An Efficient Method for Extracting Forest Canopy Density from Fisheye Photos

Canopy density index is not only the important factor of determining forest management, but also one of the main technical parameters measuring forest management level. A method of extracting forest canopy density from the fisheye photos by using PhotoShop, ArcGIS software was studied, and the forest canopy density could be calculated through photo tailoring, greyness processing and image reclassifying. The values of forest canopy density obtained by this method were verified by comparing with the results of KMean unsupervised classification method and the field observation values. The results showed that when the average value of the forest canopy density calculated by this method was 056, the corresponding field observation value was 062, and that of obtained by the unsupervised classification method was 0.65. The differences between any of the two values were less than the permissible error range of 010, indicating that the new method was efficient and practicable.