Leaf area index(LAI) is an important vegetation structural parameter for quantitative analysis of many ecological and hydrological processes related to vegetation dynamics as well as phenological trends.Short Revisit period and coarse or medium-resolution satellite imageries(e.g.SPOT/VEGETATION and MODIS) demonstrate great potential in exploring large scale leaf area index(LAI),but the reliability is still unclear when LAI algorithms based on high-resolution satellite imageries applied to coarse-resolution imageries.Totally 490 plot-LAIs(50m×50m) were measured by using Tracing Radiation and Architecture of Canopies(TRAC) and LAI-2000 instruments in the upstream catchment of Minjiang river in SW China.Landsat Thematic Mapper(TM) scenes at 30m-resolution were used to calculate Normalized Difference Vegetation Index(NDVI) and locate ground sites.Seven land cover-specific NDVI-LAI converting algorithm were constructed by regression analysis.MOD NDVI products at 250m-resolution and 1000m resolution SPOT/VEGETATION NDVI were used to produce coarse-resolution LAI data.Since regions of the spectrum among the different sensors are not exactly the same,a mutual calibration among the sensors was first performed before they were used for TM LAI algorithms,and the acquisition date of TM data,VEGETATION and MOD NDVI data were constrained in the same month,i.e.July 2002,field measurements were carried out from 2002 to 2004 with the matching dates.The mean LAI of the catchment derived from TM,MODIS and VEGETATION imageries are 4.53,3.55 and 4.20 respectively.MODIS LAI,VEGETATION LAI images and those in the matching TM scenes were compared,TM LAI map is much better correlated to MODIS LAI than to VEGETATION LAI.With the decreasing of the spatial resolution,the LAI was likely to be underestimated,in particular,MODIS LAI was underestimated by 22%.It is possible to use MODIS 250m-resolution imagery to map LAI distribution with acceptable error of approximately 30%,but 1000m-resolution VEGETATION imagery causes considerable error of 50%.Comparisons of LAI values of different-resolution resampled from TM 30m pixels indicate that it is major cause of scaling errors when aggregate map from high-resolution to coarse-resolution.We speculate that it is a likely result of landscape fragmentation of this area.