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基于Suomi NPP VIIRS数据的黄海浒苔遥感监测研究
引用本文:郭继强,潘洁,刘文雅,高晓倩,吴辰辰.基于Suomi NPP VIIRS数据的黄海浒苔遥感监测研究[J].安徽农业科学,2018,46(15):63-66.
作者姓名:郭继强  潘洁  刘文雅  高晓倩  吴辰辰
作者单位:南京林业大学,江苏南京,210037;南京林业大学,江苏南京,210037;南京林业大学,江苏南京,210037;南京林业大学,江苏南京,210037;南京林业大学,江苏南京,210037
基金项目:国家自然科学基金项目(31470579;31100414),江苏省高校优势学科建设工程项目
摘    要:目的]基于Suomi NPP VIIRS数据,对2016年黄海浒苔(Enteromorpha prolifera)进行遥感监测,探讨基于NPP影像进行黄海浒苔遥感监测的适用性和可行性。方法]基于NPP影像,利用NDVI动态阈值法提取黄海浒苔面积,获取2016年浒苔分布的时空特征,并将反演结果与MODIS进行对比。结果]2016年黄海浒苔最早发生于5月下旬,6月上旬—7月上旬进入暴发期,7月下旬进入消亡期。截止7月31日共计监测到浒苔聚集现象20次,浒苔持续时间约60 d。VIIRS数据监测到的浒苔分布面积、位置与MODIS数据一致性较好,而且VIIRS在轨运行时间较MODIS更短,光谱质量更高,对浒苔的空间分布显示更加清晰。结论]基于VIIRS数据利用NDVI动态阈值法进行浒苔面积提取的方法可行。

关 键 词:遥感  浒苔  SuomiNPPVIIRS  Terra/AquaMODIS

Study on Remote Sensing Monitoring of Enteromorpha prolifera in the Yellow Sea Based on Suomi NPP VIIRS Data
Abstract:Objective]This paper monitored Enteromorpha prolifer a in the Yellow Sea based on 2016 Suomi NPP VIIRS data and explored the feasibility and applicability of remote sensing monitoring of Enteromorpha prolif era based on NPP images.Method]The method of NDVI dy -namic threshold was used to analyze the spatial-temporal features of Enteromorpha proliferabased on NPP images.Then, the characteristics were compared with those form MODIS.Result]Enteromorpha proli fera first occurred in late May in the Yellow Sea,entered the outbreak pe-riod in early June and early July, finally, entered the extinction period in late July.By the end of July 31st,we monitored the aggregation of Enteromorpha prolifera 20 times and the duration of Enteromorpha prolifera lasted for 60 days.The distribution area and location of Enteromor-pha prolifera monitored by VIIRS data kept good consistence with that by MODIS data.Moreover,VIIRS sensor had a shorter on-orbit time and higher spectral quality compared with MODIS and the spatial distribution of Enteromorpha prolifera monitored by VIIRS data showed more clearly.Conclusion]It is feasible to use the NDVI dynamic threshold method on the extraction of Enteromorpha prolifera area based on VIIRS data.
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