title: Spatially and temporally continuous LAI datasets based on the mixed pixel decomposition method.
abstract: The leaf area index (LAI) is a key biophysical parameter that determines the state of plant growth. A global LAI has been routinely produced by the Moderate Resolution Imaging Spectro-radiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR). However, the MODIS and AVHRR LAI products cannot be synchronized with the same spatial and temporal resolution. The LAI features are not discernible when a global LAI product is implemented at the regional scale because it has low resolution and different land cover types. To obtain high spatial and temporal resolution of LAI products, an empirical model based on the pixel scale was developed. The approach to generate a long (multi-decade) time series of a 1-km spatial resolution LAI normally integrates both AVHRR and MODIS datasets for different land cover types. In this paper, a regression-based model for generating a vegetation LAI was developed using the AVHRR Global Inventory Modelling and Mapping Studies Normalized Difference Vegetation Index (NDVI), MODIS LAI and land cover as input data; the model was evaluated by using relevant data from the same period data from 2000 to 2006. The results of this method show a good consistency in LAI values retrieved from the AVHRR NDVI and MODIS LAI. This simple method has no specific-limited data requirements and can provide improved spatial and temporal resolution in a region without ground data.
authors.affiliation: School of Geographical Sciences, Northeast Normal University, Changchun, 130024 Jilin China.
authors.forename: Jianjun
authors.initials: J
authors.lastname: Zhao
authors.affiliation: School of Geographical Sciences, Northeast Normal University, Changchun, 130024 Jilin China.
authors.forename: Yanying
authors.initials: Y
authors.lastname: Wang
authors.affiliation: School of Geographical Sciences, Northeast Normal University, Changchun, 130024 Jilin China.
authors.forename: Hongyan
authors.initials: H
authors.lastname: Zhang
authors.affiliation: School of Geographical Sciences, Northeast Normal University, Changchun, 130024 Jilin China.
authors.forename: Zhengxiang
authors.initials: Z
authors.lastname: Zhang
authors.affiliation: School of Geographical Sciences, Northeast Normal University, Changchun, 130024 Jilin China.
authors.forename: Xiaoyi
authors.initials: X
authors.lastname: Guo
authors.affiliation: Inner Mongolia Key Laboratory of RS and GIS, Huhhot, 010022 Inner Mongolia China.
authors.forename: Shan
authors.initials: S
authors.lastname: Yu
authors.affiliation: Ecological and Agricultural Meteorology Center of Inner Mongolia Autonomous Region, Huhhot, 010051 Inner Mongolia China.
authors.forename: Wala
authors.initials: W
authors.lastname: Du
keywords: AVHRR; Empirical model; LAI (leaf area index); MODIS; Mixed pixel decomposition; NDVI