Digital hemispherical photography (i.e., hemiphoto) is a convenient, rapid tool to estimate two key canopy structure parameters: leaf area index (LAI) and leaf angle distribution (LAD). Underlying such use of hemiphotos is a gap probability model widely known as either the Poisson model or Beer's Law to describe light-vegetation interactions. Based on this gap formula, numerous algorithms have been developed to convert hemiphotos into LAI and LAD. The hemiphoto2LAI package implements a total of 135 LAI estimation models, including the majority of classical algorithms proposed through the past several decades and more importantly a newly proposed binary nonlinear regression algorithm (BNR). The implemented algorithms are adopted to a total of 19 common leaf angle distribution models. Details on the BNR algorithm and the package can be found in Zhao et al. (2019).
|Author||Kaiguang Zhao [aut, cre], Tongxi Hu [aut], Yang Li [aut]|
|Maintainer||Kaiguang Zhao <email@example.com>|
|License||GPL (>= 2)|
|Package repository||View on GitHub|
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