基于无人机热红外图像的核桃园土壤水分预测模型建立与应用

Establishment and application of prediction model of soil water in walnut orchard based on unmanned aerial vehicle thermal infrared imagery

为了解北方核桃园区的土壤水分状况,实现优化水资源配置的目的。该文于2016和2017年采用固定式热红外成像仪(A310 f)连续观测得到核桃主要生长季节午后(13:00和14:00)的冠层温度,并同步观测温度、湿度、辐射、风速、降雨量和0~80 cm不同土层深度的土壤体积含水量。并于2017年8月11日利用无人机热成像系统(TC640)对连续灌溉区域和干旱胁迫区域进行了图像采集。结果表明,40~60 cm土层深度可能是核桃树主要吸收水分的区域。冠层温度普遍高于空气温度,其变化范围在0~5℃之间,冠气温差与土壤含水量呈负相关,与太阳辐射呈正向关系,其中,土壤含水量的贡献值达到了75%。利用2017年13:00时的冠层与空气温差数据来建立的土壤水分预测模型,R2=0.64;同时,利用14:00时的实测数据对所建立模型进行验证,R2=0.61,表明该模型具有一定的拟合精度。最后,将模型用于诊断核桃区域水分状况,证明了其具有较好的实际应用效果。该研究首次将固定式热成像设备与无人机热成像系统相结合来研究树木的冠层温度,并成功实现了从理论模型到实际应用,从单株水平到区域尺度的转换。

Studying the soil water status of the walnut orchard and conducting reasonable irrigation play an important role in relieving the pressure of irrigation water in arid or semi-arid areas.With the development of thermal imaging technology,thermal image is a viable alternative to point measurements,since it offers the possibility of rapidly measuring a large number of plants and integrating plant temperatures over entire fields and producing a map of the plant water status distribution in the field.In this study,the canopy temperature of walnut tree was continuously observed with thermal infrared instrument(A310 f)at 13:00 and 14:00 per day in the main growing season of 2016 and 2017,and meteorological factors(air temperature,air humidity,solar radiation,wind speed,and precipitation)and the soil water content in 0-80 cm depth were observed from May 2016 to September 2017.On August 11th,2017,thermal image acquisition was carried out using unmanned aerial vehicle’s thermal imaging system(TC640)in the continuous irrigation area and drought area.The results showed that 40-60 cm soil layers may be the main areas where walnut roots absorb water.In general,when canopy temperatures reach the highest in the afternoon(13:00 and 14:00),canopy temperature will be higher than air temperature and the range of variation is 0-5℃.In sunny weather conditions in 2016 and 2017,multiple regression analysis was performed based on canopy-air temperature difference,solar radiation,wind speed,vapor pressure deficit(VPD)and relative water content(RWC)in 40-60 cm depth.Coefficients of determination in 2 fitting equations were 0.57 and 0.69 respectively.The canopy-air temperature difference was negatively correlated with the soil water content,but positively correlated with the solar radiation,and the contribution of soil water content reached 75%,which was higher than the solar radiation through principal component analysis.The soil water prediction model was established using the data of canopy-air temperature difference and soil water content at 13:00 in 2017,with the coefficient of determination of 0.64.At the same time,the measured data at 14:00 were used to verify the model established,and the coefficient of determination was 0.61,indicating that the model had a certain accuracy degree of fitting.Finally,the soil water model was used to diagnose 2 different water conditions of walnut areas,which proved that it had a good practical application effect.The range of RWC change in the continuous irrigation area was 0.5-0.6,while the range of variation for RWC in the drought stress area was 0.41-0.5.For the 3 sample trees in the continuous irrigation area,RWC values from the simulation were 0.57,0.53 and 0.55,and measured values were 0.62,0.57 and 0.52,respectively.For the 3 sample trees in the continuous drought area,RWC values from the simulation were 0.49,0.44 and 0.42,and measured values were 0.44,0.42 and 0.39,respectively.This study combines the fixed thermal imaging equipment with the thermal imaging system of unmanned aerial vehicle to study the canopy temperature of walnut trees,and successfully achieves the conversion from the theoretical model to the practical application and the extension from the individual level to the regional scale.Finally,the constructed soil water model will provide a basis for scientific water resources allocation in walnut orchards of the northern China.