Mathematical and Computational Forestry and Natural-Resource Sciences Impact factor 2025

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The latest impact factor of Mathematical and Computational Forestry and Natural-Resource Sciences and all the other Web of Science journals was released on 20th June 2025 by Clarivate. Through this web page, researchers can check the impact factor, total citation, journal quartile, and journal aim & scope.

Mathematical and Computational Forestry and Natural-Resource Sciences: Aim & Scope

Mathematical and Computational Forestry and Natural-Resource Sciences is a Web of Science indexed journal tha publishes research in the area: Forestry (Q3); Applied Mathematics (Q4); Computer Science Applications (Q4); Environmental Engineering (Q4).
The ISSN of this journal is 19467664.

Impact factor of Mathematical and Computational Forestry and Natural-Resource Sciences

Journal Title	Mathematical and Computational Forestry and Natural-Resource Sciences
Impact Factor
SJR	0.2
ISSN	19467664
Quartile	Q3

The Journal Impact Factor is defined as citations to the journal in the JCR year to items published in the previous two years, divided by the total number of scholarly items, also known as citable items, (these comprise articles and reviews) published in the journal in the previous two years.

Impact factor data has a strong influence on the scientific community, affecting decisions on where to publish, whom to promote or hire, the success of grant applications, and even salary bonuses.

Only journals listed in the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) receive an Impact Factor.

Similiar journals to publish

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Mathematical and Computational Forestry and Natural-Resource Sciences

ISSN: 19467664
Journal Impact:
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About SCI

SCI is a multidisciplinary citation index. Science Citation Index covers 9,000+ journals across 177 scientific disciplines. SCI was established in 1900 to the current. SCI-indexed journals are indexed by SCI and SSCI. SCI is described as the world's leading journal.

All journals covered in this database are reviewed for sufficiently high quality each year.

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