DETERMINING MORPHOMETRIC PROPERTIES OF RADIATA PINE USING LONG WAVE INFRARED SENSING AND BIOLOGICALLY-INSPIRED VISION

Abstract

Abstract. A miniaturised, high resolution visible and long wave infrared (LWIR) sensor was carried onboard an unmanned aerial vehicle to observe sections of radiata pine forests. The raw irradiance measurements were temporally pre-processed using a biologically-inspired vision (BIV) model to allow information within and across the images to be normalised. This permitted a larger, denser, and more tailored set of key points within the 2D image stacks to be corresponded, thereby improving 3D reconstructions of individual trees derived using structure from motion (SfM). The BIV model comprises multiple layers of processing derived from measured or assumed responses of the photoreceptor cells in the hoverfly. Its pre-processing expands the range of input signal obtained from the LWIR sensor and enhances foreground-background contrast. Morphological image processing techniques were also applied to enhance key image features before structure from motion is applied. The result allows structural properties of individual trees to be characterised in terms of their potential volume and quality; and contrasted with the point clouds obtained from the visible imagery that only depicts the tree canopies.