Digital image measurement of the area and anatomical structure of tree rings

Abstract

A microcomputer coupled to a video digitizer was used to develop methods for measuring areas of tree rings and for delineating and measuring microscopic anatomical features. Digitally imaged areas of individual rings of a loblolly pine cross section were within 2.6% of areas measured with a planimeter and were more accurate than areas calculated from radius widths. Various anatomical features were "mapped" within digitized images of consecutive rings, individual rings, and highly magnified parts of the rings of green ash. Fibers within various ring zones, including those known to have formed when trees were flooded, were readily differentiated on the basis of image brightness. The image-determined ratio of lumen to wall material within different groups of fibers was considered a measure of structural comparability. These techniques thus provide a rapid, accurate method to study relationships between tree rings and factors affecting their development. Methods could be improved by increasing both spatial and brightness resolution.

Blue Intensity In Pinus sylvestris Tree Rings: A Manual for A New Palaeoclimate Proxy

“…cell-wall thickness, cell size) and various environmental variables (Mü ller-Stoll 1963;Green 1965). Yanosky and Robinove (1986) coupled a personal computer to a video digitizer to measure or 'map' anatomical features within a digitized image of loblolly pine (Pinus taeda L.). This process permitted the identification of fibres within annual ring boundaries and the corresponding tree-ring structure.…”

“…This process permitted the identification of fibres within annual ring boundaries and the corresponding tree-ring structure. These areas were easily differentiated based on image brightness and the ratio of lumen to cell wall within groups of fibres and was determined to be related to environmental factors (Yanosky and Robinove 1986). However, there are limitations in using this image-analysis method.…”

“…Consequently, the method has not been widely adopted. Sheppard et al (1996) expanded upon the pioneering use of a video digitizer by Yanosky and Robinove (1986) to explore the use of reflectedlight image analysis to measure the brightness of red spruce (Picea rubens (Sarg.)) tree rings to reconstruct temperature.…”

“…However, the method is limited by the need to adjust magnification within cores, which alters the relationship between density and brightness measures. Also, as with the method proposed by Yanosky and Robinove (1986), the image system developed by Sheppard et al (1996) produced low brightness values at the end of cores, requiring a correction. McCarroll et al (2002) avoided the problems of optics by using a flatbed scanner and a regiongrowing algorithm (bespoke software) approach to measure the brightness of multiband images (representing the red, green and blue components).…”

A Quantitative Weathering Study of Wood Surfaces Modified by Chromium VI and Iron III Compounds. Part 2. Image Analysis of Cell Wall Pit Micro-Checking

“…More recently spectroscopic techniques have been used äs a direct means of assessing the chemical degradation of untreated (Anderson et al 1991) and treated wood surfaces (Evans et al 1992) during weathering. Image analysis has been used to quantify wood anatomical features (Gasson 1985;Yanosky and Robinove 1986), wood failure in plywood (McMillin 1981), strain in wood and paper (Choi etal. 1991) and the presence of cavities in soft-rotted wood (Wickens and Murphy 1992), but it has not been used to quantify the deterioration of wood surfaces exposed to natural weathering.…”