title: [Accuracy comparison of BJ-1, HJ and Landsat data in the retrieval of grassland vegetation coverage, leaf area index and above ground biomass].
abstract: 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.
authors.affiliation: Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China. wanghongyan225@163.com
authors.forename: Hong-Yan
authors.initials: HY
authors.lastname: Wang
authors.affiliation: Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, China.
authors.forename: Xiao-Song
authors.initials: XS
authors.lastname: Li
authors.affiliation: Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, China.
authors.forename: Jin
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China.
authors.forename: Zhi-Hai
authors.initials: ZH
authors.lastname: Gao
mesh_terms: D018533:Biomass; D065948:Grassland; D008962:Models, Theoretical; D018515:Plant Leaves; D012044:Regression Analysis; D063809:Satellite Imagery