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首页> 外文期刊>Irrigation Science >Assessment of vineyard water status variability by thermal and multispectral imagery using an unmanned aerial vehicle (UAV). (Special Issue: Advances in site-specific irrigation management and grapevine water requirements.)
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Assessment of vineyard water status variability by thermal and multispectral imagery using an unmanned aerial vehicle (UAV). (Special Issue: Advances in site-specific irrigation management and grapevine water requirements.)

机译：使用无人飞行器（UAV）通过热图像和多光谱图像评估葡萄园水状态的可变性。 （特刊：针对特定地点的灌溉管理和葡萄需水量的进步。）

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摘要

The goal of this study was to assess the water status variability of a commercial rain-fed Tempranillo vineyard (Vitis vinifera L.) by thermal and multispectral imagery using an unmanned aerial vehicle (UAV). The relationships between aerial temperatures or indices derived from the imagery and leaf stomatal conductance (gs) and stem water potential ( Psi stem) were determined. Aerial temperature was significantly correlated with gs (R2=0.68, p<0.01) and Psi stem (R2=0.50, p<0.05). Furthermore, the thermal indices derived from aerial imagery were also strongly correlated with Psi stem and gs. Moreover, different spectral indices were related to vineyard water status, although NDVI (normalized difference vegetation index) and TCARI/OSAVI (ratio between transformed chlorophyll absorption in reflectance and optimized soil-adjusted vegetation index) showed the highest coefficient of determination with Psi stem (R2=0.68, p<0.05) and g s (R2=0.84, p<0.05), respectively. While the relationship with thermal imagery and water status parameters could be considered as a short-term response, NDVI and TCARI/OSAVI indices were probably reflecting the result of cumulative water deficits, hence a long-term response. In conclusion, thermal and multispectral imagery using an UAV allowed assessing and mapping spatial variability of water status within the vineyard.
机译：这项研究的目的是使用无人飞行器（UAV）通过热图像和多光谱图像评估商业雨养Tempranillo葡萄园（Vitis vinifera L.）的水状况变化。确定了图像的气温或指数与叶片气孔导度（g s ）和茎水势（Psi stem ）之间的关系。气温与g s （R 2 = 0.68，p <0.01）和Psi stem （R 2 = 0.50，p <0.05）。此外，航空影像的热指数也与Psi stem 和g s 密切相关。此外，尽管NDVI（归一化差异植被指数）和TCARI / OSAVI（反射性中的叶绿素吸收转化率与优化的土壤调整植被指数之间的比率）显示出最高的测定系数，但Psi stem （R 2 = 0.68，p <0.05）和gs（R 2 = 0.84，p <0.05）。虽然可以将与热图像和水状态参数的关系视为短期响应，但NDVI和TCARI / OSAVI指数可能反映了累积缺水的结果，因此是长期响应。总之，使用无人机的热图像和多光谱图像可以评估和绘制葡萄园内水状态的空间变异性。

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