新疆天山北麓玛纳斯河流域冬、春季积雪覆盖,高山冰川发育,是我国西北干旱区的典型流域,其冰雪融水对北疆工农业生产和生态环境具有重要意义.近五年来,在流域开展5次科学考察、积雪常规观测和星地同步观测,利用GF-1PMS(Panchromatic and...新疆天山北麓玛纳斯河流域冬、春季积雪覆盖,高山冰川发育,是我国西北干旱区的典型流域,其冰雪融水对北疆工农业生产和生态环境具有重要意义.近五年来,在流域开展5次科学考察、积雪常规观测和星地同步观测,利用GF-1PMS(Panchromatic and Multi-Spectral)和WFV(Wide Field of View)、HJ-1CCD(Charge-Coupled Device)和IRS(Infrared Scanner)等国产高分光学遥感数据和C波段RADARSAT-2、ENVISAT ASAR等合成孔径雷达数据,探索山区复杂地形条件下的综合辐射校正方法,建立积雪识别模型获取积雪覆盖范围、积雪表面类型和积雪干湿状况,建立积雪参数反演模型获取雪粒径、雪深和雪水当量,分析流域积雪变化特征与雪盖衰退过程,进行流域融雪径流模型的参数率定、模拟与预报,为流域水资源合理利用与调配提供科学依据.展开更多
This paper proposes an applicable approach for snow information abstraction in northern Xinjiang Basin using MODIS data. Linear spectral mixture analysis （LSMA） was used to calculate snow cover fractions （SF） with...This paper proposes an applicable approach for snow information abstraction in northern Xinjiang Basin using MODIS data. Linear spectral mixture analysis （LSMA） was used to calculate snow cover fractions （SF） within a pixel, which was used to establish a regression function with NDSI. In addition, 80 snow depths samples were collected in the study region. The correlation between image spectra reflectance and snow depth as well as the comparison between measured snow spectra and image spectra was analyzed. An algorithm was developed for snow depth inversion on the basis of the correlation between snow depth and snow spectra in the region. The results indicated that the model of SF had a high accuracy with the mean absolute error 0.06 tested by 26 true measured values and the validation for snow depth model using another dataset with 50 sampling sites showed an RMSE of 1.63. Our study showed that MODIS data provide an alternative method for snow information abstraction through development of algorithms suitable for local application.展开更多
文摘新疆天山北麓玛纳斯河流域冬、春季积雪覆盖,高山冰川发育,是我国西北干旱区的典型流域,其冰雪融水对北疆工农业生产和生态环境具有重要意义.近五年来,在流域开展5次科学考察、积雪常规观测和星地同步观测,利用GF-1PMS(Panchromatic and Multi-Spectral)和WFV(Wide Field of View)、HJ-1CCD(Charge-Coupled Device)和IRS(Infrared Scanner)等国产高分光学遥感数据和C波段RADARSAT-2、ENVISAT ASAR等合成孔径雷达数据,探索山区复杂地形条件下的综合辐射校正方法,建立积雪识别模型获取积雪覆盖范围、积雪表面类型和积雪干湿状况,建立积雪参数反演模型获取雪粒径、雪深和雪水当量,分析流域积雪变化特征与雪盖衰退过程,进行流域融雪径流模型的参数率定、模拟与预报,为流域水资源合理利用与调配提供科学依据.
基金Supported by the National Natural Science Foundation of China （No.70361001）.
文摘This paper proposes an applicable approach for snow information abstraction in northern Xinjiang Basin using MODIS data. Linear spectral mixture analysis （LSMA） was used to calculate snow cover fractions （SF） within a pixel, which was used to establish a regression function with NDSI. In addition, 80 snow depths samples were collected in the study region. The correlation between image spectra reflectance and snow depth as well as the comparison between measured snow spectra and image spectra was analyzed. An algorithm was developed for snow depth inversion on the basis of the correlation between snow depth and snow spectra in the region. The results indicated that the model of SF had a high accuracy with the mean absolute error 0.06 tested by 26 true measured values and the validation for snow depth model using another dataset with 50 sampling sites showed an RMSE of 1.63. Our study showed that MODIS data provide an alternative method for snow information abstraction through development of algorithms suitable for local application.
