新疆大学学报（自然科学版中英文）2026，Vol.43Issue(2)：144-155,12.DOI:10.13568/j.cnki.651094.651316.2025.07.07.0004
基于改进BIT的耕地变化检测算法
Farmland Change Detection Algorithm Based on Improved BIT
摘要
Abstract
Farmland non-agriculturalization is a serious threat to global food security and ecological stability.Remote sens-ing change detection technology has become a core tool for identifying the process of farmland non-agriculturalization by vir-tue of its advantage of large-scale dynamic monitoring.However,existing methods face challenges in balancing the extraction of fine edge details in fragmented farmland with the maintenance of global semantic consistency in large-scale fields,often re-sulting in blurred edges and lost local features.To address these issues,a farmland change detection algorithm based on im-proved BIT,named Far-CDNet,is proposed.Firstly,a detail enhancement convolution module that connects ordinary convolu-tion and multiple differential convolutions in parallel is introduced,and the edge detail representation capability of the feature extraction network is enhanced through dynamic weighting and residual connection.Secondly,the ordinary convolution of the semantic tokenizer in the BIT module is replaced by a deep separable convolution to enhance the local feature capture ability and generate output features with higher-level semantics,so as to improve the overall feature expression ability of the model.Finally,a residual branch is added to further integrate the local and global information before and after the Transformer.The experimental results show that the improved model F1 score is 79.18%,and IoU is 69.32%.Compared with the BIT model,the F1 score is increased by 4.17%,and IoU is increased by 4.24%.关键词
变化检测/非农化/双时相图像Transformer/细节特征增强卷积模块/TransformerKey words
change detection/non-agriculturalization/bitemporal image Transformer/detail feature enhancement convolu-tion module/Transformer分类
信息技术与安全科学引用本文复制引用
徐世亮,赖民权,刘继忠..基于改进BIT的耕地变化检测算法[J].新疆大学学报（自然科学版中英文）,2026,43(2):144-155,12.基金项目
江西省高层次高技能领军人才培养工程项目"基于GIS与视频融合的自然资源监管关键技术研究"(2022233) （2022233）
江西省自然资源厅科技创新项目"基于智能监控与地理信息融合技术在自然资源监管中的应用研究"(202317). （202317）
