Wang Hong-Yan, Li Xiao-Song, Zhang Jin, Gao Zhi-Hai
Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China.
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2013 Oct;33(10):2803-8.
Domestic satellites BJ-1, HJ and the most widely used satellite Landsat were selected to systematically compare their abilities and differences on the estimation of the biophysical parameters of grassland in sandstorm source region in Beijing and Tianjin, with the combination of field-measured fractional coverage, leaf area index and aboveground biomass data. The result shows: (1) In terms of the surface reflectance, HJ-1B and Landsat have a higher correlation with biophysical parameters in red band, compared with BJ-1, while BJ-1's near infra-red band was obviously superior to HJ-1B and Landsat, (2) with respect to the vegetation indices, Landsat performed best, HJ-1B was the second, and BJ-1 was the worst, (3) compared with vegetation indices, multiple regression model can raise the estimation accuracy, BJ-1 based model improved significantly, while Landsat and HJ-1B based models were less obvious. Among them, the highest accuracy was acquired for leaf area index estimation through the BJ-1 based model (R2 = 0.61, RMSEP = 0.15). In general, domestic satellites have their own unique features, which remain a huge potential to be further tapped.
选取国内卫星BJ-1、HJ以及应用最为广泛的Landsat卫星，结合野外实测的植被覆盖度、叶面积指数和地上生物量数据，系统比较它们在北京和天津沙尘暴源区草地生物物理参数估算方面的能力及差异。结果表明：（1）在地表反射率方面，与BJ-1相比，HJ-1B和Landsat在红波段与生物物理参数的相关性更高，而BJ-1的近红外波段明显优于HJ-1B和Landsat；（2）在植被指数方面，Landsat表现最佳，HJ-1B次之，BJ-1最差；（3）与植被指数相比，多元回归模型可提高估算精度，基于BJ-1的模型精度提高显著，而基于Landsat和HJ-1B的模型精度提高不太明显。其中，基于BJ-1的模型估算叶面积指数的精度最高（R2 = 0.61，RMSEP = 0.15）。总体而言，国产卫星各有独特之处，仍有巨大的潜力有待进一步挖掘。
