Estimation of Leaf Area Index Based on Hemispherical Canopy Photography

Leaf area index (LAI) is very important for crop growth monitoring, biomass estimation, and many plant growth simulation models. Direct methods are the most accurate, but they have the disadvantage of being extremely time-consuming and labor-intensive as a consequence making them not be the preferred solutions. Indirect methods mainly include the radiometric method, inclined point quadrats, and hemispherical canopy photography. This paper focuses on the analysis of the principles and characteristics of the three indirect methods and affirms the advantages and development value of hemispheric canopy photography. The probability model is used to verify the feasibility of LAI inversion which is based on hemispheric canopy photography. In this paper, the canopy images of four sample plots on the campus were collected for LAI estimation, and the results were compared with LAI-2200C. Finally, the improvement of hemispherical canopy photography has prospected.