华南农业大学学报2026，Vol.47Issue(1)：42-51,10.DOI:10.7671/j.issn.1001-411X.202506005
基于面向对象法与U-Net模型的广东省云浮市云城区耕地后备资源遥感提取
Remote sensing extraction of cultivated land reserve resources in Yuncheng District,Yunfu City,Guangdong Province based on object-oriented method and U-Net model
摘要
Abstract
[Objective]To improve the efficiency and precision of cultivated land reserve resource information extraction,meet the demands of modern agricultural development for land resource dynamic monitoring.[Method]This paper took Yuncheng District in Yunfu City of Guangdong Province as the study area,and proposed a method for extracting cultivated land reserve resources by integrating object-oriented rule construction and deep learning.Using GF-6 high-resolution satellite imagery,multi-scale image segmentation was performed,and a stepwise elimination method was applied to construct land classification identification rules,extracting samples of typical land types.Subsequently,based on the rule-based samples,a training label dataset for the U-Net deep learning model was constructed to accomplish the extraction and classification of cultivated land reserve resources.[Result]For Yuncheng District,the optimal segmentation scale was determined to be 300.At this scale,features of the same category were effectively segmented,with clear boundaries between grassland and bare land.The overall precision of the proposed method in the study area reached 87.3%,while the mean intersection over union and F1 score achieved 75.4%and 86.7%,respectively,enabling precise extraction of complex feature boundaries.The deep learning approach based on the improved U-Net effectively reduced misclassification,particularly in areas with blurred boundaries and mixed pixels,and improved precision by approximately 5 percentage points compared to traditional object-oriented method.[Conclusion]The remote sensing intelligent extraction method developed in this study demonstrates both high precision and time efficiency.It can provide robust support for local land use planning,cultivated land resource management,and ecological conservation,showing promising potential for broader application.关键词
遥感/耕地后备资源/面向对象/多尺度分割/规则集/深度学习Key words
Remote sensing/Cultivated land reserve resource/Object-oriented/Multi-scale segmentation/Rule set/Deep learning分类
信息技术与安全科学引用本文复制引用
于洋,李哲凡,谢淑娟,刘振华,欧佳铭,司佳禾..基于面向对象法与U-Net模型的广东省云浮市云城区耕地后备资源遥感提取[J].华南农业大学学报,2026,47(1):42-51,10.基金项目
国防科工局重大专项(83-Y50G23-9001-22123) （83-Y50G23-9001-22123）
