中国农业信息2025，Vol.37Issue(3)：34-45,12.DOI:10.12105/j.issn.1672-0423.20250303
基于深度学习的地貌坎线自动提取与方向判定研究
Research on automatic extraction and direction determination of landform ridges based on deep learning
摘要
Abstract
[Purpose]Traditional manual mapping methods for extracting geomorphic terrace edges and determining their orientation suffer from inefficiency,strong subjectivity,and limited precision.To address these issues,this study proposes an efficient and accurate method for the automatic extraction of geomorphic terrace edges and orientation determination by integrating deep learning and digital image processing techniques,enabling automated identification and analysis of geomorphic features.[Method]Utilizing high-resolution orthoimagery obtained via UAV technology,the study employed an optimized Mask R-CNN model to identify cultivated land data.The segmented and recognized data were subsequently vectorized,and orientation judgments were performed to ultimately plot the terrace edge data,achieving the application of automatic terrace line extraction.[Result]This paper proposed an efficient automated extraction technique for terrace lines,constructing an end-to-end pipeline from image preprocessing and deep learning recognition to vectorization and direction determination.Through an optimized Mask R-CNN model,it demonstrated excellent performance in overall accuracy,detection capability under high IoU thresholds,and segmentation ability for complex land parcels.Combined with a direction determination algorithm that effectively overcame interference from image noise and local terrain fluctuations,this method achieved automatic and accurate extraction of terrace line information from remote sensing imagery,significantly improving mapping efficiency for surveying personnel.[Conclusion]Future work will focus on further optimizing the model's functionality and architecture and applying it in the field of automated mapping to facilitate the rapid acquisition and analysis of cultivated land data.关键词
深度学习/地貌坎线/方向判断/自动化Key words
deep learning/sill line/direction determination/automation引用本文复制引用
谭可成,刘昊,李盘盘,邓勇,江立,范冲..基于深度学习的地貌坎线自动提取与方向判定研究[J].中国农业信息,2025,37(3):34-45,12.基金项目
湖南省重点领域研发计划"城市建筑群安全风险监测和评估研究"(2023SK2012) （2023SK2012）
