The Inversion Of Vegetation Parameters By Particle Swarm Optimization Combined With Radioactive Transfer Model

The rapid development of the expressway has brought great economic and social benefits to our country.However,with the development of the expressway,the construction and operation has brought a serious impact on the ecological environment along the line,mainly for the reconstruction of damaged soil structure,vegetation and human biological split with the formation.The abnormal development of the environment for the economy has gradually aroused the attention of scholars in China and began to monitor and evaluate environmental conditions.At present,the new technical solutions is with the advantage of quantitative remote sensing,taking inversion physicochemical parameters by physical models with remote sensing image data as basis,monitoring and evaluating the vegetation environment health with the vegetation environment evaluation system.Firstly,in terms of the disadvantage of the models used now,considering the structure characteristics of coniferous and broad-leaved,taking leafs as uniform stacked infinite layer leaf cells arranged to establish optical characteristics by calculating the optical properties of infinite layer leaf cells and single leaf cell layer and the introduction of the generalized layer optical flat blade model to finish the new leaf model;Secondly,according to the principle of reversibility of light,the surface of the sun direct light direction-direction of reflection and scattering of light-reflecting hemisphere processes into canopy SAIL model of soil reflectance correction and surface heat radiation of the pupil of the impact of radiation and corresponding correction the establishment of the southern hilly area terrain modified SAIL model.Finally,the particle swarm optimization algorithm is introduced for quantitative remote sensing system based on coupling According to the characteristics of the physical model,the search times,the fitness function,especially the inertia weight of the particle swarm optimization algorithm are adjusted and the target factor is extended to retrieve the vegetation parameters.At the same time,according to the principle of "satellite ground synchronization",the vegetation parameters in the experimental area are collected and detected in the satellite transit time.The results show that the particle swarm optimization algorithm combined with the physical model can be used for the inversion of vegetation parameters in remote sensing images.In particular,the vegetation chlorophyll content(SPAD)and the canopy water content inversion results are accurate,and the inversion speed is faster.Particle swarm algorithm with the physical model of a certain amount of remote sensing inversion of vegetation parameters of this proposed can provide basic data support for the monitoring and evaluation of road vegetation environment,reflect the influence of the highway road in the construction and operation in the process of vegetation environment brings to a certain extent.The research results can improve the operational ability of quantitative remote sensing theory in the ecological environment monitoring and evaluation,and lay the foundation for the rapid and quantitative monitoring of vegetation information in the hilly area of the South china.