Automatic detection of forest trees from digital surface models derived by aerial images

Abstract

For the sustainable management of forests, obtaining the spatial information of the tree existence (location, number, height, and crown diameter of trees, etc.) with high accuracy and quickly is very important. In this context, the study aims to detect forest trees automatically through flow analysis applied to a 5 m resolution digital surface model by geospatial analysis. The study was carried out in five sample areas with different physical and topographic characteristics in the Antalya province of Turkey. The method consists of two steps which are identifying tree populations and determining tree peaks by applying flow analysis on the surface model. First, the canopy height model was extracted by applying a morphological filter to the image-based digital surface model. Then, the tree peak points are considered sink points, and these sink points were determined on the inverted surface model by the flow analysis approach which is frequently used in hydrological studies. The results showed that the applied method gives approximately 70% accuracy depending on the terrain conditions. Tree crown diameter, distance between trees, slope of the land, and digital surface model resolution significantly affect the accuracy of the results. It is predicted that this study will be an important guide for decision-makers in the preparation of forest plans.

Keywords

• Forest Inventory
• DEM
• Remote Sensing
• Tree Detection
• GIS

Supporting Institution

Ministry of National Defense, General Directorate of Mapping, Turkey.

Thanks

This work has been supported and funded by Ministry of National Defense, General Directorate of Mapping, Turkey.

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