FOREST ECOSYSTEM PROCESSES AT THE WATERSHED SCALE - SENSITIVITY TO REMOTELY-SENSED LEAF-AREA INDEX ESTIMATES

Recent research has shown that general trends in forest leaf area index along regional climatic gradients can be adequately characterized by using ratios of near-infrared and red reflectances. However it has proven difficult to represent properly the spatial distribution of Leaf Area Index (LAI) at subregional scales such as small catchments. The key problem at Thematic Mapper scale is the variation in canopy closure and understorey contribution, which dramatically influences near-infrared reflectance from conifer forests. In this paper, a new spectral index is presented to estimate LAI of conifer forests using a combination of Red, NIR and mid-IR reflectances from the Landsat Thematic Mapper (TM). A simulation system (RHESSys) was used first, to generate potential vegetation patterns around a watershed in order to test them against remotely-sensed vegetation patterns, and secondly, to test the sensitivity of forest ecosystem processes to LAI estimated from combinations of the Thematic Mapper data. The relation between Normalised Difference Vegetation Index (NDVI) and LAI is poorly defined at TM scale because of the outsized contribution of understorey vegetation and background materials to the NIR reflectance in open canopies. The mid-IR correction factor acting as a scalar for canopy closure scaled down the inflated NDVI in the open canopies, resulting in an improved relation between NDVI and LAI. LAI estimates from the MIR corrected NDVI better represented the vegetation patterns in Soup Creek watershed than those from uncorrected NDVI both in terms of magnitude and spatial patterns. Simulations using LAIs derived from corrected NDVI showed lower rates evapotranspiration and net photosynthesis. Differences in mean responses of evapotranspiration and photosynthesis were as large as 8 cm and 2 ton C ha-1 yr-1 respectively between simulation runs using LAIs from corrected and uncorrected NDVI.