多时相Sentinel-2影像在浙西北茶园信息提取中的应用  

Mapping tea gardens spatial distribution in northwestern Zhejiang Province using multi-temporal Sentinel-2 imagery

作　　者：李龙伟 李楠[1,3] 陆灯盛 LI Longwei;LI Nan;LU Dengsheng(Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province,Zhejiang A&F University,Hangzhou 311300,Zhejiang,China;School of Environmental&Resource Sciences,Zhejiang A&F University,Hangzhou 311300,Zhejiang,China;College of Biology and the Environment,Nanjing Forestry University,Nanjing 210037,Jiangsu,China;School of Geographical Sciences,Fujian Normal University,Fuzhou 350007,Fujian,China)

机构地区：[1]浙江农林大学浙江省森林生态系统碳循环与固碳减排重点实验室,浙江杭州311300 [2]浙江农林大学环境与资源学院,浙江杭州311300 [3]南京林业大学生物与环境学院,江苏南京210037 [4]福建师范大学地理科学学院,福建福州350007

出　　处：《浙江农林大学学报》2019年第5期841-848,共8页Journal of Zhejiang A&F University

基　　金：浙江省自然科学基金资助项目（LQ19D010010）;江苏省研究生科研与实践创新计划资助项目（KYCX17_0819）;南京林业大学博士学位论文创新基金资助项目

摘　　要：利用Sentinel-2遥感影像研究一种快速、准确提取茶园空间分布的新方法,可为茶园经济林资源及其动态变化的快速检测提供新的手段。以浙江省西北部为研究区,根据实地调查选取6类典型植被,基于4个季节的Sentinel多光谱影像分析不同植被物候及光谱特征。茶园在5月经历修剪后与其他植被区别较大,根据红边与短波红外波段构建归一化茶园指数(NDTI)。基于新指数建立决策树模型提取茶园,通过谷歌地球对结果进行验证。结果显示:归一化茶园指数可以最大限度扩大茶园与其他植被之间的差距。基于该指数提取茶园的总精度达93.83%,Kappa系数为0.917,成功实现了浙西北茶园信息的提取,证明了使用红边波段提取茶园的潜力。To develop a new method for accurately mapping the spatial distribution of tea gardens using Sentinel-2 remote sensing imagery,a new approach to the mapping of tea garden resources in Anji of northwestern Zhejiang Province was produced.First,six types of typical vegetation were selected according to a field survey,and their phenological and spectral characteristics were analyzed based on multi-temporal Sentinel imagery.Second,because tea gardens differed from other vegetation types after being pruned in May,a Normalized Tea garden Index(NDTI)was constructed based on the red edge and short-wave infrared bands.Third,a decision tree model based on the new index was used to identify the tea gardens,a total 600 validation points were obtained by field survey,the overall accuracy(OA)and Kappa coefficient were used to evaluate classification accuracy of tea gardens.The accuracy assessment result indicated an overall accuracy of 93.83%and a Kappa coefficient of 0.917.Spatial distribution of the tea gardens was accurately extracted demonstrating the potential to extract tea gardens using the red edge band.The tea gardens was extracted by constructing a normalized tea gardens index,which was easy to understand and realize,and it was easy to operate.

关 键 词：森林经理学 茶园 Sentinel-2 红边波段 归一化茶园指数 浙西北 

分 类 号：S771.8[农业科学—森林工程]