安徽农业科学2024，Vol.52Issue(17)：228-232,5.DOI:10.3969/j.issn.0517-6611.2024.17.052
基于不同遥感数据源的农作物精细化分类研究
Crop Refinement Classification Based on Different Remote Sensing Data Sources
摘要
Abstract
Remote sensing technology has become an important means of extracting agricultural information.In order to explore the identifica-tion and classification of crops of different remote sensing data sources,we selected Babu District Dongrong vegetable industry demonstration zone supplied to HongKong as the research area.Base on Planet,GF6 WFV,Landsat 8 OLI remote sensing images,we used the support vec-tor machine method to identify and extract different crops of the tip leaves of bean,Xuedou,Qingzai,vegetable heart of pointed leaf,cabbage mustard.We also evaluated the extraction effect through class separability,overall classification,Kappa coefficient,spectral variation and mapping effect.Results showed that GF6 WFV images were the best resource for crop recognition and extraction in the study area.关键词
Landsat 8 OLI/GF6 WFV/Planet/农作物分类/支持向量机Key words
Landsat 8 OLI/GF6 WFV/Planet/Crop classification/SVM分类
农业科技引用本文复制引用
梁明月,杨倩,何卫军,张生..基于不同遥感数据源的农作物精细化分类研究[J].安徽农业科学,2024,52(17):228-232,5.基金项目
广西壮族自治区地矿局部门预算前期项目"基于多源遥感数据融合的广西特色农产品遥感空间信息平台构建应用示范"(桂地矿综研[2023]4号). （桂地矿综研[2023]4号）
