Local Maximum Filtering for the Extraction of Tree Locations and Basal Area from High Spatial Resolution Imagery

In this study we investigate the use of local maximum (LM) filtering to locate trees on high spatial resolution (1-m) imagery. Results are considered in terms of commission error (falsely indicated trees) and omission error (missed trees). Tree isolation accuracy is also considered as a function of tree crown size. The success of LM filtering in locating trees depends on the size and distribution of trees in relation to the image spatial resolution. A static-sized 3×3 pixel LM filter provides an indication of the maximum number of trees that may be found in the imagery, yet high errors of commission reduce the integrity of the results. Variable window-size techniques may be applied to reduce both the errors of commission and omission, especially for larger trees. The distribution of the error by tree size is important since the large trees account for a greater proportion of the stand basal area than the smaller trees. An investigation of the success of tree identification by tree crown radius demonstrates the relationship between image spatial resolution and LM filtering success. At an image spatial resolution of 1 m, a tree crown radius of 1.5 m appears to be the minimum size for reliable identification of tree locations using LM filtering.