草业科学2024，Vol.41Issue(2)：322-331,10.DOI:10.11829/j.issn.1001-0629.2023-0270
基于多时相Sentinel-2A影像的狼毒分布识别
Identification of Stellera chamaejasme distribution based on multi-temporal Sentinel-2A images
摘要
Abstract
Stellera chamaejasme has been one of the main invasive noxious weeds in the alpine grasslands of the Qinghai-Tibet Plateau in recent years.Timely and efficient investigation and monitoring can provide important technical support for the integrated control of S.chamaejasme and the restoration of degraded grasslands.In this study,Sentinel-2A multi-spectral images of before flowering and full flowering were selected,and the Google Earth Engine platform cloud removal,environmental factor masking,feature selection,and random forest classification were combined to explore a regional scale remote sensing identification method for S.chamaejasme.We found that seven features of S.chamaejasme classification were extracted and four feature combinations were constructed through the calculation of the S.chamaejasme sensitivity index and the secondary dimensionality reduction,combined with Spearman rank correlation analysis and random forest importance ranking.Compared with the combination of single temporal features,the combination of multi-temporal features effectively improved the recognition accuracy of S.chamaejasme.Among them,the total classification accuracy of the six features combination scheme based on the random forest model was 84.62%,and the classification accuracy of S.chamaejasme was all more than 80%,showing the best recognition effect.This study shows that the image cloud removal and mask preprocessing can effectively reduce the classification interference information,and the combination of multi-temporal features extracted before flowering and in full bloom enhances the spectral difference between S.chamaejasme community and other plant communities,indicating good application potential in the regional scale remote sensing recognition of S.chamaejasme.关键词
去云/特征优选/分层掩膜/多时相分析/随机森林/敏感指数/狼毒Key words
cloud removal/feature selection/hierarchical masking/multitemporal analysis/random forest/sensitivity index/Stellera chamaejasme引用本文复制引用
房家玮,胡念钊,王怀玉,刘咏梅..基于多时相Sentinel-2A影像的狼毒分布识别[J].草业科学,2024,41(2):322-331,10.基金项目
国家自然科学基金项目"退化高寒草甸狼毒遥感识别及其对环境的响应关系"(41871335) （41871335）
