摘要:
快速、准确、客观地提取积雪覆盖信息,获得积雪覆盖时空分布资料,是资源生态环境变化研究中的基本问题,卫星遥感技术为有效解决这个问题提供了技术支持.归一化差值雪指数(normalized difference snow index,ND-SI)法利用积雪在绿光波段(0.53~0.59 μm)高反射和短波红外波段(1.57~1.65 μm)强吸收特征,可实现遥感自动提取积雪区.以Landsat8 OLI影像为数据源根据积雪的光谱特征,在加入波段 B1(0.433 ~0.453 μm)和 B2 (0.450~0.515 μm)特征的基础上,运用提出的增强型雪指数(enhanced normalized difference snow index,ENDSI),从OLI影像上进行积雪自动提取.研究结果表明,对积雪厚度变化ENDSI敏感度强于NDSI;在裸土、薄雪及厚雪区,随着积雪厚度的增加,ENDSI值变化幅度强于NDSI,能有效增大雪与非雪的差异;当ENDSI阈值取0.3时,可以有效区分雪与非雪,提高积雪提取精度.
Abstract:
Detecting snow cover information and snow space-time distribution quickly and accurately is a basic problem of ecological environment changes in the resources. Remote sensing technology effectively provides technical support for solving this problem. Normalized difference snow index (NDSI) is an important method for automatic extracting snow cover information using spectral features of snow,which have high reflection in the green band (0.53~0.59 μm) and strong absorption characteristics in short wave infrared band(1.57~1.65 μm). By using Landsat8 OLI images as the data source and according to the spectral characteristics of snow, the authors propose the enhanced normalized difference snow index(ENDSI) based on adding emissivity characteristics of snow in first band B1 (0.433~0.453 μm) and second band B2 (0.450~0.515 μm),and the utilization of this index to extract snow from OLI images. Simulation and case study results show the following characteristics: the sensitivity of ENDSI is stronger than that of NDSI for the snow thickness;with the increase of the thickness of snow, the change of ENDSI value is stronger than that of NDSI; ENDSI can effectively increase the difference between snow and non-snow;it is easy to extract snow from the image with 0.3 as ENDSI threshold and,in this way,snow extraction accuracy is improved.
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