Determination of the corn hotspot diurnal and seasonal change by real scene models

Abstract

The corn hotspot dependence on its structure at various times in one day and various growth periods is investigated in this paper. We simulate the scattering of light in the canopy based on three dimensional corn canopies. Our approach consists of seven processes. Firstly, the biophysical parameters of corn, such as plant height, leaf base height, size of leaf, and shape of leaf, are measured on field, and the statistics of the parameters is gotten based on the measurement. Secondly, the three dimensional structure of single corn is re-built by L-system and the statistics. Thirdly, the real pixel scene is configured according to spatial pattern of corns in pixel, such as planting by row or by random. Fourthly, hotspots are calculated by light interception model under various viewing geometric condition. Fifthly, the correlation of corn structure parameters and diurnal consecutive hotspot is evaluated, and key factors are tried to find. Sixthly, the correlation of corn structure parameters and seasonal consecutive hotspot also is evaluated, and key factors are tried to find. Last, the dependence of the key factors that form seasonal consecutive hotspot on the ones that form diurnal consecutive hotspot is estimated at various growth periods. Our conclusion is about to get key factors of consecutive hotspot. The result will improve our understanding about hotspot satellite Triana data, and help us to use the data effectively.