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融合FY-3C号和FY-4A号卫星数据的积雪面积变化研究—以祁连山区为例
引用本文:乔海伟,张彦丽.融合FY-3C号和FY-4A号卫星数据的积雪面积变化研究—以祁连山区为例[J].遥感技术与应用,2020,35(6):1320-1328.
作者姓名:乔海伟  张彦丽
作者单位:1.西北师范大学地理与环境科学学院,甘肃 兰州 730070;2.中国科学院空天信息创新研究院,北京 100094;3.中国科学院大学,北京 100049
基金项目:国家自然科学基金项目(41871277);中国博士后科学基金项目(2016M602893)
摘    要:祁连山区积雪类型丰富、判识复杂,是中国积雪研究的典型区域。因此,精确地监测祁连山区积雪面积变化及其时空演变,对祁连山区生态环境和社会经济发展等具有重要意义。FY-3C MULSS利用多阈值积雪指数模型提供全球日积雪覆盖产品,FY-4A AGRI传感器每15~60 min提供一景覆盖全球的多光谱影像。基于FY-4A AGRI高时间分辨率的特征,构建适合于FY-4A号数据的动态多阈值多时相云隙间积雪识别方法,很大程度上减小了云对光学数据识别积雪造成的影响,并结合FY-3C MULSS积雪覆盖日产品较高空间分辨率的优势,融合得到去除云后的FY3C4积雪覆盖数据。利用Landsat 8 OLI卫星数据对融合后的积雪数据进行对比验证,结果表明融合FY-3C和FY-4A后的数据能更好地判识祁连山区的积雪覆盖情况。以MODIS MOD10A2积雪产品为真实值,随机检验了2018年3月~2019年3月融合后数据的积雪判识精度,发现无云情况下方法的总体精度可达到85.25%。进一步研究发现祁连山区积雪面积在海拔、气候和坡向等因素的影响下时空分布极不均匀,总体呈现出冬春季节大于夏秋季节,以及东部积雪面积大于西部积雪面积的特征。

关 键 词:祁连山区  风云系列影像  影像融合  积雪识别  积雪面积  时空变化  
收稿时间:2019-12-25

FY-3C and FY-4A Satellite Data were Combined to Study the Variation of Snow Cover Area: A Case Study of Qilian Mountains
Haiwei Qiao,Yanli Zhang.FY-3C and FY-4A Satellite Data were Combined to Study the Variation of Snow Cover Area: A Case Study of Qilian Mountains[J].Remote Sensing Technology and Application,2020,35(6):1320-1328.
Authors:Haiwei Qiao  Yanli Zhang
Abstract:Qilian Mountains is a typical area of snow cover research in China because of its rich snow types and complex identification. Therefore, it is of great significance for the regional ecological environment and socio-economic development to accurately monitor the change of snow area and its spatiotemporal evolution in the Qilian Mountains. FY-3C MULSS uses the multi-threshold snow index model to provide global daily snow cover products, and the FY-4A AGRI sensor provides a global multispectral image every 15~60 min on average. By using the characteristics of FY-4A AGRI with the high temporal resolution, a dynamic multi-threshold and multi-temporal snow detection method suitable for FY-4A data was constructed, which greatly reduced clouds impact on snow detection in optical images. Then combining with the advantages of the higher spatial resolution of snow-covered daily products FY-3C MULSS, the FY3C4 snow-covered data after cloud removal is obtained. Using Landsat 8 OLI high-resolution satellite data to verify the accuracy of the fused snow cover, the results show that the fused FY-3C and FY-4A can better identify the snow cover in the Qilian Mountains. Taking MODIS MOD10A2 snow cover product as the real value, the recognition accuracy of the fused daily snow cover product from March 2018 to March 2019 is tested randomly, and the overall accuracy is as high as 85.25% without the clouds. Further research shows that the snow area in the Qilian Mountains is extremely uneven in time and space under the influence of altitude, climate and slope direction. In general, the snow cover area in winter and spring is larger than that in summer and autumn, and the snow cover area in the east is larger than that in the west.
Keywords:Qilian Mountains  FengYun series images  Image fusion  Snow cover identification  Snow cover area  Change of time and space  
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