热带农业科学2026，Vol.46Issue(2)：152-160,9.DOI:10.12008/j.issn.1009-2196.2026.02.019
农业信息系统监测中遥感和深度学习技术的应用研究进展
Research Progress on the Application of Remote Sensing and Deep Learning Technologies in Agricultural Information System Monitoring
摘要
Abstract
In the process of agricultural modernization,the measurement of crop area and estimation of yield play a crucial role in agricultural production management,food security assessment,and the formulation of food policies.However,tradi-tional manual survey methods have problems such as low efficiency,high cost,and lagging data updates,which make it diffi-cult to meet the needs of large-scale,dynamic,and high-precision agricultural monitoring over large areas.In the fields of agricultural remote sensing and deep learning,crop information extraction based on remote sensing technology has been an important research direction in the past decade,and considerable progress has also been made in crop area measurement and yield estimation.This paper systematically reviews the research progress in remote sensing data acquisition and fusion meth-ods,image segmentation and classification methods,and crop area measurement and yield estimation models,and conducts a comparative analysis of the performance of different deep learning models(such as U-Net,SegNet,and DeepLab series,etc.)in crop identification and area estimation.It summarizes the typical applications of remote sensing and deep learning tech-nologies in the field of agricultural information system monitoring at home and abroad,and points out the challenges existing in current research,such as insufficient model generalization ability,inadequate multisource data fusion,and poor model in-terpretability.Combined with the development trend of agricultural digitization,this paper looks forward to the development direction of intelligent remote sensing in future agricultural resource surveys and precise policy implementation to provide inspiration for the current research and practice in the fields related to crop area measurement and yield estimation.关键词
智慧农业/农业信息系统/遥感技术/深度学习/作物识别/面积测量/产量估算/图像分割Key words
smart agriculture/agricultural Information system/remote sensing technology/deep learning/crop identification/area measurement/yield estimation/image segmentation分类
农业科技引用本文复制引用
但晨,刘芳,黄浩..农业信息系统监测中遥感和深度学习技术的应用研究进展[J].热带农业科学,2026,46(2):152-160,9.基金项目
广西重点研发计划项目(No.桂农科AB241484029) （No.桂农科AB241484029）
广西农业职业技术大学校级项目(No.XJG2304) （No.XJG2304）
广西农业职业技术大学横向项目(No.HX2314). （No.HX2314）
