天津农学院学报 ›› 2025, Vol. 32 ›› Issue (3): 50-53.doi: 10.19640/j.cnki.jtau.2025.03.010

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区域性农业碳排放核算与预测方法综述

杨恺斯1, 高斌1, 金政翰2,通信作者   

  1. 1.天津农学院 计算机与信息工程学院,天津 300392;
    2.无锡职业技术学院 机械工程学院,江苏 无锡 214121
  • 收稿日期:2025-04-13 出版日期:2025-06-30 发布日期:2025-07-02
  • 通讯作者: 金政翰(1995—),男,讲师,硕士,主要从事智能方面的研究。E-mail:63254894@qq.com。
  • 作者简介:杨恺斯(1993—),男,讲师,博士,主要从事人工智能、测控技术方面的研究。E-mail:296280063@qq.com。

Review of regional agricultural carbon emission accounting and prediction methods

Yang Kaisi1, Gao Bin1, Jin Zhenghan2,Corresponding Author   

  1. 1. College of Computer and Information Engineering, Tianjin Agricultural University, Tianjin 300392, China;
    2. School of Mechanical Engineering, Wuxi Institute of Technology, Wuxi 214121, Jiangsu Province, China
  • Received:2025-04-13 Online:2025-06-30 Published:2025-07-02

摘要: 在“双碳”目标驱动下,区域性农业碳排放的精准核算与预测有利于碳减排措施的制定。本文系统梳理了农业碳排放核算与预测方法的技术体系,将碳排放核算方法分类为模型估算法、样地清查法以及遥感估算法,将碳排放预测方法分为系统建模法、灰色系统预测法、机器学习法。此外,本文还对不同方法的适用场景与局限性进行了分析。

关键词: 碳排放核算, 碳排放预测, 农业碳排放

Abstract: Driven by the “Dual Carbon” goals, accurate accounting and prediction of regional agricultural carbon emissions facilitate the formulation of carbon emission reduction measures. This paper systematically reviews the technical system of agricultural carbon emission accounting and prediction methods, categorizing carbon emission accounting methods into model estimation methods, sample plot inventory methods, and remote sensing estimation methods, while classifying prediction methods into system modeling methods, grey system prediction methods, and machine learning methods. The applicable scenarios and limitations of different approaches are analyzed too.

Key words: carbon emission accounting, carbon emission prediction, agricultural carbon emissions

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