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当前位置: 首页 > 文章 > 多时相Sentinel-2影像在浙西北茶园信息提取中的应用 浙江农林大学学报 2019 (5) 841-848
Position: Home > Articles > Mapping tea gardens spatial distribution in northwestern Zhejiang Province using multi-temporal Sentinel-2 imagery Journal of Zhejiang A&F University 2019 (5) 841-848

多时相Sentinel-2影像在浙西北茶园信息提取中的应用

作  者：
李龙伟;李楠;陆灯盛
单  位：
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
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
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。图6表1参17
译  名：
Mapping tea gardens spatial distribution in northwestern Zhejiang Province using multi-temporal Sentinel-2 imagery
作  者：
LI Longwei;LI Nan;LU Dengsheng;Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A&F University;School of Environmental & Resource Sciences, Zhejiang A&F University;College of Biology and the Environment, Nanjing Forestry University;School of Geographical Sciences, Fujian Normal University;
关键词：
forest management;;tea garden;;Sentinel-2;;red edge band;;Normalized Tea Garden Index(NDTI);;northwestern Zhejiang Province
摘  要：
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. [ Ch, 6 fig. 1 tab. 17 ref.]

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