Assessment of MODIS, MERIS, GEOV1 FPAR Products over Northern China with Ground Measured Data and by Analyzing Residential Effect in Mixed Pixel

Remote Sensing

Xiaoyu Li¹  Hongyan Ren²  Maogui Hu²  Fei Yang²  Yaping Yang² 

[1] Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Science, 4888 Shengbei Street, Changchun 130102, China;The State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources, Chinese Academy of Sciences, Beijing 100101, China;

关键词: FPAR;    MODIS;    MERIS;    GEOV1;    residential area;    mixed pixel;   

DOI  :  10.3390/rs6065428

来源: DOAJ

【 摘 要 】

Fraction of Photosynthetically Active Radiation (FPAR) is a critical parameter in land surface energy balance and climate modeling. Several global FPAR products are available, but these still require considerable assessment and validation due to low spatial resolution. Three major FPAR products that have covered China and provided continuous time series data—MODIS, MERIS and GEOV1—were assessed from 2006–2010. Based on the ground measurement data, the accuracies of these three FPAR products were directly validated for maize and winter wheat over northern China. This investigation also assessed the consistencies among the three FPAR products, and analyzed the residential area in mixed pixels effect on the FPAR products accuracy, at each of the main growth stages of maize and winter wheat. The GEOV1 FPAR product was found to be the most accurate with regression R2 values of 0.818 and 0.655 for ground measured maize and winter wheat FPAR. The maize FPAR data were generally more accurate than the winter wheat FPAR data. The MODIS, MERIS and GEOV1 products all indicated that FPAR variations among the growth stages differed from year to year. The scattered residential areas in mixed pixels were found to significantly affect the FPAR data uncertainties, and these were also analyzed in detail. The effect of residential area percentage in mixed pixels on FPAR values differed for different crops, and this was not necessarily in accordance with the FPAR product accuracy. For the mixed pixels, a quadratic polynomial was able to fit the residential area and FPAR data reasonably well with R2 values higher than 0.9 for most relationships. Quadratic polynomial fitting may provide a simple and convenient method to assess and reduce the residential area effect on FPAR in the mixed pixels.

【 授权许可】

Unknown