deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Mosig, C, Vajna-Jehle, J, Mahecha, MD, Cheng, Y, Hartmann, H, Montero, D, Junttila, S, Horion, S, Schwenke, MB, Koontz, MJ, Maulud, KNA, Adu-Bredu, S, Al-Halbouni, D, Ali, M, Allen, M, Altman, J, Amorós, L, Angiolini, C, Astrup, R, Awada, H et al (2025) deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics. Remote Sensing of Environment, 332. p. 115027. ISSN 0034-4257

Preview

Text deadtreesearth An openaccess and interactive database for centimeterscale aerial imagery to uncover global tree mortality dynamics.pdf - Published Version Available under License Creative Commons Attribution. Download (6MB) | Preview

Abstract

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.

Item Type:	Article
Uncontrolled Keywords:	Orthophoto; Drone; Tree mortality; Remote sensing; Database; Citizen science; Forests; Open-access; 0406 Physical Geography and Environmental Geoscience; 0909 Geomatic Engineering; Geological & Geomatics Engineering; 37 Earth sciences
Subjects:	G Geography. Anthropology. Recreation > GE Environmental Sciences S Agriculture > SD Forestry T Technology > T Technology (General)
Divisions:	Biological and Environmental Sciences (from Sep 19)
Publisher:	Elsevier
Date of acceptance:	12 September 2025
Date of first compliant Open Access:	28 October 2025
Date Deposited:	28 Oct 2025 15:52
Last Modified:	28 Oct 2025 16:00
DOI or ID number:	10.1016/j.rse.2025.115027
URI:	https://researchonline.ljmu.ac.uk/id/eprint/27437

View Item