Abstract: Both leaf area index (LAI) and standard error (SEL) have been used as important structural variables of vegetation. These variables have been used as reference data in the performance of forest management, pest control and quarantine. Several studies have reported retrieval of LAI but few have retrieved the related SEL, another significant index in sustainable forest management. This study proposed a method for the applications of LAI and SEL measured with testers in complex conditions. In the study, pictures of pine forest canopy were taken with a common digital camera. The pictures were used to calculate two forest indicators - leaf coverage (Cover) and leaf coverage standard deviation (Cover SD) - via 2G B characteristic index. The correlation models of LAI-Cover and SEL-Cover SD were constructed, from which LAI and SEL of the pine forest were estimated. The results showed highly significant positive correlations between leaf coverage and LAI, and then between leaf coverage standard deviation and SEL. The analysis showed that it was possible to accurately estimate the indexes of pine forests from the models LAI = 0.1926e ^3.0955cover (R² = 0.613 5) for LAI and (R² = 0.493 5) for SEL. The estimation accuracy reached 0.894 6 and 0.798 5, respectively. It was therefore highly feasible and accurate to estimate LAI and SEL of pine forests using common digital cameras. This gadget does not require much outside light conditions and is very convenient, especially in restricted measurement conditions. The proposed method was suitable for solving inaccuracy measurement issues and saving manpower and material resources. Thus it was concluded that the method should be given high-profile promotion to facilitate a wide application.