FY-3A/MERSI积雪制图中NDSI指标建立及积雪判识模型研究——以祁连山区为例  

The establishment of NDSI and snow identification model for mapping regional snow cover using FY-3A/MERSI data:a case study in Qilian Mountains

作　　者：韩涛[1] 王大为[1] 李丽丽[2] HAN Tao;WANG Dawei;LI Lili(Northwest Regional Climate Center,Lanzhou 730020,China;College of Earth and Environmental Sciences Lanzhou University,Lanzhou 730000,China)

机构地区：[1]西北区域气候中心,甘肃兰州730020 [2]兰州大学资源环境学院,甘肃兰州730000

出　　处：《冰川冻土》2018年第3期511-527,共17页Journal of Glaciology and Geocryology

基　　金：甘肃省气象局人才专项"石羊河流域综合治理生态效果气象评价";甘肃省气象局科研项目(GSMAMs2011-02;GSMAMs2016-18)资助;中国气象局风云四号卫星应用示范项目"西北干旱区沙尘监测评估系统";甘肃省科技厅青年科学基金项目(1506RJYA188)

摘　　要：我国新型自主的极轨气象卫星风云3号A星(简称FY-3A)上搭载的中分辨率光谱成像仪(MERSI)为大面积雪监测提供了新的遥感数据源。以中国西北祁连山区为例,分析FY-3A/MERSI传感器积雪与其它地物的图谱特征差异,建立了适用于FY-3A/MERSI的归一化差分积雪指数(NDSI),以此为基础,构建了综合利用多光谱判别指标及土地覆盖类型(LULC)定类辅助的积雪判识模型,生成250 m分辨率的日积雪制图产品。模型通过逐步逼近的树状判别结构,去除了易和积雪混淆的部分乔木林、云、云阴影、水体、湖冰、沙(盐)地等地物,并提出应考虑积雪下覆地表特性的影响,调整设定不同LULC类型的积雪判别阈值约束,实时结合区域LULC影像进行积雪的最终判定与优化。对祁连山区2010-2011年积雪季FY-3A/MERSI影像的积雪制图应用结果表明,该资料能够客观精细地反映积雪的空间分布与动态发展过程。同时利用气象台站积雪观测记录及Terra/MODIS积雪判识结果进行对比验证,结果表明基于FY-3A/MERSI建立的积雪判识模型具有较高的精度和稳定性,特别是提高了云雪区分的效能。Medium Resolution Spectral Imager（MERSI） on board China＇s newgeneration polar orbit meteorological satellite FY-3 A provides a newdata source for snowmonitoring in large area. As a case study,the typical snowcover of Qilian Mountains in northwest China was selected in this paper to develop the algorithm to map snowcover using FY-3 A/MERSI. By analyzing the spectral response characteristics of snowand other surface elements,as well as each channel image quality on FY-3 A/MERSI,the widely used Normalized Difference SnowIndex（NDSI） was defined to be computed from channel 2 and channel 7 for this satellite data. Basing on NDSI,a tree-structure prototype version of snowidentification model was proposed,including five newly-built multi-spectral indexes to remove those pixels such as forest,cloud shadow,water,lake ice,sand（salty land）,or cloud that are usually confused with snowstep by step,especially,a snow/cloud discrimination index was proposed to eliminate cloud,apart from use of cloud mask product in advance. Furthermore,land cover land use（LULC） image has been adopted as auxiliary dataset to adjust the corresponding LULC NDSI threshold constraints for snowfinal determination and optimization. This model is composed as the core of FY-3 A/MERSI snowcover mapping flowchart,to produce daily snowmap at 250 m spatial resolution,and statistics can be generated on the extent and persistence of snowcover in each pixel for time series maps. Preliminary validation activities of our snowidentification model have been undertaken. Comparisons of the 104 FY-3 A/MERSI snowcover maps in 2010-2011 snowseason with snowdepth records from 16 meteorological stations in Qilian Mountains region,the sunny snowcover had an absolute accuracy of 92. 8%. Results of the comparison with the snowcover identified from 6 Terra/MODIS scenes showed that they had consistent pixels about 85%. When the two satellite resultant snowcover maps compared with the 6 supervise-classified and expert-verified snowcover maps derived from integr

关 键 词：积雪 归一化差分积雪指数NDSI FY-3A/MERSI 祁连山 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]