Objective Hyperspectral characteristics and effect of aspect on spectral reflectance of Pinus kesiya var. langbianensis canopy based on airborne remote sensing imagery were investigated in Caiyanghe National Park, southeast Pu'er, Yunnan province.

Method Hyperspectral and Lidar data were obtained using airborne LiCHy system in April, 2014. The Lidar data were used to get DEM and slope data. In addition, the characteristic values of spectral curves of P.kesiya var. langbianensis stands in different aspects were statistically analyzed using hyperspectral and forest resources inventory data.

Result (1) The spectral reflectance of P.kesiya var. langbianensis canopy was similar to that of green plant. The canopy reflectivity was high in the near infrared band (0.74~1.0 μm), of which, the highest reflectivity located in 0.89μm. (2) The spectral reflectance of P.kesiya var. langbianensis canopy in shady slope was higher than that in sunny slope. There was a significant difference at the peak reflectance of band in north, northeast, south and southeast slopes. (3) According to the solar elevation angle, east, northeast and southeast slopes where face the light has more light radiation than west, northwest and southwest slope and the spectral reflectance was also high. In 0.89 μm band, the reflection of the backlight was 14%~23% lower than that of the face light.

Conclusion (1) The spectral reflectance of P.kesiya var. langbianensis canopy shows typical vegetation spectrum characteristics such as "two valleys and one peak" and "red edge". The reflectivity is higher in 0.74~1.0μm band which usually used as special spectrum for P.kesiya var. langbianensis. (2) The solar elevation angle is the main factor affecting the spectral reflectance of different aspect. Besides, the aspect is another important reason causing the difference of reflectance. This study will provide references for complex terrain hyperspectral quantitative remote sensing and tree species identification.