Abstract The interest in tree phenology monitoring is increasing because this trait is a robust indicator of the impacts of climate change on natural and managed ecosystems. Different approaches to monitor phenology at different spatial scales, from in situ monitoring to remote sensing, are used to investigate spring and/or autumn phenological changes. In Mediterranean area, most of phenological changes occur during cloudy periods (spring and autumn), leading to a loss of information also for very high temporal resolution satellites. Instead, cloud-uninfluenced sensors, such as radar sensors, can allow to bypass this problem and produce a temporally continuous coverage. In this paper, we analyzed the spring phenology of two European beech (Fagus sylvatica L.) populations, located at different latitudes in Mediterranean area. Weekly in situ monitoring of leaf-out has been correlated with data collected by Synthetic Aperture Radar. Spring phenological phases were monitored in situ following a modified BBCH-code with a 5-scores scale (from 1 - buds closed and covered by scales, to 5 - leaf completely unfolded). The score 3 (young leaves starting to emerge from the bud) was considered the bud break. Different site conditions based on aspect (northern and southern) and altitudinal gradient (high and low altitude) have been considered. The aim was to test and implement a new methodology able to decrease the frequency of the field sampling, using remote data, to extend more detailed information on geographical scale, and to reconstruct past phenology. Results showed a statistically significant different length of the vegetative spring period, spanning from dormant buds, up to leaves completely unfolded, between sites. Through Synthetic Aperture Radar estimation, this study demonstrates that leaf-out can be monitored with an extreme accuracy. The phenophase score 4 and 5 estimation showed the best performance (RMSE This radar approach fixes the cloud problem typical of multispectral approach and very frequent in phenophase change periods in Mediterranean climate. This study promotes the proposed remote sensing approach as a very useful tool to monitor growing season starting in remote areas, helping to reduce in situ observations and allowing past phenology reconstruction.

中文翻译：

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通过原位观察和合成孔径雷达方法监测地中海山毛榉种群的春季物候

摘要 树木物候监测的兴趣正在增加，因为该特性是气候变化对自然和管理生态系统影响的有力指标。在不同空间尺度上监测物候的不同方法，从原位监测到遥感，用于调查春季和/或秋季物候变化。在地中海地区，大部分物候变化发生在多云时期（春季和秋季），导致时间分辨率非常高的卫星也丢失信息。相反，不受云影响的传感器，例如雷达传感器，可以绕过这个问题并产生时间上的连续覆盖。在本文中，我们分析了位于地中海地区不同纬度的两个欧洲山毛榉 (Fagus sylvatica L.) 种群的春季物候。每周一次的原位监测与合成孔径雷达收集的数据相关联。春季物候阶段按照修改后的 BBCH 代码进行原位监测，评分为 5 分（从 1 - 芽闭合并被鳞片覆盖，到 5 - 叶完全展开）。分数 3（幼叶开始从芽中出现）被认为是芽断裂。已经考虑了基于方位（北部和南部）和海拔梯度（高海拔和低海拔）的不同场地条件。目的是测试和实施一种新方法，该方法能够使用远程数据降低现场采样的频率，扩展地理范围的更详细信息，并重建过去的物候。结果显示，从休眠芽、直到叶子完全展开，在站点之间。通过合成孔径雷达估计，这项研究表明可以极其准确地监测叶出。物相评分 4 和 5 的估计显示出最佳性能（RMSE 这种雷达方法解决了多光谱方法中典型的云问题，并且在地中海气候的物相变化期间非常频繁。这项研究将所提出的遥感方法作为一种非常有用的监测工具从偏远地区开始的生长季节，有助于减少现场观察并允许过去的物候重建。