首页 | 官方网站   微博 | 高级检索  
     

基于Landsat-8 OLI与Sentinel-2 MSI传感器的香港近海海域叶绿素a浓度遥感反演
引用本文:董舜丹,何宏昌,付波霖,范冬林,王涛涛.基于Landsat-8 OLI与Sentinel-2 MSI传感器的香港近海海域叶绿素a浓度遥感反演[J].科学技术与工程,2021,21(20):8702-8712.
作者姓名:董舜丹  何宏昌  付波霖  范冬林  王涛涛
作者单位:桂林理工大学,桂林理工大学
基金项目:国家自然科学基金(21976043);广西自然科学(2018GXNSFBA281015);桂林理工大学科研启动基金资助项目(GUTQDJJ2017096);广西八桂学者团队项目联合资助
摘    要:为验证Landsat-8 OLI遥感数据与Sentinel-2 MSI遥感数据监测近海海域叶绿素a浓度可行性,以其为数据源,香港近海海域为研究区域,以半分析模型为方法,挑选与监测点实测叶绿素a浓度采集时间一致且遥感影像云覆盖率小于10% 影像清晰的两类遥感影像。对两类遥感影像分别选取2/3的遥感影像数据经预处理后提取其对应实测日期监测点位置遥感反射率进行相关性分析,得到相关性最高的反演因子进行建模,并且利用剩下的1/3数据对其反演回复回归模型进行精度检验,其结果与OCx模型反演结果进行对比效果显著。基于Landsat-8遥感数据建立的最佳反演回归模型为Y=6.8x2-20.77x+17.02,R2=0.906略高于基于Sentinel-2遥感数据建立的最佳反演回归模型Y=-3.345e+05x2+3826x-3.44,R2=0.801,证明了就香港近海海域叶绿素a浓度反演两类遥感数据的可行性,且两类数据的反演结果均呈现出香港近海海域内部海域叶绿素a浓度高于外部叶绿素a浓度的现象。

关 键 词:Landsat-8  OLI    Sentinel-2  MSI    叶绿素a浓度    半分析模型
收稿时间:2020/11/14 0:00:00
修稿时间:2021/4/18 0:00:00

Remote sensing retrieval of chlorophyll a concentration in the coastal waters of Hong Kong based on Landsat-8 OLI and Sentinel-2 MSI sensors
Dong Shundan,He Hongchang,Fu Bolin,Fan Donglin,Wang Taotao.Remote sensing retrieval of chlorophyll a concentration in the coastal waters of Hong Kong based on Landsat-8 OLI and Sentinel-2 MSI sensors[J].Science Technology and Engineering,2021,21(20):8702-8712.
Authors:Dong Shundan  He Hongchang  Fu Bolin  Fan Donglin  Wang Taotao
Affiliation:Guilin University of Technology,
Abstract:To verify the feasibility of using Landsat-8 OLI remote sensing data and Sentinel-2 MSI remote sensing data to monitor the concentration of chlorophyll a in the coastal waters, we used it as the data source, the coastal waters of Hong Kong as the study area, and used the semi-analytical model as the method to select and monitor the measured chlorophyll at points a Two types of remote sensing images with the same concentration collection time and less than 10% cloud coverage in remote sensing images. For the two types of remote sensing images, two thirds of the remote sensing image data are selected after preprocessing, and the remote sensing reflectance of the monitoring point location corresponding to the actual date is extracted for correlation analysis, and the most relevant inversion factor is obtained for modeling, and the remaining 1/3 of the data is used to test the accuracy of its inversion and recovery regression model, and the comparison between the results and the inversion results of the OCx model is significant. The best inversion regression model based on Landsat-8 remote sensing data is Y=6.8x2-20.77x+17.02, R2=0.906 is slightly higher than the best inversion regression model based on Sentinel-2 remote sensing data Y=-3.345e +05x2+3826x-3.44, R2=0.801, which proves the feasibility of inverting the two types of remote sensing data for the chlorophyll a concentration in the Hong Kong offshore waters, and the inversion results of the two types of data show that the chlorophyll a concentration in the internal waters of the Hong Kong offshore waters is high The phenomenon of external chlorophyll a concentration.
Keywords:Landsat-8 OLI      Sentinel-2 MSI      chlorophyll a concentration    semi-analytical mode
点击此处可从《科学技术与工程》浏览原始摘要信息
点击此处可从《科学技术与工程》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司    京ICP备09084417号-23

京公网安备 11010802026262号