Producing and integrating regional leaf area index (LAI) maps into groundwater recharge assessment models

In this study, leaf area index (LAI) was estimated to produce regional maps using a robust approach from well-calibrated coverages of Landsat-5 TM and Landsat-7 ETM+ imagery. These regional maps were further integrated into groundwater recharge assessment models to propagate LAI retrieval errors. Landsat scenes acquired for Oak Ridges Moraine and Chateauguay regions were geo-referenced and atmospherically corrected. Ground LAI measurements were acquired with a digital hemispherical photography (DHP) technique and processed using CAN-EYE software for selected plots during the growing season. Empirical regressions between measured ground LAI and vegetation indices calculated from the reflectance data were performed to establish equations for LAI retrieval. Furthermore, a 30-meter resolution land cover map was used to produce a single LAI map for different land cover types. Finally, the LAI map was used as an input into groundwater recharge assessment model in order to find its sensitivity to final water budgets.