【摘要】 为了分析高分一号卫星数据在稀疏植被信息提取方面的能力,该文选取浑善达克沙地及其周边为研究区,以GF-1和Landsat TM为数据源,结合地面同步实测数据,比较了两个传感器在荒漠化地区植被覆盖度和地上生物量估算方面的能力与差异。结果表明:在该区域,两种数据基于NDVI建立的对数模型可用于植被覆盖度的估测(GF-1:R2=0.7966,RMSEP=0.0908;Landsat 8:R2=0.8080,RMSEP=0.0871),GF-1基于SAVI和Landsat 8基于NDVI建立的乘幂模型进行地上生物量的估测效果最好(R2=0.4866,0.3715;RMSEP=143.46,130.71)。其次,在该区域,经过修正的土壤调节植被指数MSAVI相对于没有经过修正的土壤调节植被指数SAVI,与植被覆盖度和植被生物量的相关性并没有多大提高。第三,两种数据通过引入蓝色、绿色波段的多元回归模型估算植被覆盖度相比单一植被指数植被要好,尤其是对于Landsat影像改进效果更为明显,R2提高了0.3。总之,GF-1的16m数据具有相对较高的质量,可以代替Landsat 8多光谱数据,而且其具有更高的分辨率、重访周期和覆盖范围。更多还原

【Abstract】 With the wide use of GF-1data,the ability of sparse vegetation information estimation of the data needs to be further analyzed.Based on the data of domestic satellite GF-1and Landsat 8as well as the simultaneous field survey of vegetation cover and above-ground biomass,the research was implemented on Otindag sandy land and its surrounding areas,in which abilities of two sensors to estimate vegetation physiological parameters in desertification areas were compared with each other.It was shown that,firstly,in study region,logarithmic functions which were established on NDVI of GF-1data(R2=0.7966,RMSEP=0.0841)and Landsat 8data(R2=0.8080,RMSEP=0.0871)could be used to estimate the vegetation coverage perfectly,the power functions which were established on NDVI of GF-1and SAVI of Landsat 8 have the best estimation effect(R2=0.4866,0.3715;RMSEP=143.46,130.71).Secondly,compared with the unrevised vegetation index SAVI,the correlation of MSAVI with vegetation cover and above-ground biomass was not significantly improved.Thirdly,blue and green band were introduced into multiple regression models,which were supposed to enhance the ability of estimating vegetation coverage,especially for Landsat,and R2 was improve 0.3.In general,GF-1has a relatively high data quality,it can replace Landsat 8data in vegetation parameter inversion,and it has a higher resolution,shorter revisit cycle and wider coverage.更多还原