Airborne laser scanning (ALS) is increasingly used in the forestry over time, especially in forest inventory process. Great potential of ALS lies in providing quick high precision data acquisition for purposes such as measurements of stand attributes over large forested areas. Models were developed using an area-based approach to predict wood volume, basal area and other forest variables. The solution was performed through developing an object-oriented script using Python programming language, Pandas library, which represents very flexible and powerful data analysis tool in conjunction with interactive computational environment Ipython notebook. Several regression models for estimation of forest inventory attributes were developed.

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