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Mathematical and Computational Forestry and Natural-Resource Sciences - Contemporary Journal Concept Press | 2024 Cite Score:0.8 | Q4

Mathematical and Computational Forestry and Natural-Resource Sciences Journal With Cite Score

Cite Score and Journal Rank of Mathematical and Computational Forestry and Natural-Resource Sciences

  • About: Mathematical and Computational Forestry and Natural-Resource Sciences Journal is a peer-reviewed academic journal dedicated to the application of mathematical and computational methods in the fields of forestry and natural resource management. It provides a platform for researchers to share their latest findings and advancements in modeling, analysis, and decision-making related to natural resources.
  • Objective: The primary objective of the Mathematical and Computational Forestry and Natural-Resource Sciences Journal is to advance the application of mathematical and computational techniques to solve problems and optimize decision-making in forestry and natural resource management. The journal covers a wide range of topics including forest modeling, resource optimization, environmental impact assessment, spatial analysis, and decision support systems. It aims to foster the development of innovative methodologies and tools that improve the management and conservation of natural resources.
  • Interdisciplinary Approach: The journal adopts an interdisciplinary approach by integrating research from fields such as applied mathematics, computer science, environmental science, ecology, and forestry. This approach enables the journal to address complex problems related to natural resource management that require a combination of mathematical modeling, computational analysis, and ecological understanding. Contributions that explore the integration of these disciplines and provide novel solutions to resource management challenges are highly encouraged.
  • Impact and Significance: The Mathematical and Computational Forestry and Natural-Resource Sciences Journal has a significant impact on both the academic community and natural resource management practices. The research published in the journal contributes to the advancement of new mathematical models, computational tools, and decision support systems that enhance the management and conservation of forestry and natural resources. The journal serves as a valuable resource for researchers, policymakers, and practitioners seeking to apply advanced techniques to real-world challenges in these fields.

  • Editor-in-Chief:  Prof. Aaron Weiskittel

  • Scope: The Mathematical and Computational Forestry and Natural-Resource Sciences journal focuses on the application of mathematical and computational methods to problems in forestry and natural resource management. The journal covers a range of topics where quantitative techniques are applied to improve the understanding and management of natural resources. Key areas include:
  • 1. Forest Modeling: Development and application of mathematical models to simulate and predict forest dynamics, growth, and productivity.
  • Wildlife Management: Computational techniques for modeling wildlife populations, habitats, and interactions, including conservation and management strategies.
  • Natural Resource Management: Application of mathematical and computational methods to the management of natural resources such as water, soil, and minerals.
  • Ecological Modeling: Research on mathematical models that describe ecological processes, including ecosystem dynamics, species interactions, and environmental impacts.
  • Spatial Analysis and GIS: Use of geographic information systems (GIS) and spatial analysis techniques to manage and analyze spatial data related to forestry and natural resources.
  • Remote Sensing: Techniques and applications of remote sensing data for monitoring and assessing natural resources and environmental changes.
  • Optimization in Resource Management: Development of optimization models for resource allocation, land use planning, and management strategies.
  • Climate Change Impacts: Modeling and analysis of the effects of climate change on forests, ecosystems, and natural resources.
  • Decision Support Systems: Development of computational tools and decision support systems to aid in the management and policy-making for natural resources.
  • Statistical Methods and Data Analysis: Application of statistical methods to analyze data related to forestry and natural resource management, including predictive modeling and uncertainty analysis.
  • Simulation and Forecasting: Use of simulation techniques to forecast future scenarios and impacts related to forestry and natural resources.
  • Latest Research Topics for PhD in Computer Science

  • Print ISSN:  19467664

    Electronic ISSN:  

  • Abstracting and Indexing:  Scopus, Science Citation Index Expanded

  • Imapct Factor :  

  • Subject Area and Category:   Agricultural and Biological Sciences, Forestry, Computer Science, Computer Science Applications, Environmental Science, Environmental Engineering, Mathematics, Applied Mathematics

  • Publication Frequency:  

  • H Index:  14

  • Best Quartile:

    Q1:  

    Q2:  

    Q3:  

    Q4:  Forestry

  • Cite Score:  0.8

  • SNIP:  0.254

  • Journal Rank(SJR):  0.160