Research On Utilization Of Maximum Light Energy In Henan Province Based On Vegetation Photosynthetic Model

With remote sensing products getting more convenient and remote sensing models becoming more perfect,simulation of vegetation growth based on remote sensing ground reflectance products has become a trend in carbon cycle.Study on the utilization of vegetation light energy has important reference value for the study of the spatial-temporal evolution of carbon cycle and carbon accumulation.Study of vegetation carbon cycle and carbon accumulation at the smaller regional scale mostly uses research methods based on measured data from ground stations.The other hand,the site survey methods for vegetation growth on a large regional scale are difficult due to the large amount of information and data acquisition.The use of remote sensing models to obtain accurate,real-time reflectivity numbers of remote sensing products to extract information on vegetation growth is of great significance for the study of regional carbon cycle and carbon accumulation.Remote sensing estimation of medium and high spatial resolution remote sensing data products has become an important method for studying vegetation growth status.As a key parameter in the light energy utilization model,the estimation of the maximum light energy utilization has important reference value for the inversion of vegetation growth status.The traditional light energy utilization model ignores the difference between different vegetation types and sets the maximum light energy utilization to a fixed value.The maximum light energy utilization rate not only differs among different vegetation types,but also has the difference in time and space distribution of the maximum light energy utilization rate of the same planting type.Its value is extremely sensitive to the estimation result of the model,and it needs to consider the influence of environmental impact factors,spatial and temporal distribution differences,vegetation types and other factors.The utilization of light energy of vegetation has relatively intuitive reflection on the accumulation of vegetation dry matter energy and vegetation growth.Based on the basic principle of light energy utilization model,this paper uses Henan Province as the study area,combines the most commonly used remote sensing estimation model CASA model and the regression model of vegetation index and net primary productivity,and uses the MODIS data of medium resolution imaging spectrometer to study photosynthetic efficiency.Spatial-temporal evolution properties of intermediate parameters of radiation,stress factors,net primary productivity,and maximum light energy utilization rate,taking the distribution of vegetation zones as the research object on the time scale from 2001 to 2015,using spatial analysis methods and statistical methods in GIS The temporal and spatial distribution of the maximum light energy utilization of different vegetation cover was analyzed.The main research contents and research conclusions include:?1?Estimation of photo synthetically active radiation actually absorbed by vegetation.The requirement for APAR values is to first calculate the ratio of photo synthetically active radiation absorption?FPAR?and total solar radiation?SOL?.The estimation of FPAR introduces SR,and the FPAR is estimated based on the respective weights of SR and NDVI.The study found that there are two high-value areas in the spatial distribution of APAR,one is the mountainous forest land in the west,and the other high-value area is the farmland vegetation type in the eastern plain of Henna Province,and the area of higher value has been expanded from 2001 to 2015.The order of APAR values for different vegetation types was farmland>woodland>paddy field>grassland,and the APA values of grassland and paddy field vegetation types were the closest.Estimation of net primary productivity NPP.Using the vegetation index to invert the net primary productivity NPP,combined with the relationship between NPP,APAR,and light energy utilization in the CASA model,the utilization of different vegetation light energy was obtained.The study found that NPP of different vegetation types showed an increasing trend and increased significantly,and there was a large difference in net primary productivity of different vegetation types and the seasonal differences were significant.?2?Net primary productivity estimates.Using the relationship between NDVI and net primary productivity,we obtain the NPP,and combine the functional relationship between NPP,APAR and LUE to obtain different vegetation LUE.The study found that NPP showed a significant increase trend,and there was a significant difference in seasonal distribution.?3?Maximum light energy utilization estimate.The calculation result LUE introduces the environmental stress drivers and combines the vegetation photosynthetic model VPM to estimate?_max.The stress-recovery factor in environmental stress factors was obtained from MODIS data ground reflectance data obtained by the number LSWI.The temporal and spatial distributions of APAR,NPP,and?_maxax in forest lands,grasslands,dry lands,and paddy fields and the seasonal distribution were analyzed.It can be found that the light,effective radiation,stress factors,and net primary productivity of upland vegetation are significantly higher than those of other types of vegetation on the inter-annual time scale.Except for the obvious inter-annual fluctuations in farmland vegetation types that are sensitive to human activities,the inter-annual variations of other vegetation types are relatively flat,with peaks at the moon phases from April to September.?4?The results of the two methods of?_maxare compared.The?_max research in farmland was calculated using VPM model and agricultural statistics respectively.The comparison between the two methods found that most of Henna Province's county based remote sensing model estimation results were relatively large compared with statistical data.?5??_maxax influence factor analysis.There are significant differences in?_max between woodland,grassland,farmland and paddy fields.The role of human activities is more significant,and the?_maxax of the dry fields fluctuates significantly from year to year,compared with the gradual change of the?_maxax of other types of vegetation.In2013,the area of several major vegetation types decreased compared with 2000,and most of them were converted to other types of land.However,the dry land area always occupied the vast majority of the total;in addition,vegetation index,topographic factor,latitude and longitude,and?_maxax were correlated to find vegetation.The correlation between the index and?_maxax is the best,while the correlation between?_maxax and terrain factors is poor.