| Soil moisture is crucial to the normal growth of crops.Real-time and accurate monitoring of soil moisture provides guarantee for the growth and development of crops under optimal conditions.UAV remote sensing technology has become a common method for monitoring soil moisture due to its advantages of speed and convenience.However,the bidirectional reflectance distribution function of the canopy have a significant impact on the canopy spectral information obtained by UAV remote sensing,which reduces the accuracy of the monitoring soil moisture model.In order to solve this problem,this paper takes the summer maize canopy of the China Institute of Water-Saving Agriculture in Arid Areas as the research object,and uses unmanned The multi-spectral remote sensing images of the corn canopy under different water treatments at multiple times(9:00,11:00,13:00,15:00,17:00)in the test area were obtained by computer,and the spectral information of the corn canopy was obtained through data processing The BRF and DHRF of the corn canopy were calculated,and the DHRF components were divided into hot spot effect components,volume scattering components,and diffuse reflection components through the BRF frequency accumulation curve,and the twoway reflection characteristics of the corn canopy under different water treatments were qualitative analysis and quantitative analysis.The multiple linear regression method was used to establish the estimation model of corn canopy DHRF and volumetric scattering DHRF and soil moisture.Finally,the estimation accuracy of the model was evaluated and the specific impact of corn canopy non-Lambert on the model accuracy results was analyzed.The main research conclusions are as follows:(1)The bidirectional reflectance distribution function of the corn canopy are affected by many factors.The peak of BRF in a specific observation direction caused by hot spot effect and volume scattering is an internal factor,while water stress,observation time,and band dependence are external factors.Observation time,water stress,and band dependence affect the bidirectional reflection characteristics of corn canopy in different ways: different observation time will change the observation range of corn canopy BRF,and then affect the appearance of hot spot effect and volume scattering;water stress will affect The degree of hot spot effect and volume scattering,its BRF peak value and distribution range vary with the degree of water stress,and the degree of difference changes with the observation time;the band dependence will make the performance of hot spot effect and volume scattering different under different bands.(2)During the transmission of sunlight through the corn canopy,the contribution of diffuse reflection,hot spot effect,and volume scattering to the DHRF of the corn canopy is different.The change of the observation time will only affect the total amount of the DHRF of the corn canopy,but not the proportion of its components.big.The hot spot effect BRF is relatively large,but its solid angle distribution is small,and its contribution to DHRF is extremely low;the diffuse reflection component is the main part of the corn canopy DHRF,and the diffuse reflection component accounts for about 60% in the RED band and about 80%in the NIR band,the diffuse reflection component in the NIR band is correlated with the degree of water stress;the volume scattering component accounts for about 40% in the RED band,and about 20% in the NIR band.The size of the volume scattering component in the NIR band determines the non-Lambertian degree of the corn canopy.(3)A UAV multispectral soil moisture estimation model based on volumetric scatter removal is proposed.The estimation accuracy of the soil moisture model established by the DHRF using the multiple linear regression method changes with the observation time,showing a trend of first increasing and then decreasing in a day,which is consistent with the non-Lambert change trend of the corn canopy NIR band.The reason for this change is mainly due to the influence of hot spot effect and volume scattering on the non-Lambert character of corn canopy.At the same time,the impact of water stress change on the volume scattering DHRF component is not linear,resulting in the estimation of soil moisture accuracy using linear regression method.decline.Eliminating the volume scattering component in DHRF helps to improve the accuracy of estimating soil moisture,and reduces the impact of observation time on the accuracy of estimating soil moisture,making it more convenient to estimate soil moisture by UAV remote sensing. |
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