. 3 Monthly average time series of backscatter coefficient in stable areas after time correction
图 4 稳定区域后向散射系数随入射角变化 (黑色实线为拟合线)
Fig. 4 Backscatter coefficient varying with incident angle for stable areas (the black solid line denotes fitting curve)
图 5 稳定区域后向散射系数随方位角变化 (黑色实线为拟合线)
Fig. 5 Backscatter coefficient varying with azimuth angle for stable areas (the black solid line denotes fitting curve)
图 6 MetOp-C卫星ASCAT散射计定标检验曲线
Fig. 6 Validation curve of ASCAT scatterometer onboard MetOp-C satellite
表 1 掩膜确定方法的阈值
Table 1 Thresholds for each mask determination method
时段 平均值法/dB 相对标准差法/dB 标准差法/dB 白天 ±0.5 1.0 0.2 夜间 ±0.5 1.0 0.2 
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表 2 不同稳定区域的评价指标
Table 2 Evaluation indices in different stable areas
地区 时段 均方根误差/dB 平均绝对误差/dB 决定系数 亚马逊雨林 夜间 0.182 0.145 0.960 白天 0.157 0.120 0.971 刚果雨林 夜间 0.175 0.138 0.961 白天 0.159 0.122 0.970 东南亚雨林 夜间 0.317 0.254 0.893 白天 0.280 0.222 0.913
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表 3 不同入射角和方位角响应下的评价指标
Table 3 Results of each evaluation index under different incident angle and azimuth angle responses
地区 模型参数项 时段 均方根误差/dB 平均绝对误差/dB 决定系数 亚马逊雨林 无入射角调制 夜间 0.717 0.554 0.410 白天 0.711 0.540 0.431 仅含线性入射角调制 夜间 0.203 0.162 0.951 白天 0.191 0.151 0.958 无方位角调制 夜间 0.191 0.152 0.955 白天 0.167 0.130 0.966 仅含一阶方位角调制 夜间 0.183 0.146 0.959 白天 0.160 0.123 0.969 刚果雨林 无入射角调制 夜间 0.717 0.551 0.390 白天 0.739 0.562 0.409 仅含线性入射角调制 夜间 0.200 0.159 0.951 白天 0.195 0.155 0.957 无方位角调制 夜间 0.181 0.143 0.959 白天 0.166 0.129 0.968 仅含一阶方位角调制 夜间 0.176 0.139 0.961 白天 0.161 0.124 0.970
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