利用人工智能,机器学习和深度学习来实现可持续的林业管理和保护:变革潜力和未来前景
Taojing Wang1, Yinyue Zuo1, Teja Manda1
1State Key Laboratory of Tree Genetics and Breeding, College of Life Sciences, Nanjing Forestry University, Nanjing 213007, China.
Plants (Basel, Switzerland)
|April 12, 2025
概括
人工智能 (AI),机器学习 (ML) 和深度学习 (DL) 为可持续森林管理 (SFM) 提供了变革性的潜力. 这些技术可以改善森林保护和资源利用,解决关键的生态和经济挑战.
科学领域:
- 林业和环境科学 林业和环境科学
- 生态学中的人工智能
背景情况:
- 森林生态系统提供了重要的生态,环境和经济效益.
- 可持续森林管理 (SFM) 是至关重要的,但在平衡利用和保护方面面临着挑战,气候变化和资源枯竭加剧了这一挑战.
研究的目的:
- 审查人工智能 (AI),机器学习 (ML) 和深度学习 (DL) 在SFM中的变革潜力.
- 总结当前的人工智能应用,局限性和现代化SFM的未来前景.
主要方法:
- 审查当前的研究和技术进步在AI,ML和DL为SFM.
- 分析人工智能在预测分析,建模和森林管理决策支持系统中的应用.
主要成果:
- 人工智能,ML和DL能够准确预测森林动态,包括碳捕获,物种分布和生态系统健康.
- 基于人工智能的决策支持系统集成实时数据,用于适应性森林管理策略.
- 确定了AI在SFM中的局限性,并提出了解决方案.
结论:
- 人工智能,ML和DL在现代化SFM和应对当前挑战方面具有巨大的潜力.
- 进一步研究和实施这些技术对于有效的森林保护和管理至关重要.
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