An assessment of the statistical performance of the horizontal point sampling (HPS) in an open coppice forest

Abstract

Abstract Sampling surveys are broadly employed in forest inventories due to their efficiency in evaluating forest characteristics. However, the selection of an appropriate sampling method is essential. This study introduces a novel application of horizontal point sampling (HPS) in a coppice forest. The study evaluates the statistical characteristics of the horizontal point sampling (HPS) method when used in conjunction with crown relascope (CR). It further examines the variations in the crown basal area factor (CBAF) and the impact of different sample sizes (n). The study also conducts a comparative analysis between horizontal point sampling and fixed-radius (FR) plot sampling methods. This study was conducted in an open coppice forest. To achieve this, a sampling simulation with a large number of repetitions was employed. In HPS, a greater CBAF for a given sample size leads to a higher relative coefficient variation (CV %). Multiple regression model shows that both sample size (n) and CBAF influence CV %. There is an inverse relationship between n and CV%, whereas a positive relationship exists between CBAF and CV%. A combination of HPS and CR is easily applicable in fieldwork. This combined method demonstrates enhanced efficiency when compared to the traditional FR for estimating some forest attributes in CFs.