Retrieval and application of leaf area index over China using HJ-1 data

Abstract

Although leaf area index (LAI) is one of the essential parameters employed to monitor global vegetation, no global LAI products which use a fine spatial resolution yet exist. To remedy this, we herein outline an adapted LAI retrieval algorithm which employs HuanJing-1 charge-coupled device (HJ-1 CCD) data, which was originally determined using Landsat thematic mapper (TM) data. Validation of this adapted LAI retrieval algorithm via field measurements demonstrates that errors for ∼72% of the sample sites were within a range of 0.2 for the Bashang Grassland in Hebei Province, and within 1.0 for the Taihe region in Jiangxi Province. In addition, the correlation coefficients (R) of HJ-1 LAI and ground-measured LAI data were similar to those of MODIS LAI and ground-measured LAI datasets for both regions. These results demonstrate the potential for transposing a mature Landsat LAI-retrieval algorithm to HJ-1 data. Furthermore, we generated 30 m HJ-1 LAI datasets for China for the summer of 2012. An analytical comparison between retrieved HJ-1 LAI and MODIS LAI data showed the coherence of the LAI distribution. Finally, a specific post-forest fire area was mapped using HJ-1 LAI datasets.