Comparation of different LAI products in hulunber meadow steppe

Abstract: Leaf area index (LAI) is an important parameter in vegetation physiological process model. It is important for global climate change research. Recent years, LAI products is increasing in different characteristics. Different products are suitable for different areas, our research fouced on finding out the most suitable LAI product for typical meadow steppe. The study compared the Moderate Resolution Imaging Spectroradiometer (MODIS), GEOLAND2 Version1 (GEOV1), Global Land Surface Satellite (GLASS) Leaf Area Index (LAI) products and HJ LAI in hulunber China in 2013. 6 measurements of LAI data in 2013 from June to August were acquired. The field measurements achieved by LAI-2000 in 3 km×3 km areas on the temperate meadow steppe in hulunber. The SR (simple ratio index) was calculated from the HJ-1A/B CCD image band reflectance in study area. statistical model between vegetation index SR and LAI ground measurement was established. LAI field measurement were well simulated with the statistical model (R2=0.6042). The HJ-1A/B CCD images with 30m spatial resolution were used on generation of LAI reference map. And others LAI products were 1km spatial resolution. So spatial resolution need transformed to the same scale. The three LAI products HJ LAI were evaluated and cross compared to assess their uncertainty and variability. The results showed that the three LAI products are overestimated meadow steppe LAI the most severe GLASS LAI, over about 41%, followed by MODIS about 32%. GEOV1 LAI product is close to HJ LAI, RMSE=0.289 MAE=0.216. In terms of accuracy, the products were ranked in the following order: GEOV1> MODIS> GLASS.GEOV1 appears to be the most accurate product.Compared to MODIS and GLASS, GEOV2 significantly improved the accuracy in the high LAI area. The neural network (NNT) algorithm, whose training dataset was derived from fused CYCLOPES and MODIS products with varied weights and an additional SWIR band, was the key to the favorable performance of GEOV1. So GEOV1 was the most accurate product for estimates meadow steppe. The differences between LAI products were compared. No significant discrepancies existed between the GEOV1 and GLASS LAI product results (R2=0.6465). By comparing LAI products data in whole year we found that the three products with good timing consistency. GLASS LAI showed a smooth curve, and had significantly overestimated when LAI valuesas wsmall. MODIS LAI was unstable. The LAI of GEOV1 products were smaller than the other two products from the 133rd day to the 201st day. GEOV1 LAI was similar with GLASS LAI, and higher than the MODIS LAI. The numerous pixels that cause obvious LAI retrieval anomalies had the highest quality. So few pixels contaminated by clouds were not a significant cause of the LAI retrieval anomalies in study area.