多功能林业的规划与分析

Q4 Agricultural and Biological Sciences
H. Korjus, A. Kiviste, M. Hordo
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引用次数: 0

摘要

新的国际研究项目“多功能林业规划与分析”于2022年秋季在爱沙尼亚生命科学大学启动,共有五名外国学生参加。该学习计划的目的是培养在森林和自然资源管理方面具有深厚知识的专家,使他们能够在国际组织,林业企业和政府机构工作。毕业生将掌握林业决策的技能和知识,使用不同的方法、模型和工具来分析可能的情景,并在战略、战术和操作层面上制定情景。森林经营不断受到环境、社会需求和市场条件变化的影响。预测森林动态和模拟可能的管理活动的新工具的需要得到许多新技术的支持,例如自动数据收集、遥感、现代分析方法等。人工智能与虚拟现实相结合是解决森林管理中复杂问题的一种很有前景的决策支持方法。这些技术如今已广泛应用,自20世纪中叶以来已在不同领域得到应用。然而,这些技术在林业中的应用是相当新的。人工智能已经在三维点云数据应用的森林建模和统计森林数据分析中得到了应用,但在林业的其他领域和问题上还没有得到广泛的应用。定量方法在林业规划和分析中占主导地位。随着Artur Nilson(1931-2022)于1969年被聘为森林管理规划教授,应用数学和计算的新趋势进入爱沙尼亚林业。几十年来,阿图尔·尼尔森一直在推广数学方法在林业和计算机辅助方法中的应用。他关于决策支持、现代林业和虚拟林业的思想具有创新性和新颖性,其中许多在未来仍将得到应用。我们,他的学生和同事,怀念他对森林研究问题的热情和理性的看法,并试图在研究和教育中实施他的想法和方法。以证据为基础的森林管理也在更深入地研究为精确林业方法做准备的细节。在许多应用中,放大和缩小是一项具有挑战性的任务,并导致对不同层次生态系统过程的更深刻理解。在树木年代学和树木生长生理学方面的新进展不断改进我们的建模工具,以及提高对生态系统功能、森林结构特征和管理影响的认识,将使森林生态系统更好地提供商品和服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Planning and analysis in multifunctional forestry
The new international study programme “Planning and analysis in multifunctional forestry” started at the Estonian University of Life Sciences with five foreign students in autumn 2022. The aim of the study programme is to prepare specialists with deep knowledge in the management of forest and nature resources which enable them to work in international organisations, forest enterprises, and government agencies. The graduates will have skills and knowledge on decision-making in forestry using different methods, models and tools to analyse possible scenarios and make scenarios at strategic, tactical and operational levels. Forest management is constantly under the impact of changing conditions in the environment, society demands and markets. The need for new tools to predict forest dynamics and to simulate possible management activities is supported by many new technologies, e.g. automatic data collection, remote sensing, modern analysis methods, etc. Artificial intelligence combined with virtual reality seems a very promising decision support for complex questions in forest management. These technologies are widely available nowadays, and have been used in different fields since the middle of the 20th century. However, the use of these technologies in forestry is quite new. Artificial intelligence is already applied in forest modelling with 3D point cloud data applications and in statistical forest data analysis, but it is not yet used that often in other fields and issues of forestry. Quantitative methods are dominating in forestry planning and analysis. New trends of applying mathematics and computing arrived in Estonian forestry with Artur Nilson (1931–2022) when he was employed as Professor of forest management planning in 1969. Artur Nilson was promoting the use of mathematical methods in forestry and computer-aided approaches for many decades. His ideas about decision support, modern and virtual forestry are innovative and novel, many of which will still be applied in the future. We, his students and colleagues, miss his enthusiastic and rational view to forest research questions and try to implement his ideas and approaches in research and education. Evidence-based forest management is also looking deeper into the details of preparing for the approach of precision forestry. Scaling up and down is a challenging task in many applications and leads to a more profound understanding of ecosystem processes at different levels. New advances in dendrochronology and in understanding tree growth physiology are constantly improving our modelling tools, as well as improving knowledge on ecosystem functioning, forest structural traits and management impacts will enable better provision of goods and services from forest ecosystems.
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来源期刊
Forestry Studies
Forestry Studies Agricultural and Biological Sciences-Forestry
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