数据与计算发展前沿 ›› 2023, Vol. 5 ›› Issue (3): 39-48.

CSTR: 32002.14.jfdc.CN10-1649/TP.2023.03.004

doi: 10.11871/jfdc.issn.2096-742X.2023.03.004

• 专刊：“人工智能&大数据”科研范式变革专刊（下） • 上一篇    下一篇

基于“大数据+人工智能”科研范式的黑土地保护与利用智能决策

李之超1,2(),廖晓勇1,2,*(),姚启星1,2,董金玮1,2,李泽红1,2,李静1,2   

  1. 1.中国科学院地理科学与资源研究所，北京 100101
    2.中国科学院大学，北京 100049
  • 收稿日期:2023-04-20 出版日期:2023-06-20 发布日期:2023-06-21
  • 通讯作者: *廖晓勇（E-mail: liaoxy@igsnrr.ac.cn）
  • 作者简介:李之超，中国科学院地理科学与资源研究所，副研究员，长期从事土地利用变化及其健康效应，构建了“地理空间大数据+云计算平台+人工智能”的土地利用信息提取与健康风险评估方法。
    本文中主要负责文献调研、论文撰写及修改。
    LI Zhichao, Associate Professor, Institute of Geographic Scie-nces and Natural Resources Research (IGSNRR), China Acade-my Science (CAS). He has been engaged in land use changes and health effects. He has proposed the method for land use mapping and health assessment based on geospatial data cloud computing and artificial intelligence.
    In this paper, he is mainly responsible for literature review, manuscript drafting, and revision.
    E-mail: lizc@igsnrr.ac.cn|廖晓勇，中国科学院地理科学与资源研究所，研究员，国家杰出青年，科技北京百名领军人才，长期从事污染农田土壤和城市工业场地风险评估、修复技术和装备研究。我国较早从事污染土地修复技术研究和工程示范的学者之一。
    本文主要承担工作是科研范式构建与应用示范落地。
    LIAO Xiaoyong, Professor of Institute of Geographic Sciences and Natural Resources Research (IGSNRR), China Academy Science (CAS), National Science Foundation for Distinguished Young Scholars. He has been engaged in the risk assessment, remediation technology and equipment of contaminated farml-and soil and urban industrial sites. He is one of the early scho-lars in China conducting research and engineering demonstr-ation on polluted land restoration technology.
    In this paper, he is mainly responsible for research design and application demonstration.
    E-mail: liaoxy@igsnrr.ac.cn
  • 基金资助:
    基于“大数据+人工智能”黑土地退化修复的种植模式推荐与应用示范(CAS-WX2023SF-0102)

“Big Data-Artificial Intelligence" Scientific Research Paradigm for Intelligent Decision-Making in Black Soil Conservation and Utilization

LI Zhichao1,2(),LIAO Xiaoyong1,2,*(),YAO Qixing1,2,DONG Jinwei1,2,LI Zehong1,2,LI Jing1,2   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2023-04-20 Online:2023-06-20 Published:2023-06-21

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摘要：

【目的】 我国黑土地受到多种自然和人类活动因素的影响，其退化问题多样以及退化程度存在明显的空间差异，为黑土地保护与利用带来挑战。在此背景下，本文拟提出基于“大数据+人工智能”的黑土地保护与利用智能决策的科研范式，实现退化问题的智能诊断以及关键保护与利用技术在黑土地全域的科学、精准和智能推荐。【方法】 本文通过对国内外土壤保护与利用的文献调研，结合星、空、地、网多源观测技术和机器学习、深度学习等人工智能方法，提出了面向黑土保护与利用的智能决策和应用示范的科研范式。【结果】 黑土保护与利用新科研范式的五项关键技术，包括多源数据汇聚与处理、黑土信息一张图制备、黑土地退化问题智能诊断、保护与利用技术集构建以及黑土地退化修复智能决策。【结论】 本文提出的科研范式有助于我国黑土地退化问题与技术措施的智能匹配，实现黑土地保护与利用的精细化、智慧化和高效化。

关键词: 黑土地, 保护与利用, 退化诊断, 智能决策, 应用示范

Abstract:

[Objective] The black soil in China is affected by various natural and human factors. The degradation problems are diverse, and the degree of degradation shows obvious spatial heterogeneity, posing challenges for black soil protection and utilization. In this context, this study proposes a scientific research paradigm for intelligent decision-making in black soil conservation and utilization based on big data and artificial intelligence, which realizes intelligent diagnosis of degradation problems and generates the scientific, accurate, and intelligent recommendation of key technologies for black soil conservation and utilization in China. [Methods] This paper conducts a literature review on black soil conservation and utilization and proposes a new research paradigm based on big data obtained by satellites, unmanned aerial vehicles, ground monitoring apparatuses, Internet of Things, and artificial intelligence methods. [Results] The new research paradigm consists of five key technologies, including collection and processing of multi-source data, generation of black soil information, diagnosis of black soil degradation, construction of the conservation and utilization technology set, and intelligent decision-making for black soil degradation restoration. [Conclusions] The proposed research paradigm contributes to achieving the precise, intelligent, and efficient black soil conservation and utilization by intelligent matching of black soil degradation problems and the technologies.

Key words: Black soil, conservation and utilization, degradation diagnosis, intelligent decision-making, application and dem-onstration