摘要
针对国产卫星HJ-1B数据积雪像元识别的问题,该文分析了归一化差分积雪指数法和改进的归一化差分积雪指数法的优缺点,并根据积雪与其他地物的光谱特征变化幅度的差异性,提出了一个仅用HJ-CCD数据作为数据源的积雪识别方法。实验中,选取了两块不同特征的影像进行试验,以神经网络分类结合目视解译方法的提取结果作为标准进行精度评价。结果表明,该文提出的方法操作简单,能快速、准确地识别区域积雪覆盖面积。
-Aiming at the problem of snow pixel recognition of domestic satellite HJ-1Bdata,this paper analyzed the advantages and disadvantages of normalized difference snow index(NDSI)and modified normalized difference snow index(MNDSI),then proposed a method to identify snow that is merely based on HJ-CCD data according to the difference between the amplitude of variation of snow and other objects.This paper selected two block remote sensing images with different characteristics and conducted a comparative study that took the results extracted through the combination of neural network classification and artificial interpretation methods as standard.The results showed that the method proposed in this paper was simpler,faster,and more effective on the extraction of snow cover area.
出处
《测绘科学》
CSCD
北大核心
2016年第8期129-133,共5页
Science of Surveying and Mapping
基金
国家重大科技专项(08-Y30B07-9001-13/15)
国家科技支撑计划项目(2013BAB05B01)
中国博士后科学基金资助项目(2014M552558XB)
中国水利水电科学研究院科研专项基金项目(514310)