无人机热成像技术在葡萄园水状态自动化中的应用

S. Shakya
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引用次数: 10

摘要

热成像技术由于其在估算冠层表面温度和预测作物水位方面的效率而被用作农业作物水分管理的技术。随着热成像系统重量的减轻和分辨率的提高,热成像被认为是农业和土木工程用途的无人机(UAV)的有益集成。在现场实施时,该技术能够解决许多困难,包括在考虑官方诱导的变化或自然存在的水位的同时,估计农场或田地中的植物水分。该项目旨在利用高分辨率热成像技术确定葡萄园的含水量。这项研究工作开发了一种无人驾驶飞行器(UAV),专门用于显示高分辨率图像。这种方法将能够在晴天利用热成像系统生成作物水分胁迫指数(CWSI)。将测量值与沿葡萄园的气孔导度(sg)和茎水分势(s)进行比较。为了评估所提出的工作的性能,使用了特殊的建模方法来确定水位变化的模式。结果表明,“sg”和“s”值与CWSI值具有良好的相关性,具有监测水位瞬时变化的潜力。然而,根据水势的季节变化,发现记录的热像与水势的季节变化并不对应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unmanned Aerial Vehicle with Thermal Imaging for Automating Water Status in Vineyard
Thermal imaging is utilized as a technique in agricultural crop water management due to its efficiency in estimating canopy surface temperature and the ability to predict crop water levels. Thermal imaging was considered as a beneficial integration in Unmanned Aerial Vehicle (UAV) for agricultural and civil engineering purposes with the reduced weight of thermal imaging systems and increased resolution. When implemented on-site, this technique was able to address a number of difficulties, including estimation of water in the plant in farms or fields, while considering officially induced variability or naturally existing water level. The proposed effort aims to determine the amount of water content in a vineyard using the high-resolution thermal imaging. This research work has developed an unmanned aerial vehicle (UAV) that is particularly intended to display high-resolution images. This approach will be able to generate crop water stress index (CWSI) by utilizing a thermal imaging system on a clear-sky day. The measured values were compared to the estimated stomatal conductance (sg) and stem water (s) potential along the Vineyard at the same time. To evaluate the performance of the proposed work, special modelling approach was used to identify the pattern of variation in water level. Based on the observation, it was concluded that both ‘sg’ and ‘s’ value have correlated well with the CWSI value by indicating a great potential to monitor instantaneous changes in water level. However, based on seasonal changes in water status, it was discovered that the recorded thermal images did not correspond to seasonal variations in water status.
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