摘要
以新疆生产建设兵团第八师150团为研究区域,选用2021年、2022年4个季度共计10期陆地卫星8号陆地成像仪(Landsat8 OLI)遥感数据作为信息获取的数据源;在进行预处理后,应用分层分类的方法,掩膜并去除其他非植被地物,结合时间序列的Landsat8 OLI获取的归一化植被指数(NDVI)物候特征获取农田防护林信息,应用外业调查数据对其进行精度评价。结果表明:150团的农田防护林面积为3099.87 hm^(2)。实地样地调查结果显示,在选取的35个农田防护林样点中,有31个被正确获取,分类准确率达到88.5%。150团的农田防护林均匀分布于各个连队中,但在整个团场范围内分布不均匀,并伴有断带现象。运用分层分类的方法和依据时间序列的遥感图像,能够有效获取农田防护林信息。
Taking the 150th Regiment of the Eighth Division of the Xinjiang Production and Construction Corps as the study area,this research utilized a total of 10 periods of Landsat 8 Operational Land Imager(Landsat8 OLI)remote sensing data collected across four quarters in 2021 and 2022 as the data source for information acquisition.Following preprocessing,a stratified classification method was applied to mask and remove other non-vegetation features.By combining the phenological characteristics obtained from the time series of Landsat 8 OLI normalized difference vegetation index(NDVI),information on farmland shelter forests was acquired,and accuracy assessment was conducted using field survey data.The results showed that the area of farmland shelter forests in the 150 th Regiment is 3099.87 hm^(2).Field survey results showed that out of the 35 selected sample points for farmland shelter forests,31 were accurately identified,yielding a classification accuracy of 88.5%.The farmland shelter forests in the 150 th Regiment are evenly distributed among various teams.However,their distribution within the entire regiment is uneven,and accompanied by the phenomenon of broken belt.The stratified classification method,combined with time-series remote sensing imagery,effectively facilitates the acquisition of information on farmland shelter forests.
作者
戚文文
刘楚豪
史庆秋
李园园
Qi Wenwen;Liu Chuhao;Shi Qingqiu;Li Yuanyuan(Shihezi University,Shihezi 832003,P.R.China)
出处
《东北林业大学学报》
CAS
CSCD
北大核心
2024年第12期111-116,共6页
Journal of Northeast Forestry University
基金
石河子大学高层次人才科研启动资金专项(RCZK202020)。
关键词
农田防护林
归一化植被指数物候特征
信息获取
Farmland shelter forests
Normalized difference vegetation index phenological characteristics
Information acquisition