基于无人机热红外遥感的玉米地土壤含水率诊断方法

Diagnosing Method of Soil Moisture Content in Corn Field Based on Thermal Infrared Remote Sensing of UAV

为使热红外遥感诊断土壤含水率更加准确、高效,以不同水分处理的大田玉米为研究对象,借助无人机可见光图像,对热红外图像进行植土分离,并提取玉米冠层温度和地表土壤温度。通过剔除温度直方图两端1%的温度像元对温度信息进行优化,进而计算作物水分胁迫指数(Crop water stress index,CWSI)、冠层相对温差(Canopy relative temperature difference,CRTD)、地表相对温差(Surface relative temperature difference,SRTD),利用三者之和求得水分温度综合指数(Water-temperature composite index,WTCI),并用于诊断不同深度的土壤含水率。结果表明,剔除温度直方图两端1%温度像元的玉米冠层温度与实测冠层温度的相关性更高(4次试验的R2由0.823、0.886、0.899、0.876提高至0.906、0.938、0.944、0.922),剔除温度直方图前端1%温度像元的地表土壤温度与实测地表温度的相关性也更高(2次试验的R2由0.841、0.875提高至0.908、0.925),即通过直方图法优化的温度更接近实测温度;在拔节前期,CWSI、WTCI诊断0~20 cm土壤含水率效果较优,而拔节后期、抽雄吐丝期、乳熟期诊断0~40 cm土壤含水率效果较优;在半覆盖条件下,包含冠层温度信息(CWSI、CRTD)和土壤温度信息(SRTD)的WTCI1与土壤含水率的相关性更高(0~40cm:决定系数为0.500、0.821,高于0.463、0.748);在全覆盖状态下,包含冠层相对温差(CRTD)的WTCI2与土壤含水率的相关性更高(0~40 cm:决定系数为0.809、0.729,高于0.721、0.656),表明WTCI是诊断土壤含水率效果较优的指标。

In order to make the thermal infrared remote sensing diagnosis of soil moisture content more accurate and efficient,different water treatments of field corn were taken as the research object,the plant and soil separation of thermal infrared image was realized by the visible light image of UAV and corn canopy temperature and surface soil temperature were extracted.Optimization of temperature information by eliminating 1%of temperature pixels at both ends of the temperature histogram was made to calculate crop water stress index(CWSI),canopy relative temperature difference(CRTD)and surface relative temperature difference(SRTD).The sum of the above three indices led to a new indicator which can diagnose soil moisture content at different depths.The results showed that there were higher correlation between the corn canopy temperature which eliminated 1%of temperature pixels at both ends of the temperature histogram and the measured canopy temperature(R^2 was increased from 0.823,0.886,0.899 and 0.876 to 0.906,0.938,0.944 and 0.922 of four tests),and there were also higher correlation between the soil temperature which eliminated the 1%temperature pixel at the front of the temperature histogram and the measured soil temperature(R^2 was increased from 0.841 and 0.875 to 0.908 and 0.925 of two tests),which indicated that the temperature optimized by the histogram method was closer to the measured temperature.In the early stage of jointing,CWSI and WTCI had better soil moisture content in the diagnosis of 0~20 cm,while the soil moisture content in the late stage of jointing,tasseling-silking and maturity was better than that of 0~40 cm.Under half coverage,WTCI1 with canopy temperature information(CWSI,CRTD)and soil temperature information(SRTD)was more correlated with soil moisture(0~40cm:R^2 was 0.500 and 0.821,which was higher than 0.463 and 0.748).Under full coverage,WTCI2 with canopy relative temperature difference(CRTD)was more correlated with soil moisture(0~40 cm:R^2 was 0.809 and 0.729,which was higher than 0.721 and 0.656),it indicated that WTCI was a new indicator for better diagnosis of soil moisture content.The research result provided new methods and new ideas for accurate acquisition of crop canopy temperature and accurate diagnosis of soil moisture content.