基于形态指纹特征的耕地遥感监测轻量化大模型构建 (中国农业科学 2026, 59(1):78-89)
核心期刊论文，提出耕地遥感监测轻量化大模型新思路，方法新颖，但发表时间较早，时效性低。
唐华俊、李会宾、苏宝峰、范蓓蕾、胡琼、叶剑秋、张帅、吴文斌、余强毅、史云、段玉林、李文娟、钱建平、宋茜、夏浪发表论文。本研究构建基于形态指纹特征的耕地遥感监测轻量化大模型,通过强化注意力机制以聚焦和捕获耕地形态的重要特征,并基于这些特征构建轻量化多模态模型,服务于耕地遥感监测应用场景。
唐华俊 1 李会宾 1 苏宝峰 2 范蓓蕾 3 胡琼 4 叶剑秋 5 张帅 6 吴文斌 1 余强毅 1 史云 1 段玉林 1 李文娟 1 钱建平 1 宋茜 1 夏浪 1
作者信息
- 1. 中国农业科学院农业资源与农业区划研究所/北方干旱半干旱耕地高效利用全国重点实验室/农业农村部农业遥感重点实验室,北京 100081
- 2. 西北农林科技大学机械与电子工程学院,陕西 杨凌 712100
- 3. 中国农业科学院农业信息研究所,北京 100081
- 4. 华中师范大学城市与环境科学学院,武汉 430070
- 5. 中国热带农业科学院科技信息研究所,海口 571101
- 6. 农业农村部农田建设管理司,北京 100125
- 折叠
摘要
Abstract
The spatio-temporal dynamics of cropland and their utilization are crucial to national food security,resource security and ecological security.Currently,the approach to cropland remote sensing monitoring generally follows the"data-(model)-information"paradigm.However,this paradigm has a significant"innovation-application"gap,with numerous information products but weak knowledge service capabilities,which fail to meet practical application needs of cropland protection and utilization.Artificial intelligence(AI)technology is accelerating the transformation from active data retrieval and analysis to intelligent knowledge services and empowerment.In the new era,the technical system for cropland remote sensing monitoring needs to be restructured.This paper thus proposed an innovative idea for constructing a lightweight multimodal model for cropland remote sensing monitoring.Firstly,it analyzed the demands of different subjects and categorized the application scenarios of cropland remote sensing monitoring into four aspects(cropland area and use,infrastructure,degradation,and crop growth),clarifying the specific requirements for monitoring information and knowledge services in different scenarios.Secondly,from the perspective of human cognition,it analyzed the"macro-level knowledge"and"fine-grained information"characteristics contained in the morphological features of cropland,providing a new entry point for the construction of a multimodal model for cropland remote sensing monitoring.Finally,it combines multi-modal remote sensing data with general large language models to construct an AI agent for cropland remote sensing monitoring,featuring capabilities in perception,reasoning,learning,and execution.It strengthens the attention mechanism to focus on and capture the important features of cropland morphology,and builds a lightweight multimodal model based on these features.
关键词
人工智能 / 耕地遥感监测 / 应用场景 / 形态特征 / 注意力机制 / 轻量化大模型
Key words
artificial intelligence / cropland remote sensing monitoring / application scenarios / morphological characteristics / attention mechanism / lightweight multimodal model
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唐华俊,李会宾,苏宝峰,范蓓蕾,胡琼,叶剑秋,张帅,吴文斌,余强毅,史云,段玉林,李文娟,钱建平,宋茜,夏浪..基于形态指纹特征的耕地遥感监测轻量化大模型构建[J].中国农业科学,2026,59(1):78-89,12.