Comparative Verification of Leaf Area Index Products for Different Grassland Types in Inner Mongolia, China

Leaf area index (LAI) is a key indicator of vegetation structure and function, and its products have a wide range of applications in vegetation condition assessment and usually act as important input parameters for ecosystem modeling. Grassland plays an important role in regional climate change and the global carbon cycle and numerous studies have focused on the product-based analysis of grassland vegetation changes. However, the performance of various LAI products and their discrepancies across different grassland types in drylands remain unclear. Therefore, it is critical to assess these products prior to application. We evaluated the accuracy of four commonly used LAI products (GEOV2, GLASS, GLOBMAP, and MODIS) using LAI reference maps based on both bridging and cross-validation approaches. Under different grassland types, the GLASS LAI performed better in meadow steppe (R2 = 0.26, RMSE = 0.41 m2/m2) and typical steppe (R2 = 0.32, RMSE = 0.38 m2/m2); the GEOV2 LAI performed better in desert steppe (R2 = 0.39, RMSE = 0.30 m2/m2). When we assessed their spatial and temporal discrepancies during the period from 2010 to 2019, the four LAI products overall showed a high spatial and temporal consistency across the region. Compared with GLASS LAI, the most consistent to least consistent correlations can be ordered by GEOV2 LAI (R2 = 0.94), MODIS LAI (R2 = 0.92), and GLOBMAP LAI (R2 = 0.87). The largest differences in LAI throughout the year occurred in July for all grassland types. Limited by the location and number of sample plots, we mainly focused on spatial and temporal variations. The spatial heterogeneity of land surface is pervasive, especially in vast grassland areas with rich grassland types, and the results of this study can provide a basis for the application of the product in different grassland types. Furthermore, it is essential to develop highly accurate and reliable satellite-based LAI products focused on grassland from the regional to the global scale according to these popular approaches, which is the next step in our work plan.

Automated summary

Leaf area index (LAI) is an important indicator for vegetation structure and function, and its accuracy assessment is crucial for vegetation condition assessment and ecosystem modeling. In this study, the performance of four commonly used LAI products (GEOV2, GLASS, GLOBMAP, and MODIS) was evaluated, and their spatial and temporal consistency across different grassland types in drylands were analyzed. The results showed that GLASS LAI performed better in meadow steppe and typical steppe, while GEOV2 LAI performed better in desert steppe. Overall, the four LAI products exhibited high consistency across the region, with GEOV2 LAI showing the highest correlation. The largest differences in LAI occurred in July for all grassland types. The findings provide a basis for the application of LAI products in different grassland types and highlight the need for highly accurate and reliable satellite-based LAI products focused on grassland at regional and global scales.