Abstract

This study investigated the performances of the Moderate Resolution Imaging Spectroradiometer (MODIS) and GEOLAND2 Version 1 (GEOV1) Leaf Area Index (LAI) products using ground measurements and LAI reference maps over four sites in North China for 2011–2013. The Terra + Aqua MODIS and Terra MODIS LAI retrieved by the main algorithm and GEOV1 LAI within the valid range were evaluated and intercompared using LAI reference maps to assess their uncertainty and seasonal variability The results showed that GEOV1 LAI is the most similar product with the LAI reference maps (R2 = 0.78 and RMSE = 0.59). The MODIS products performed well for biomes with low LAI values, but considerable uncertainty arose when the LAI was larger than 3. Terra + Aqua MODIS (R2 = 0.72 and RMSE = 0.68) was slightly more accurate than Terra MODIS (R2 = 0.57 and RMSE = 0.90) for producing slightly more successful observations. Both MODIS and GEOV1 products effectively followed the seasonal trajectory of the reference maps, and GEOV1 exhibited a smoother seasonal trajectory than MODIS. MODIS anomalies mainly occurred during summer and likely occurred because of surface reflectance uncertainty, shorter temporal resolutions and inconsistency between simulated and MODIS surface reflectances. This study suggests that further improvements of the MODIS LAI products should focus on finer algorithm inputs and improved seasonal variation modeling of MODIS observations. Future field work considering finer biome maps and better generation of LAI reference maps is still needed.

Highlights

  • The leaf area index (LAI), which is defined as the one-sided green leaf area per unit ground area [1,2], is a crucial parameter for describing vegetation structures

  • This study suggests that further improvements of the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI products should focus on finer algorithm inputs and improved seasonal variation modeling of MODIS observations

  • For croplands that have LAI values larger than 3 and domains with LAI-retrieval accuracies limited by the precision of MODIS surface reflectances, Terra + Aqua MODIS produced more successful observations than Terra MODIS

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Summary

Introduction

The leaf area index (LAI), which is defined as the one-sided green leaf area per unit ground area [1,2], is a crucial parameter for describing vegetation structures. The index is closely associated with vegetative photosynthesis, transpiration, and the land surface energy balance [3,4], and is important in modeling biophysical processes and earth system productivity [5,6]. Satellite remote sensing is one of the most effective methods of monitoring terrestrial seasonal and inter-annual variability within regional to global domains [7]. Several global LAI products have been produced from remote sensing data obtained from different sensors, including SPOT/VEGETATION [8,9] and TERRA-AQUA/MODIS [10].

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