Multi-Scale Validation of MODIS LAI Products Based on Crop Growth Period

Abstract

Leaf area index (LAI) is one of the most important canopy structure parameters utilized in process-based models of climate, hydrology, and biogeochemistry. In order to determine the reliability and applicability of satellite LAI products, it is critical to validate satellite LAI products. Due to surface heterogeneity and scale effects, it is difficult to validate the accuracy of LAI products. In order to improve the spatio-temporal accuracy of satellite LAI products, we propose a new multi-scale LAI product validation method based on a crop growth cycle. In this method, we used the PROSAIL model to derive Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LAI data and Gaofen-1 (GF-1) for the study area. The Empirical Bayes Kriging (EBK) interpolation method was used to perform a spatial multi-scale transformation of Moderate Resolution Imaging Spectroradiometer (MODIS) LAI products, GF-1 LAI data, and ASTER LAI data. Finally, MODIS LAI satellite products were compared with field measured LAI data, GF-1 LAI data, and ASTER LAI data during the growing season of crop field. This study was conducted in the agricultural oasis area of the middle reaches of the Heihe River Basin in northwestern China and the Conghua District of Guangzhou in Guangdong Province. The results suggest that the validation accuracy of the multi-scale MODIS LAI products validated by ASTER LAI data were higher than those of the GF-1 LAI data and the reference field measured LAI data, showing a R2 of 0.758 and relative mean square error (RRMSE) of 28.73% for 15 m ASTER LAI and a R2 of 0.703 and RRMSE of 30.80% for 500 m ASTER LAI, which imply that the 15 m MODIS LAI product generated by the EBK method was more accurate than the 500 m and 8 m products. This study provides a new validation method for satellite remotely sensed products.

Plant phenotyping relevance

作物キャノピーのLAIという植物形質について、衛星LAI製品のマルチスケール検証手法を提案・評価しており、形質取得と検証が研究の中心である。

Code and data availability

The paper's LAI validation analysis relies on two public data assets: field-measured corn LAI/LAD/spectral samples from the Heihe Plan Science Data Center (public URL given) and the MOD15A2H LAI satellite product from LP DAAC, both directly used in the paper's multi-scale MODIS LAI validation. No author analysis code,