Zheng, DL, Heath, LS, Ducey, MJ (2007). "Forest biomass estimated from MODIS and FIA data in the Lake States: MN, WI and MI, USA". FORESTRY, 80(3), 265-278.
This study linked the Moderate Resolution Imaging Spectrometer and USDA Forest Service, Forest Inventory and Analysis (FIA) data through empirical models established using high-resolution Landsat Enhanced Thematic Mapper Plus observations to estimate aboveground biomass (AGB) in three Lake States in the north-central USA. While means obtained from larger sample sizes in FIA datasets can be used as reference numbers over large scales, remote sensing (RS)-based observations have the ability to reflect spatial variation of properties of interest within a given area. Thus, combining two national on-going datasets may improve our ability to accurately estimate ecological properties across large scales. Using standard and consistent data sources can reduce uncertainty and provide more comparable results at both temporal and spatial dimensions. We estimated total forest AGB in the region was 1479 T-g (10(12) g, dry weight) in 2001 with mean AGB value of 95 mg ha(-1) ranging from 4 to 411 mg ha(-1) (within 95 per cent percentiles). Mixed forests featured 66 per cent of the total AGB while deciduous and evergreen forests contained 32 and 2 per cent of the total AGB, respectively, at 1-km pixel resolution. Spatially, AGB values increased from north-west to south-east in general. The RS-based estimates indicated a greater range in AGB variations than the FIA data. Deciduous forests were more variable (both in absolute and relative terms) than evergreen forests. The standard deviation of AGB for deciduous forests was 137 mg ha(-1), or a coefficient of variation of 92 per cent, that for evergreen forests was 24 mg ha(-1), or a coefficient of variation of 37 per cent.