摘要
风云三号D星(FY-3D)是我国新一代极轨气象卫星,中分辨率光谱成像仪Ⅱ(MERSI-Ⅱ)是其携带的核心传感器之一,MERSI-Ⅱ实现了云、气溶胶、水汽、陆地表面特性、海洋水色等大气、陆地、海洋参量的高精度定量反演。选取2018年7、8月无云时相的FY-3D/MERSI-Ⅱ数据对天山中段终年积雪进行归一化积雪指数(NDSI)的计算。结合高分辨率Landsat-8影像,利用混淆矩阵对FY-3D/MERSI-Ⅱ数据计算结果与同期MODIS日积雪产品数据MOD10A1进行精度对比分析。结果表明:FY-3D/MERSI-Ⅱ图像平均总体精度为0.855,MOD10A1图像平均总体精度为0.820,FY-3D/MERSI-Ⅱ积雪覆盖提取平均总体精度比MOD10A1积雪覆盖提取平均总体精度高0.035。FY-3D/MERSI-Ⅱ的Kappa系数平均值为0.659,MOD10A1的Kappa系数平均值为0.558,FY-3D/MERSI-Ⅱ的Kappa系数平均值大于MOD10A1的Kappa系数平均值。故FY-3D/MERSI-Ⅱ数据提取积雪覆盖面积精度更高,更接近高分辨率Landsat-8影像目视解译结果。
In 2017,China launched FY-3 D,a next-generation meteorological satellite,into polar orbit.One of its core sensors is the Medium-Resolution Spectral Imager Ⅱ(MERSI-Ⅱ) that is capable of high-precision quantitative inversion of atmospheric,terrestrial,and oceanic parameters,including metrics of cloud,aerosol,water vapor,land surface characteristics,and ocean color.We established the true snow cover extent of the middle Tianshan Mountains,Xinjiang,China with visual interpretation of high-resolution Landsat-8 images.We then used FY-3 D/MERSI-Ⅱ data,captured during cloudless conditions in July and August 2018,to calculate the normalized snow cover index.We compared the accuracy of FY-3 D/MERSI-Ⅱ data calculated by confusion matrix against MODIS daily snow product data.With an average overall snow cover extraction accuracy of 0.855,the FY-3 D/MERSI-Ⅱ imagery outperformed MODIS that had an accuracy of 0.820.The average Kappa coefficient of FY-3 D/MERSI-Ⅱ(0.659) was also higher than that of MODIS(0.558).Overall,the accuracy of the snow cover area extracted from FY-3 D/MERSI-Ⅱ data was higher than from MODIS,achieving a closer match to the high-resolution Landsat-8 images.
作者
陈鹏
王勇
张青
李悦
CHEN Peng;WANG Yong;ZHANG Qing;LI Yue(Urumqi Meteorological Satellite Ground Station,Urumqi 830011,Xinjiang,China)
出处
《干旱区地理》
CSCD
北大核心
2020年第2期434-439,共6页
Arid Land Geography
基金
国家自然科学基金项目(41965002)
中国气象局气象卫星工程地面应用系统应用示范项目(FY-3(02)-UDS-1.5.3)资助。
作者简介
陈鹏(1987-),男,工程师,学士,主要从事遥感应用服务与技术开发.E-mail:wxzchenpeng@sina.com;通讯作者:王勇(1968-),男,副研级高工.E-mail:qfwy721@sina.com。
