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

作者:Zhao, XJ (Zhao, Xiaojie)[ 1,2 ] ; Cao, CX (Cao, Chunxiang)[ 1,3 ] ; Ni, XL (Ni, Xiliang)[ 1 ] ; Chen, W (Chen, Wei)[ 1 ]

GEOMATICS NATURAL HAZARDS & RISK

卷: 8  期: 2  页: 478-495

DOI: 10.1080/19475705.2016.1238854

出版年: 2017

摘要

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 similar to 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.

通讯作者地址: Cao, CX (通讯作者)

Inst Remote Sensing & Digital Earth Chinese Acad, State Key Lab Remote Sensing Sci, Beijing, Peoples R China.

通讯作者地址: Cao, CX (通讯作者)

Ctr Applicat Spatial Informat Technol Publ Hlth, Beijing, Peoples R China.

地址:

[ 1 ] Inst Remote Sensing & Digital Earth Chinese Acad, State Key Lab Remote Sensing Sci, Beijing, Peoples R China

[ 2 ] Univ Chinese Acad Sci, Beijing, Peoples R China

[ 3 ] Ctr Applicat Spatial Informat Technol Publ Hlth, Beijing, Peoples R China