Academic Journal
Q1Ecological Informatics
About Ecological Informatics
Ecological Informatics is a scholarly journal published by Elsevier B.V.. SCImago 2025 lists it in Q1, with an SJR of 1.77 and H-index of 101.
Coverage: 2006-2026. Research categories: Applied Mathematics (Q1); Computational Theory and Mathematics (Q1); Computer Science Applications (Q1); Ecological Modeling (Q1); Ecology (Q1); Ecology, Evolution, Behavior and Systematics (Q1); Modeling and Simulation (Q1).
Open-access policies and author information
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Source-backed journal facts
Topics in published research
Species Distribution and Climate Change; Remote Sensing in Agriculture; Land Use and Ecosystem Services; Ecology and Vegetation Dynamics Studies; Wildlife Ecology and Conservation; Remote Sensing and LiDAR Applications.
OpenAlex classifies topics from published works. These topics are not the publisher’s official aims and scope.
Source: OpenAlex source record. Retrieved 2026-10-03. Source record updated 2026-10-02. OpenAlex metrics are different from SCImago metrics and the Clarivate Journal Impact Factor.
Journal Metrics
Quartile, SJR and the listed SCImago H-index use the 2025 imported SCImago dataset. A quartile may vary by subject category. Values without a source or reporting year are unverified historical entries. Verify the current Journal Impact Factor with Clarivate or the publisher before using it.
Aims & Scope
The publisher’s official aims and scope have not yet been verified for this profile. Use the journal website to check subject fit and accepted article types before submitting.
Recent Research Articles
Latest publications matched automatically by ISSN.
A UAV-LiDAR multi-dimensional crown metric system and adaptive extraction methods for mountainous Chinese fir plantations
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Kristopher Nolte, Jan Baumbach, Philip Kollmannsberger, Felix Gregor Sauer et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104031Benchmarking European food recovery systems considering operational efficiency, social outreach, civic engagement, and economic recovery
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2026-11 · DOI: 10.1016/j.ecoinf.2026.104058Vulnerability evolution and interactive feature attributions of vegetation productivity in the Jinsha river dry-hot valley using physics-guided neural networks
Xiong Duan, Yu Yu, Haiying Wang
2026-11 · DOI: 10.1016/j.ecoinf.2026.104042Localizing yellow-bellied marmot burrows in a subalpine environment using remote sensing
Isla Duporge, Katie A. Adler, Stavi R. Tennenbaum, Alex R. Frias et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104053Anatomical landmark detection of giant pandas in the wild with infrared camera traps
Nuo Xu, Yanqi Dong, Jiali Zi, Feixiang Chen et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104022Annual canopy height mapping in Italy from Landsat and multi-source LiDAR for disturbance and recovery monitoring
Yang Su, Nikola Besic, Saverio Francini, Xianglin Zhang et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104036Deep learning-based optical monitoring system on floating platforms: enabling long-term activity monitoring of the finless porpoise in the Nanjing section
Hanke He, Qian Tang, Zongwei Liu, Qiulei Dong et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104050Identifying and prioritizing potential ecological corridors that integrate structural connectivity and efficiency: An integrated framework combining Infomap, the gravity model, and robustness analysis
Huimin Wang, Haifeng Li, Canrui Lin, Qianying Feng et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104041Short- and long-term drivers of post-fire forest recovery in Mediterranean forests
Ana Laura Giambelluca, Txomin Hermosilla, María González-Audícana, Jesús Álvarez-Mozos et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104064Beyond point predictions: Probabilistic algal biomass forecasting for risk-based management via Bayesian additive regression trees
Yong Li, Zhengyu He, Kai Ding, Zufei Xiao et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104038Role of high-resolution phenology and productivity data from Sentinel-2 in prediction of grassland management type
A. Terskaia, R. Oucheikh, J. Peng, J. Oliveira et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104051Symbolic regression for empirically realistic population dynamic time series
Cheyenne N. Jarman, Taal Levi, Mark Novak
2026-11 · DOI: 10.1016/j.ecoinf.2026.103988Does freezing actually “freeze” information over time? Biomass conservation impact on metagenomic profiling of microbial communities from wastewater treating systems
Leandro Di Gloria, Jan Pietro Czellnik, Serena Falcioni, Caterina Senesi et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104047An uncertainty-aware compute continuum architecture for underwater species detection
Michele Ferrari, Joaquin Del Rio Fernandez, Jacopo Aguzzi, Daniele D’Agostino et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104067Acoustic remote sensing with deep learning enables non-invasive estimation of seabird nest density
Francesca Terranova, Lorenzo Todaro, Xavier Forte, Katrin Ludynia et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104017Automated detection, tracking and laser-based sizing of scallops from towed video using deep learning
Christopher J. Jackett, Candice Untiedt, Bec Gorton, Carlie Devine et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104023In-situ integration reveals cyanobacteria-specific residence-time signals that Sentinel-2 NDCI/FAI and Landsat NDVI do not resolve in South Korea's Four Rivers
Eungyu Park, Hyung-Sup Jung, Sungwook Choung, Taeyu Kim et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104014Agroclimatic drivers and suitability niches of major European crops revealed by explainable machine learning
Helder Fraga, Nathalie Guimarães, Sebastian Candiago, Chenyao Yang et al.
2026-11 · DOI: 10.1016/j.ecoinf.2026.104065Reviews
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September 25, 2026 at 7:14 am
September 25, 2026