Wheat and rapeseed are significant crops in Czech agriculture and remote sensing has huge potential for their management, given Sentinel-1 can overcome issues of cloudiness and monitor vegetation development via radar backscatter. This study compares radar and optical data characterizing the development of wheat and rapeseed in an agricultural cooperative in the Czech Republic. Radar Vegetation Index (RVI) and Normalized Difference Vegetation Index (NDVI) time-series of the main vegetation seasons between 2015 and 2018 are processed, analysed, and compared with each other. In 2018, the comparison of data with ground measurement by camera was also used. The temporal development of RVI is affected by noise, which is caused by the composition of imagery from different Relative orbits. The separation of imagery according to the Relative orbit used seemed to provide results more comparable to the phenological curve. Simple linear regression between NDVI and RVI illustrated that considering Relative orbit can slightly increase the Coefficient of determination. By selecting a suitable Relative orbit, the coefficient of determination between NDVI and RVI increased from 0.281 to 0.387 in the case of wheat and from 0.233 to 0.316 in the case of rape monitoring. The RVI for rapeseed and the height of canopy correlation was 0.392. The results for RVI presented in this article demonstrated that monitoring wheat and rapeseed development by Sentinel-1 has potential, however more research needs to be conducted in the areas of spatial and temporal noise removal.

小麦和油菜籽是捷克农业中的重要作物，鉴于 Sentinel-1 可以克服多云问题并通过雷达反向散射监测植被发育，遥感对其管理具有巨大潜力。本研究比较了表征捷克共和国农业合作社小麦和油菜籽发育特征的雷达和光学数据。对2015-2018年主要植被季节的雷达植被指数（RVI）和归一化差异植被指数（NDVI）时间序列进行处理、分析和比较。2018年也采用了相机地面测量数据对比。RVI 的时间发展受到噪声的影响，噪声是由来自不同相对轨道的影像组合引起的。根据所使用的相对轨道分离图像似乎提供了与物候曲线更具有可比性的结果。NDVI 和 RVI 之间的简单线性回归说明考虑相对轨道可以稍微增加确定系数。通过选择合适的相对轨道，小麦的NDVI和RVI之间的决定系数从0.281增加到0.387，油菜监测从0.233增加到0.316。油菜籽的 RVI 与冠层高度相关性为 0.392。本文介绍的 RVI 结果表明，Sentinel-1 监测小麦和油菜籽发育具有潜力，但需要在时空噪声去除领域进行更多研究。NDVI 和 RVI 之间的简单线性回归说明考虑相对轨道可以稍微增加确定系数。通过选择合适的相对轨道，小麦的NDVI和RVI之间的决定系数从0.281增加到0.387，油菜监测从0.233增加到0.316。油菜籽的 RVI 与冠层高度相关性为 0.392。本文介绍的 RVI 结果表明，Sentinel-1 监测小麦和油菜籽发育具有潜力，但需要在时空噪声去除领域进行更多研究。NDVI 和 RVI 之间的简单线性回归说明考虑相对轨道可以稍微增加确定系数。通过选择合适的相对轨道，小麦的NDVI和RVI之间的决定系数从0.281增加到0.387，油菜监测从0.233增加到0.316。油菜籽的 RVI 与冠层高度相关性为 0.392。本文介绍的 RVI 结果表明，Sentinel-1 监测小麦和油菜籽发育具有潜力，但需要在时空噪声去除领域进行更多研究。NDVI和RVI之间的决定系数在小麦的情况下从0.281增加到0.387，在油菜监测的情况下从0.233增加到0.316。油菜籽的 RVI 与冠层高度相关性为 0.392。本文介绍的 RVI 结果表明，Sentinel-1 监测小麦和油菜籽发育具有潜力，但需要在时空噪声去除领域进行更多研究。NDVI和RVI之间的决定系数在小麦的情况下从0.281增加到0.387，在油菜监测的情况下从0.233增加到0.316。油菜籽的 RVI 与冠层高度相关性为 0.392。本文介绍的 RVI 结果表明，Sentinel-1 监测小麦和油菜籽发育具有潜力，但需要在时空噪声去除领域进行更多研究。