UruDendro, a public dataset of 64 cross-section images and manual annual ring delineations of Pinus taeda L.

The automatic detection of tree-ring boundaries and other anatomical features using image analysis has progressed substantially over the past decade with advances in machine learning and imagery technology, as well as increasing demands from the dendrochronology community. This paper presents a publicly available database of 64 scanned images of transverse sections of commercially grown Pinus taeda trees from northern Uruguay, ranging from 17 to 24 years old. The collection contains several challenging features for automatic ring detection, including illumination and surface preparation variation, fungal infection (blue stains), knot formation, missing cortex or interruptions in outer rings, and radial cracking. This dataset can be used to develop and test automatic tree ring detection algorithms. The dataset was used to develop the Cross-Section Tree-Ring Detection (CS-TRD) method. Dataset Article published in ANFS. Method Image and annotations can be inspected using the TRAS tool developed during the project. 1) Open TRAS 2) Open Image 3) File>Load Annotations