OOIR: Observatory of International Research

Papers

(The H4-Index of Forestry is 14. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-01-01 to 2026-01-01.)

Article	Citations
A new approach to small area estimation: improving forest management unit estimates with advanced preprocessing in a multivariate Fay–Herriot model	155
Drought, wildfire and forest transformation: characterizing trailing edge forests in the eastern Cascade Range, Washington, USA	56
Alternative approaches to forest sector carbon accounting and assessment: a literature review and synthesis	49
Commentary to the paper by Roell, Nord-Larsen et al. ‘Mapping tree species ecograms based on soil pH and soil water availability across Denmark’	34
Scots pine (Pinus sylvestris) and silver birch (Betula pendula) mixed-species growth dynamics in the North York moors	32
Forest practitioners’ requirements for remote sensing-based canopy height, wood-volume, tree species, and disturbance products	32
Impact of coarse woody debris on habitat use of two sympatric rodent species in the temperate Białowieża Forest	22
Management of mushroom resources in Spanish forests: a review	19
Deep learning for forest inventory and planning: a critical review on the remote sensing approaches so far and prospects for further applications	18
Managing harvesting residues: a systematic review of management treatments around the world	18
The impact of natural constraints in linear regression of log transformed response variables	17
Acute and Chronic Oak Decline in urban and forest ecosystems in Southern Italy	15
Effects of Norway spruce shelter density and soil scarification method on mortality and height growth of underplanted European beech, European silver fir and Douglas fir	15
Xylem function and leaf physiology in European beech saplings during and after moderate and severe drought stress	14
A bootstrap-based approach to combine individual-based forest growth models and remotely sensed data	14