Abstract
Numerous validation efforts have been conducted over the last decade to assess the accuracy of global leaf area index (LAI) products. However, such efforts continue to face obstacles due to the lack of sufficient high-quality field measurements. In this study, a fine-resolution LAI dataset consisting of 80 reference maps was generated during 2003–2017. The direct destructive method was used to measure the field LAI, and fine-resolution LAI images were derived from Landsat images using semiempirical inversion models. Eighty reference LAI maps, each with an area of 3 km × 3 km and a percentage of cropland larger than 75%, were selected as the fine-resolution validation dataset. The uncertainty associated with the spatial scale effect was also provided. Ultimately, the fine-resolution reference LAI dataset was used to validate the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI product. The results indicate that the fine-resolution reference LAI dataset builds a bridge to link small sampling plots and coarse-resolution pixels, which is extremely important in validating coarse-resolution LAI products.
Highlights
Background & SummaryThe leaf area index (LAI), defined as one-half of the total leaf area per unit ground surface area[1], is a critical parameter used to characterize the structure and function of vegetation[2]
Since the LAI directly relates to the acquisition and utilization of sunlight by leaves, it is a key parameter in terrestrial ecosystem models and closely related to the carbon cycle as well as to photosynthesis, respiration and transpiration in leaves[3]
Direct validation of coarse-resolution LAI products derived from remote sensing data works in concert with the comparison of satellite products with upscaled field LAI maps on the basis of spatial–temporal synchronization[40]
Summary
The leaf area index (LAI), defined as one-half of the total leaf area per unit ground surface area[1], is a critical parameter used to characterize the structure and function of vegetation[2]. For the purpose of validating coarse-resolution satellite products, this validation project has developed high spatial-resolution (10–30 m) maps of biophysical variables including LAI that were calibrated using ground measurements[34]. A seasonal field campaign was carried out by Fang et al to collect LAI measurements of paddy rice, maize, soybean and sorghum using indirect optical methods in Northeast China in 2012–2013 and 2016, which were used to evaluate satellite-based LAI products[38,39]. Direct validation of coarse-resolution LAI products derived from remote sensing data works in concert with the comparison of satellite products with upscaled field LAI maps on the basis of spatial–temporal synchronization[40]. The aim of this study was to develop a highly accurate LAI validation dataset with fine-resolution for Chinese croplands to validate coarse-resolution satellite products based on direct field measurements. Reference maps were applied to validate the accuracy of the MODIS LAI product
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