Study On Fraction Of Photosynthetically Active Radiation Of Maize In Midwest Of Jilin Province

Fraction of Photosynthetically Active Radiation(FPAR)is important vegetation physiological parameters.As an effective cofactor of vegetation growth monitoring,plays an important role in the photosynthesis of green vegetation.It not only reflects the energy conversion rate between solar energy and biomass,but also represents the ability of vegetation to absorb photosynthetic effective radiation.The estimation of maize canopy FPAR is very important for the study of maize productivity and yield model.This article taken the Midwest of Jilin province as the whole study area,based on the remote sensing inversion method estimated the FPAR of maize canopy,the variation rules of maize canopy FPAR in different in different regions were explored,and the relationship between maize canopy FPAR of different resolutions in the same region was studied.The influencing factors of FPAR size were analyzed,and FPAR data of different resolutions were used to estimate maize yield.3 m resolution PL satellite images was utilized to extract four kinds of vegetation index,the function relationship between four kinds of vegetation and the measured FPAR were set up.The results showed that in the four kinds of vegetation index,there was a strong correlation between soil adjusted vegetation index(SAVI)and measured FPAR and the fitting correlation coefficient was 0.665,Based on the FPAR estimation model of NDVI linear stretching method,the fitting correlation coefficient between the estimated results and the measured FPAR data was 0.701.indicating that the FPAR estimation model of NDVI linear stretching method was superior to the statistical linear relation model of four kinds of vegetation index.Based on FPAR estimation model of NDVI linear stretching method,the FPAR data of maize in each growth period of insurance plot in Dehui city with 3m resolution were estimated,the FPAR data of three maize growth periods in Dehui city with 16 m resolution were estimated.The FPAR data of maize growth periods in Midwest of Jilin province with 300 m resolution were obtained.FPAR image data of tasseling stage and milk maturation stage with 16 m resolution were calculated by combining FPRA data with 3m resolution and GEOV1/FPAR data product with 300 m resolution.Analysis the change trend of FPAR in maize growth periods.The mutual verification of FPAR data with different resolutions in the same region,The validation results showed that the FPAR estimation results under different resolutions in the same region showed a certain consistency in space.The effects of average temperature,cumulative temperature,cumulative precipitation and cumulative solar radiation on FPAR of maize canopy during different growth periods were analyzed.The results showed it is not that the higher the temperature,the smaller the precipitation and the greater the solar radiation,the larger the FPAR of maize canopy.A functional relationship was established between the proportion of residential land and water in the mixed pixels and the FPAR of the pixel.The results showed that the proportion of residential land and water in the mixed pixels were negatively correlated with the FPAR of the pixel.Based on light energy utilization model,FPAR data with different resolutions were used to estimate maize yield.Estimation results showed that there was a certain correlation between corn yield estimation results at different resolutions in the same region.Combined with the measured yield data of Jilin Midwest the results were verified and the absolute value of relative error between the verification point and the measured point was within 30%,which can satisfy the accuracy requirement of crop yield estimation.