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).
Package details |
|
---|---|
Author | Kaiguang Zhao [aut, cre], Tongxi Hu [aut], Yang Li [aut] |
Maintainer | Kaiguang Zhao <lidar.rs@gmail.com> |
License | GPL (>= 2) |
Version | 0.1 |
URL | https://github.com/zhaokg/hemiphoto2LAI |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.