基于高分光学遥感影像的湖南省油茶林地识别技术研究——以汉寿县为例

Study on Camellia Oleifera Forest Identification Technology Based on High Resolution Optical Remote Sensing Image in Hunan Province——Taking Hanshou County as an Example

基于高分光学遥感影像技术,对湖南省油茶产业大县汉寿县油茶林地进行分类特征提取、标注样本类别及建立分类模型等操作,实现研究区油茶林地高精度识别。结果显示:利用基于高分光学遥感影像的深度网络智能化提取油茶林地及人工确认的数据分析方法能够很好识别汉寿县油茶林地的空间分布,与2022年全县油茶精细化调查面积数据对比后精度较高(优于70%);空间分布上,汉寿县太子庙镇的油茶分布集中且面积最大,和地面调查的面积数据相比,该镇的油茶分布面积提取精度最高,为92.57%。研究方法能够较为精准地识别汉寿县油茶林地斑块,从而为湖南省油茶林地遥感普查与保护规划提供重要参考。

Based on high-resolution optical remote sensing image technology,classification feature extraction,annotated sample category,and establishment of classification models were carried out on the Camellia Oleifera forest land in Hanshou County,a major Camellia Oleifera industry county in Hunan Province,to achieve highprecision recognition of the Camellia Oleifera forest land in the research area.The results show:the data analysis method of deep network intelligent extraction and manual confirmation of Camellia oleifera forest land based on high-resolution optical remote sensing images can effectively identify the spatial distribution of Camellia oleifera forest land in Hanshou County,and compared with the refined survey area data of Camellia oleifera in the whole county in 2022,the accuracy is relatively high(better than 70%);in terms of spatial distribution,the distribution of Camellia oleifera in Taizimiao Town,Hanshou County,is relatively concentrated and largest in area,and compared with the field survey area data,the extraction accuracy of Camellia oleifera distribution area is the highest at 92.57% in Taizimiao Town.The research method can accurately identify the patches of Camellia oleifera forest in Hanshou County,therefore,it can also provide important reference for remote sensing survey and protection planning of Camellia oleifera forest in Hunan Province.