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1 In this paper, we present an approach for generating a consistent long-term global leaf area index (LAI) product (1981–2011) by quantitative fusion of Moderate Resolution Imaging Spectroradiometer (MODIS) and historical Advanced Very High Resolution Radiometer (AVHRR) data. First, a MODIS LAI series was generated from MODIS data based on the GLOBCARBON LAI algorithm. Then, the relationships between AVHRR observations and MODIS LAI were established pixel by pixel using two data series during overlapped period (2000–2006). Then the AVHRR LAI back to 1981 was estimated from historical AVHRR observations based on these pixel-level relationships. The long-term LAI series was made up by combination of AVHRR LAI (1981–2000) and MODIS LAI (2000–2011). The LAI derived from AVHRR was intercompared with that from MODIS during the overlapped period. The results show that the LAIs from these two different sensors are good consistency, with LAI differences are within ±0.6 over 99.0% vegetated pixels. The long-term LAI was also compared with field measurements, which has an error of 0.81 LAI on average. Compared with the LAI retrieved directly from the GLOBCARBON algorithm, the LAI derived by our method has a lower temporal noise, which means uncertainties from the low quality of AVHRR measurements can be reduced with the aid of high-quality MODIS data. This product is hosted on the GlobalMapping Web site (http://www.globalmapping.org/globalLAI) for free download, which will provide a long-term LAI over 30 years for modeling the carbon and water cycles.
Liu et al. (Mon,) studied this question.