GIS based methods for computing the mean extraction distance and its correction factors in Romanian mountain forests

Extraction distance is an important factor used for locating new forest roads. Correction factors should be used for adapting theoretical modelsto real life situations.The aim of thisstudy wasto show how extraction distance and the correction factors can be computed and used for assessing forestroad optionsin a more efficient and effective manner using process automation in GIS. The study was located in a mountain forest in the South Central Carpathians of Romania. For determining the mean extraction distance, 71.5 km ofskid trails were tracked in the field and mapped in GIS. Four computing methods were defined: raster method, grid point method, buffer strips method and centre of gravity method. For testing and validating the methods, four infrastructure scenarios were defined: one was describing the existing forest infrastructure and three otherswere proposing newroad options. Statistical analyseswere performed fortesting the accuracy and the possible differences between methods.The paired samplest-testsrevealed significant differences between scenarios proposing new forest roads and the current infrastructure conditions. The raster method, the grid point method and the buffer strip method reported high accuracy for computing the mean extraction distance. This study reported an extraction correction factor (ks) value of 1.50 and a total correction factor(kt) value of 3.40 which can be used forrough calculationsin practice. The automation models developed in GIS improved the efficiency of computations.The correction factors determined in thisstudywere comparablewith those reported in literature, highlighting the reliability of the analysed methods.