| 引用本文: | 钱建平,陈颂超,陈奕云,高秉博,程涛,郑文刚,任周桥,张若宇,刘红恩,陈家赢,于雷,徐新朋,李文娟,肖鹏南,蒋一铭,余强毅,吴文斌.数字土壤:赋能传统土壤学研究升级[J].中国农业信息,2025,37(4):1-21 |
| |
|
| 摘要: |
| 【目的】 土壤学的发展经历了由经验科学向实验科学转型、由单一学科向多学科交叉融合的历程。信息技术的快速迭代推动传统土壤学研究迈向定量化、精准化、智能化,为数字土壤的产生与发展奠定了关键基础。因此,系统梳理数字土壤的技术体系、应用场景与发展挑战,对赋能传统土壤学研究升级、推动数字土壤研究具有重要意义。【方法】 文章采用系统综述的方法,辨析数字土壤的概念及与传统土壤学的差异,构建数字土壤技术框架,阐述土壤信息获取、数据处理与融合、空间预测制图、土壤信息系统与数据标准等核心技术体系,总结主要应用场景,深入分析数据、模型、应用层面的关键挑战。【结果】 数字土壤以土壤科学理论为基础、信息技术为支撑,构建了信息获取、数据处理、建模预测、产品构建和服务应用5层技术体系,具有多技术融合、多尺度覆盖、多场景适配三大特点;在智慧农业、耕地利用与保护、气候变化应对与碳管理、农业资源区划等领域发挥关键作用;但仍面临数据共享机制不健全、质量控制难度大,模型精度与泛化能力不足,应用成本高、服务效率待提升等问题。【结论】 数字土壤赋能传统土壤学研究升级,为多尺度、高精度、动态化土壤信息获取与应用提供了全新路径,为全球粮食安全、耕地利用与保护、土壤改良与利用等提供智能决策支持。 |
| 关键词: 数字土壤 智慧农业 耕地保护 土壤信息 数据融合 数字土壤制图 土壤信息系统 |
| DOI:10.12105/j.issn.1672-0423.20250401 |
| 分类号: |
| 基金项目:中国农业科学院科技创新工程科学中心重点任务“复杂环境下土壤光谱响应机理”(CAAS-CSAL-202402);北方干旱半干旱耕地高效利用全国重点实验室开放课题“基于知识引导机器学习的耕地土壤有机碳时空演变”(EUAL-2025-01) |
|
| Digital soil:Driving the transformation of traditional soil science research |
|
Qian Jianping1, Chen Songchao2, Chen Yiyun3, Gao Bingbo4, Cheng Tao5, Zheng Wengang6, Ren Zhouqiao7, Zhang Ruoyu8, Liu Hong'en9, Chen Jiaying10, Yu Lei11, Xu Xinpeng1, Li Wenjuan1, Xiao Pengnan1, Jiang Yiming1, Yu Qiangyi1, Wu Wenbin1
|
|
1State Key Laboratory of Efficient Utilization of Arable Land/Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences,Beijing 100081,China;2College of Environmental and Resource Sciences,Zhejiang University,Hangzhou 310058,Zhejiang,China;3School of Resource and Environmental Sciences,Wuhan University,Wuhan 430079,Hubei,China;4College of Land Science and Technology,China Agricultural University,Beijing 100083,China;5College of Agriculture,Nanjing Agricultural University,Nanjing 210095,Jiangsu,China;6Intelligent Equipment Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,China;7Institute of Digital Agriculture,Zhejiang Academy of Agricultural Sciences,Hangzhou 310021,Zhejiang,China;8College of Mechanical and Electrical Engineering,Shihezi University,Shihezi 832003,Xinjiang,China;9College of Resources and Environment,Henan Agricultural University,Zhengzhou 450002,Henan,China;10College of Resources and Environment,Huazhong Agricultural University,Wuhan 430070,Hubei,China;11College of Urban and Environmental Sciences,Central China Normal University,Wuhan 430079,Hubei,China
|
| Abstract: |
| [Purpose] The development of soil science has undergone a transformation from empirical science to experimental science,and has evolved from a single discipline to an interdisciplinary field through integration. The rapid advancement of information technology is driving traditional soil science research towards quantification,precision,and intelligence,laying a crucial foundation for the emergence and development of digital soil. Therefore,systematically sorting out the technical system,application scenarios,and development challenges of digital soil is of great significance for empowering the upgrading of traditional soil science research and promoting digital soil studies.[Method] A systematic review method was adopted. The concept of digital soil and its differences from traditional soil science were distinguished and analyzed,the technical framework of digital soil was established,and the core technical systems including soil information acquisition,data processing and fusion,spatial prediction and mapping,soil information system and data standards were elaborated. The main application scenarios were summarized,and the key challenges at the data,model and application levels were deeply analyzed.[Result] Based on soil science theories and supported by information technology,digital soil constructed a five-layer technical system covering information acquisition,data processing,modeling and prediction,product construction,and service application,featuring multi-technology integration,multi-scale coverage,and multi-scenario adaptation. It played a key role in fields such as smart agriculture,cultivated land utilization and protection,climate change response and carbon management,and agricultural resource regionalization. However,it still faced issues including imperfect data sharing mechanisms,great difficulties in quality control,insufficient model accuracy and generalization ability,high application costs,and room for improvement in service efficiency.[Conclusion] Digital soil empowers the upgrading of traditional soil science research,providing a new approach for the acquisition and application of large-scale,high-precision and dynamic soil information,and provides intelligent decision support for global food security,cultivated land use and protection,soil amelioration and application,and other fields. |
| Key words: digital soil smart agriculture cultivated land protection soil information data fusion digital soil mapping soil information system |