林业经济问题2024，Vol.44Issue(5)：449-460,12.DOI:10.16832/j.cnki.1005-9709.20240458
智慧林业研究前沿与展望
The Research Frontiers and Prospects of Smart Forestry
摘要
Abstract
⑴ Background——With rapid population growth,there is an increasing demand for diverse forest products and ecosystem services.Global climate change exacerbates risks and uncertainties in forestry systems.However,digital and smart technologies are recognized as the driving forces of the innovative economy and sustainable de-velopment,with great potential to change the future direction of forestry systems.The 26th world congress of the International Union of Forest Research Organizations(IUFRO)is the largest and most influential forestry aca-demic event,and smart forestry is one of the current frontier research fields of forestry. ⑵ Methods——According to the concept,characteristics,connotation and extension of smart forestry,the related issues of smart forestry were selected from the conference agenda of the 26th World Congress of IUFRO,and the text data set was extracted as the research basis of this paper.The python was used as the main tool to analyze the text data set,the specific process is:First,import the necessary libraries;Second,preprocess the text data,remove the stop words and punctuation marks,and eliminate the words with too high frequency and low analytical value such as"forest","forestry"and"trees"combined with the research theme;Third,the term frequency-inverse document frequency(TF-IDF)values of the text were calculated,and the highest values were used to generate word cloud maps or the heatmap functions were used to draw heat maps.Finally,it further analyzed the frontier issues of smart forestry research from the perspectives of natural science and social science. ⑶Results——From the perspective of natural science,the research of smart forestry mainly focuses on two aspects:one is digitalization,that is,achieve the near-real-time,multi-scale and all-round forest monitoring through the application of digital technologies such as remote sensing.The other is intelligentization,that is,the intelligent decision support system helps solve the problems of forest resource management such as multi-objective management decision-making,complex decision-making and multi-stakeholder decision-making.From the per-spective of social science,the research of smart forestry mainly focuses on three aspects:efficiency,equity and policy.In terms of efficiency,it includes the digitally literate labour forces in the future,modern forest opera-tions,and AI-enabled decision-making.In terms of equity,it includes gender equality in the forestry sectors,forest voice on digital platforms,and bridging the digital divide in forest governance.In terms of policy,it mainly includes global forest governance and international cooperation. ⑷ Conclusions and Discussions——The development of global smart forestry has important practical sig-nificance:while making full use of digital monitoring technology and intelligent decision support system,it can a-chieve the integration of efficiency,equity and policy.In addition,the technology application and policy innova-tion of smart forestry not only provide a useful reference for the development of Chinese forestry,but also promote the technical cooperation,technology sharing and policy dialogue in the field of smart forestry among countries a-round the world.The Strategies to meet the challenges of smart forestry research include:promoting the standard-ization and interoperability of technologies,rapidly updating the research methods and techniques,effectively ac-quiring and processing big data,and improving the application of research results.Future research on the smart forestry can focus on three key areas:innovation and diffusion of technology,deepening of multidisciplinary re-search,and strengthening of policy and global cooperation.关键词
智慧林业/数字技术/数字化/智能化/IUFROKey words
smart forestry/digital technology/digitalization/intelligentization/IUFRO分类
农业科技引用本文复制引用
曹玉昆,张亚芳,任月,刘嘉琦..智慧林业研究前沿与展望[J].林业经济问题,2024,44(5):449-460,12.基金项目
国家社会科学基金青年项目(23CGL063)、黑龙江省博士后面上项目(LBH-Z23052)、国家资助博士后研究人员计划(GZC20240232)、中央高校基本科研业务费专项资金项目(2572024DZ03) （23CGL063）
