人工林经营优化决策模型、系统研究与应用
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利用信息技术集成人工林培育经营全过程中所需的专业知识和决策技术，以信息化带 动林业生产管理现代化，针对传统立地因子获取手段单一、动态变化反应不及时、精度低 等问题，以资源调查、固定样地和标准地自动观测、遥感影像等数字化信息为基础，研究森林生境因子的精准获取技术与方法 以杉木人工林、华北落叶松为研究对象，研究人工林的立地评价模型与技术、林木形态模型模拟、生长收获预测技术和经营方案优化决策模 型的构建，研制人工林经营决策支持系统，辅助进行资源优化配置和生产经营决策支持。 项目研究森林立地评价技术，针对无林地立地因子和历史经营数据，研究无林地立地 质量评价技术，为人工林抚育以及经营管理提供决策支持 针对有林地的林分数据，研究 有林地的林分质量评价技术，为人工林抚育以及经营管理提供决策支持。运用结构功能模 型和生长收获模型，构建树木形态模型、形态收获模型及经营实施方案优化决策模型，通 过该模型进行数值优化计算，从而探索功能结构、物质分配等理论在森林经营研究领域中的运用，得出栽培立地条件下合理的造林初植密度、间伐次数、间伐时间、间伐强度和主 伐年龄，使投资收益最优。针对森林中重要组成部分的人工林不同经营目标，在数字化森林生境评价模型的基础上，结合森林经营管理过程中生长收获、分析预测、效益评价模型， 研究森林经营管理过程模型的存储管理、解译解析和动态更新技术 结合不同社会环境条 件与市场因素下的经济技术指标，研究人工林经营经济技术指标预测模型 根据林分抚育 间伐、培育管护、收获调整等经营实施方案的实施效果，进行经济效益、生态效益、社会 效益、投资收益、森林碳汇收益计算，研究数字化森林经营决策支持技术，模拟收获方案 制定的决策过程。构建森林经营知识库、林分生长模型库、生长收获与经营决策模型库， 研建森林经营管理决策支持系统，以适应林区土地承包、经营权流转新形式下的经营管理 与服务模式，提高土地生产力和林农的生活水平，为管理部门在经营管理过程中提供专业技术持。
This study integrates professional knowledge and decision-making technologies required for the entire lifecycle of planted forest cultivation and management via information technology, with the goal of advancing the modernization of forestry production management through digitalization. Aiming to address the limitations of traditional site factor acquisition approaches, including single data sources, delayed responses to dynamic changes, and low precision, this research develops precise acquisition technologies and methods for forest habitat factors, leveraging digital information such as resource surveys, automated observations of permanent and standard sample plots, and remote sensing imagery. Focusing on Chinese fir planted forests and North China larch (Larix principis-rupprechtii) as research subjects, this study constructs site evaluation models and technologies for planted forests, tree morphological simulation models, growth and yield prediction technologies, and management plan optimization decision-making models, and develops a planted forest management decision support system to facilitate resource optimization allocation and production and operation decision support. The project also investigates forest site evaluation technologies: for non-forest land site factors and historical management data, it develops non-forest land site quality evaluation technologies to provide decision support for planted forest tending and management; for stand data of forested lands, it develops stand quality evaluation technologies for forested lands, likewise offering decision support for planted forest tending and management. Adopting structure-function models and growth and yield models, this study constructs tree morphological models, morphological yield models, and management plan optimization decision-making models. Numerical optimization calculations are conducted using these models to explore the application of theories such as functional structure and material allocation in forest management research, and to derive reasonable initial planting density for afforestation, thinning frequency, thinning timing, thinning intensity, and final cutting age under cultivation site conditions to achieve optimal investment returns. For diverse management objectives of planted forests, which constitute a critical component of forest ecosystems, based on the digital forest habitat evaluation model and combined with growth and yield, analysis and prediction, and benefit evaluation models used in forest management processes, this research investigates storage management, interpretation and analysis, and dynamic update technologies for forest management process models. Combining economic and technical indicators under different social environmental conditions and market factors, it develops artificial forest management economic and technical indicator prediction models. Based on the implementation outcomes of management plans including stand tending thinning, cultivation and protection, and harvest adjustment, this study calculates economic benefits, ecological benefits, social benefits, investment returns, and forest carbon sequestration revenues, and develops digital forest management decision support technologies to simulate the decision-making process of harvest plan formulation. A forest management knowledge base, stand growth model base, growth and yield and management decision model base are constructed, and a forest management decision support system is developed to adapt to the management and service models under the new forms of forest land contracting and management right transfer, improve land productivity and the living standards of forest farmers, and provide professional technical support for management departments during their management processes.
