关键词: NOAA数据, 多角度遥感, 模型反演, BRDF, 地物分类

Abstract:

This paper utilizes multi-angle NOAA satellite data and combines several main land cover type in agriculture-grazing neighboring zone of neimeng semi-arid region to study the method of obtaining and appraising the multi-angle directional information. After data pretreatment, atmosphere iterative inversion utilizing Ambrals model and Rahman model,we register the obtained multi-angle directional information with landuse map, normal NOAA 1B data to prove and evaluate its validation in enhancing precision and improving method on land type identifying, distilling, classifying. All these aim to integrate multi-angle remote sensing, model inversion, experimental simulation with practical application of satellite remote sensing. At last, we combine and appraise the classification ability of different multi-angle data respectively, and compare the classification result of different classification mode. The classification result shows that the whole classification precision can improve 2%～7% compared with normal 1B data by adding angle information.

Key words: NOAA data, multi-angle remote sensing, model inversion, BRDF, land calssification