Multi-resolution integration of land cover for sub-pixel estimation of urban impervious surface and forest cover

A methodology is presented for estimating percent coverage of impervious surface(IS)and forest cover(FC)within Landsat thematic mapper(TM)pixels of urban areas.High-resolution multi-spectral images from Quickbird(QB)play a key role in the sub-pixel mapping process by providing information on the spatial distributions of ISs and FCs at 2.4 m ground sampling intervals.Thematic classifications,also derived from the Landsat imagery,have then been employed to define relationships between 30 m Landsat-derived greenness values and percent IS and FC.By also utilizing land cover/land use classification derived from Landsat and defining unique relationships for urban sub-classes(i.e.residential,commercial/industrial,open land),confusion between impervious and fallow agricultural lands has been overcome.Test results are presented for Ottawa-Gatineau,an urban area that encompasses many aspects typical of the North American urban landscape.Multiple QB scenes have been acquired for this urban centre,thereby allowing us to undertake an in-depth study of the error budgets associated with the fractional inference process.