ABSTRACT With the advent of optical sensors, thermal-based indicators can be retrieved at multiscale levels from handheld devices to satellite platforms, providing a low-cost method to mirror plant water status. Here, we measured the canopy temperature of Orange trees subjected to different irrigation levels (100%, 75%, and 50% of crop water requirement) and strategies (regulated deficit irrigation (DI) and partial root drying (PRD)) to determine the crop water stress index (CWSI). Additionally, the CWSI was estimated based on Land Remote-Sensing Satellite (Landsat) thermal data using hot-cold patches (approach 1) and a novel mechanistic method combined with Sentinel-2 data (approach 2). Based on the in-situ measurements, the CWSI non-water stressed baseline was estimated as T c – T a = −0.57 × (VPD) + 2.31 (N = 370, R 2 = 0.82), defining ‘VPD’ as ‘vapour pressure deficit’, and the upper limit was found to be relatively constant (T c – T a = 3.43°C). The in-field water stress variability among the different irrigation levels was effectively captured using the CWSI; however, the difference between the DI and PRD irrigated trees was only significant at the 50% irrigation level. Considering the remotely-sensed approach, the CWSI from our proposed method (approach 2) resulted in higher accuracy (root mean square error, RMSE = 0.03; mean bias error, MBE = −0.02) compared to approach 1 (RMSE = 0.10, MBE = −0.08). The improved accuracy from our proposed method was attributed to accounting for VPD and net radiation, applying an iterative method to calculate and calibrate aerodynamic resistance, and the use of high-resolution imagery from Sentinel-2 for reducing the soil background impact on canopy temperature.

中文翻译：

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使用原位测量、Landsat 和 Sentinel-2 数据评估柑橘作物水分胁迫指数

摘要 随着光学传感器的出现，可以在从手持设备到卫星平台的多尺度水平上检索基于热的指标，提供了一种反映植物水分状况的低成本方法。在这里，我们测量了在不同灌溉水平（100%、75% 和 50% 的作物需水量）和策略（调节亏缺灌溉 (DI) 和部分根部干燥 (PRD)）下橙树的冠层温度，以确定作物水分胁迫指数（CWSI）。此外，CWSI 是基于陆地遥感卫星 (Landsat) 热数据使用冷热补丁（方法 1）和结合 Sentinel-2 数据的新型机械方法（方法 2）估算的。根据原位测量，CWSI 无水压力基线估计为 T c – T a = -0.57 × (VPD) + 2.31 (N = 370, R 2 = 0.82)，将“VPD”定义为“蒸气压不足”，发现上限相对恒定（T c – T a = 3.43°C）。使用 CWSI 有效地捕获了不同灌溉水平之间的田间水分压力变化；然而，DI 和珠三角灌溉的树木之间的差异仅在 50% 的灌溉水平上显着。考虑到遥感方法，与方法 1（RMSE = 0.10，MBE）相比，我们提出的方法（方法 2）的 CWSI 具有更高的精度（均方根误差，RMSE = 0.03；平均偏差误差，MBE = -0.02） = -0.08）。我们提出的方法提高的准确性归因于考虑 VPD 和净辐射，应用迭代方法来计算和校准空气动力阻力，