Journal Information

Ecological Informatics

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Impact Factor:
7.3
Publisher:
Elsevier
ISSN:
1574-9541
Viewed:
19198
Tracked:
2

Call For Papers

Ecological Informatics is an academic journal published by Elsevier. (ISSN 1574-9541, impact factor 7.3).

An International Journal on Computational Ecology and Ecological Data Science The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science, biogeography, and ecosystem analysis. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable ecosystem management in view of global environmental and climate change. The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling of ecological data, and uncertainty analysis. The journal invites papers on: novel concepts and tools for monitoring, acquisition, management, analysis, and synthesis of ecological data, innovative strategies and applications of eco-acoustics, eco-genomics, digital image processing, machine and deep learning, Bayesian inference and uncertainty analysis techniques, species distribution modelling, understanding and forecasting of ecosystem functioning and evolution, and use of quantitative tools to inform management decisions on environmental issues like ecosystem sustainability, climate change, and biodiversity.
Last updated by Dou Sun in

Special Issues

Special Issue on Data Management and Data Analytics for Sustainable Agriculture Submission Date: 2026-07-16 Agriculture is undergoing a profound transformation, driven by the increasing availability of heterogeneous, dynamic, and huge volumes of data from ground sensors, remote sensing, and autonomous robots. Leveraging these data for sustainable agricultural practices remains a challenge due to issues related to data integration, real-time analytics, scalability, and actionable decision-making. This Special Issue on Data Management and Data Analytics for Sustainable Agriculture, aims to address these challenges by exploring cutting-edge methods for managing and analyzing big data for sustainable agriculture. The aim is to collect contributions that tackle the full data lifecycle in smart agriculture, from data acquisition (e.g., from the Internet of robotic things - IoRT, remote sensing, or autonomous platforms) to scalable storage solutions, efficient data fusion techniques, and advanced analytics. Emphasis will be placed on interdisciplinary approaches that bridge data science and agronomy to enhance productivity, while ensuring environmental sustainability. Attention will be also given to novel machine learning models that integrate domain knowledge, fog-edge-cloud computing frameworks for real-time processing, and federated learning strategies for collaborative data analysis in agricultural networks. This Special Issue aims to highlight state-of-the-art advancements that enable data-driven, smart agriculture and support informed decision-making at different scales, from individual farms to regional food systems. By bringing together contributions from researchers in big data, AI, robotics and agricultural sciences, we seek to foster innovative solutions that contribute to biodiversity and environmental preservation, resource efficiency, climate resilience, green computing, and all other topics that contribute to sustainable agriculture. Guest editors: Dr. Sandro Bimonte TSCF, INRAE, Ferrand, France sandro.bimonte@inrae.fr Dr. Riccardo Bertoglio TSCF, INRAE, Ferrand, France riccardo.bertoglio@inrae.fr Prof. Piotr Skrzypczyński Poznan University of Technology, Poznan, Poland piotr.skrzypczynski@put.poznan.pl Prof. Robert Wrembel Poznan University of Technology, Poznan, Poland robert.wrembel@cs.put.poznan.pl Special issue information: The Journal of Ecological Informatics is calling for submissions to a special issue on Data Management and Data Analytics for Sustainable Agriculture. As agriculture embraces digital transformation, the integration of big data technologies is becoming essential to enhance sustainability, productivity, and resilience. With the rapid development of IoT sensors, autonomous machinery, and remote sensing technologies, vast amounts of agricultural data are being generated, creating both opportunities and challenges in data management and analysis. We invite researchers to submit papers that explore innovative approaches to managing and analyzing big agricultural data, including topics such as data acquisition from IoRT, real time analytics, scalable storage systems, data fusion techniques, and AI-driven predictive modeling. We seek original research articles, survey papers, and case studies that address innovative datamanagement and analytics strategies promoting sustainable agricultural practices. Topics of interest include, but are not limited to: IoT and robotics-enabled sensor networks for real-time soil, weather, life stock, and crop monitoring Data fusion techniques for combining heterogeneous agricultural data sources (e.g., UAVs, satellites, field sensors) Standardization and interoperability of agricultural data formats and platforms Scalable storage systems and distributed databases for agricultural data New database management systems based on multi-model, multi-modal, and polyglot approaches Data warehouse, data lake, data lakehouse, lambda, data mesh architectures Distributed and edge-fog-cloud computing frameworks for processing big agricultural data Federated learning for collaborative AI in agriculture, ensuring farmer data ownership Machine learning and deep learning approaches for decision support and automation in farming Explainable AI (XAI) techniques to enhance transparency and adoption of AI-driven agricultural solutions Interactive (geo)visualization tools for making complex data accessible to farmers and agronomists Business intelligence methods and systems for sustainable agriculture decision-making Manuscript submission information: When submitting your manuscript please select the article type “VSI: Sustainable Agriculture” at https://www.editorialmanager.com/ecoinf/default.aspx. The submission portal will be open from 15 December 2025 to 16 July 2026. All submissions deemed suitable to be sent for peer review will be reviewed by at least two independent reviewers. Once your manuscript is accepted, it will go into production, and will be simultaneously published in the current regular issue and pulled into the online Special Issue. Articles from this Special Issue will appear in different regular issues of the journal, though they will be clearly marked and branded as Special Issue articles. Keywords: Big Data, Data Management, Data Analytics, AI, Sustainable Agriculture
Last updated by Dou Sun in

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