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精确灌溉对无损、快速的水分监测技术有迫切需求。研究棉花冠层高光谱参数与水分的定量关系并建立水分估测模型,以实现棉花水分及时、准确监测。通过2年试验,测定棉花冠层高光谱及植株水分,根据光谱参数与植株含水量的相关关系,建立了植株含水量监测模型。结果表明:棉株含水量与叶片含水量在一定范围内随灌溉量增减而增减,并能区分棉花干旱程度;棉株及叶片含水量与冠层460～514 nm、605～698 nm、1451～1576 nm和1960～2457 nm反射率极显著负相关,与727～1345 nm反射率极显著正相关,且棉株的相关性好于叶片含水量。所选作物水分指数、归一化差值水分指数1、归一化差值水分指数2、水分胁迫指数1、水分胁迫指数2、水分波段指数、水分指数与归一化差值植被指数之比均与棉株及叶片含水量极显著相关;构建了棉株含水量和叶片含水量的最佳监测模型;所建模型精度能满足大田生产对棉花水分监测的要求。
Accurate irrigation has an urgent need for non-destructive, rapid moisture monitoring techniques. The quantitative relationship between the canopy hyperspectral parameters and water content was studied, and the moisture estimation model was established to realize the timely and accurate monitoring of cotton moisture content. After two years of experiment, the canopy hyperspectral and plant water content were determined. According to the correlation between spectral parameters and plant water content, the water content monitoring model was established. The results showed that the moisture content and the leaf water content of cotton plants increased and decreased with the increase or decrease of irrigation volume within a certain range, and could distinguish the degree of cotton drought. The water content of cotton plants and leaves were in the range of 460-549 nm, 605-698 nm, There was a significant negative correlation between the reflectance of 1451 ~ 1576 nm and 1960 ~ 2457 nm, and a significant positive correlation with the reflectance of 727 ~ 1345 nm. The correlation between the two strains was better than the leaf water content. The selected crop moisture index, normalized difference water index 1, normalized difference water index 2, water stress index 1, water stress index 2, water band index, water index and normalized difference vegetation index ratio Which were significantly correlated with the moisture content of cotton plants and leaves. The optimal monitoring model for the moisture content and leaf water content of cotton plants was established. The accuracy of the model could meet the requirement of cotton field moisture monitoring.