Abstract The study investigates the suitability of Sentinel-1 data product of C-band frequency (5.36 GHz) in the estimation of terrestrial biomass. The experiment was carried out in the Perambular District, Tamil Nadu, India. The model DPSVI (Dual Polarization SAR Vegetation Index) was proposed based on the pattern of scatter plot constructed between the backscattering coefficient of VV (σvvo) and VH (σvho) imageries in which the pixels representing the surface features such as vegetation, soil, and water bodies were distributed according to the theory ‘Degree of Depolarization (DOP)’. The model was developed by proposing and integrating three crucial parameters (i) Inverse Dual-Pol Diagonal Distance (IDPDD) (ii) Vertical Dual De-polarization Index (VDDPI) and (iii) σvho which are highly influential towards biomass extraction. The model was executed for two different seasons (wet and dry) from 2015 to 2017. The resultant output was tested with Normalized Differential Vegetation Index (NDVI) derived from Sentinel 2, and the field observed Above Ground Biomass (AGB) from 50 sampling locations to demonstrate the theoretical and in-situ potential of the proposed model. The resultant product of the DPSVI has shown the acceptable R2 value of 0.75 for the dry season and 0.73 for the wet season with NDVI and got R2 value of 0.73 for the dry and R2 value of 0.70 for the wet season with AGB which manifested that the proposed model was an effective indicator of terrestrial vegetation irrespective of seasons.

中文翻译：

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双极化合成孔径雷达在生物量反演中的意义：Sentinel-1的尝试

摘要 本研究研究了C波段频率(5.36 GHz)的Sentinel-1数据产品在估算陆地生物量中的适用性。该实验在印度泰米尔纳德邦的 Perambular 区进行。模型 DPSVI（双极化 SAR 植被指数）是基于 VV (σvvo) 和 VH (σvho) 影像的后向散射系数之间构建的散点图模式提出的，其中像素代表植被、土壤和土壤等地表特征。根据“去极化程度（DOP）”理论分布水体。该模型是通过提出和整合三个关键参数来开发的：(i) 反双极化对角线距离 (IDPDD) (ii) 垂直双去极化指数 (VDDPI) 和 (iii) σvho，它们对生物量提取有很大影响。该模型在 2015 年至 2017 年的两个不同季节（干湿两季）执行。结果输出使用源自哨兵 2 的归一化差异植被指数 (NDVI) 进行测试，并从 50 个采样位置观察到的地面生物量 (AGB)证明所提出模型的理论和原位潜力。DPSVI 的结果表明，NDVI 的干季 R2 值为 0.75，湿季的 R2 值为 0.73，干季的 R2 值为 0.73，AGB 的雨季 R2 值为 0.70，这表明拟议的模型是一种有效的陆地植被指标，不受季节影响。以及从 50 个采样位置观察到的地上生物量 (AGB) 的现场，以证明所提出模型的理论和原位潜力。DPSVI 的结果表明，NDVI 的干季 R2 值为 0.75，湿季的 R2 值为 0.73，干季的 R2 值为 0.73，AGB 的雨季 R2 值为 0.70，这表明拟议的模型是一种有效的陆地植被指标，不受季节影响。以及从 50 个采样位置观察到的地上生物量 (AGB) 的现场，以证明所提出模型的理论和原位潜力。DPSVI 的结果表明，NDVI 的干季 R2 值为 0.75，湿季的 R2 值为 0.73，干季的 R2 值为 0.73，AGB 的雨季 R2 值为 0.70，这表明拟议的模型是一种有效的陆地植被指标，不受季节影响。