Interval sampling methods in Zagros forests using GIS

Abstract

In this study, for accuracy and cost an optimal inventory method was examined and introduced to obtain information about Zagros forests, Iran. For this purpose, three distance sampling methods (compound, order distance and random-pairs) in 5 inventory networks (100 m × 100 m, 100 m × 150 m, 100 m × 200 m, 150 m × 150 m, 200 m × 200 m) were implemented in GIS environment, and the related statistical analyses were carried out. Average tree density and canopy cover in hectare with 100% inventory were compared to each other. All the studied methods were implemented in 30 inventory points, and the implementation time of each was recorded. According to the results, the best inventory methods for estimating density and canopy cover were compound 150 m × 150 m and 100 m × 100 m methods, respectively. The minimum amount of product inventory time per second (T), and (E%)2 square percent of inventory error of sampling for the compound 150 m × 150 m method regarding density in hectare was 691.8, and for the compound 100 m × 100 m method regarding canopy of 12,089 ha. It can be concluded that compound method is the best for estimating density and canopy features of the forests area.