Abstract
Abstract Stem maps describing the spatial location of trees sampled in a forest inventory are used increasingly to model relationships between neighboring trees in distance-dependent growth and yield models, as well as in stand visualization software. Current techniques and equipment available to acquire tree spatial locations prohibit widespread application because they are time-consuming, costly, and prone to measurement error. In this report, we present a technique to derive stem maps from a series of digital photographs processed to form a seamless 360° panorama plot image. Processes are described to derive distance from plot center and azimuth to each plot tree. The technique was tested on 46 field plots (1,398 sample trees) under a range of forest conditions and compared with traditional methods. Average absolute distance error was 0.38 ± 0.44 m, and average absolute azimuth error was 2.3 ± 2.5°. Computed average horizontal accuracy was 0.40 ± 0.42 m, with 85% of measured trees being within 0.5 m of the field-measured tree location.
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