Seasonal Albedo of an Urban/Rural Landscape from Satellite Observations

Abstract

The spatial distribution and seasonal variation of surface reflectance and albedo in a heterogeneous urban/rural landscape (Hartford, Conn.) was examined using 27 calibrated Landsat observations. Atmospheric effects were removed by a target calibration procedure using 22 urban targets (building rooftops and parking lots) whose reflectance has been measured by a radiometer. Landsat bands 4 and 7, representing the visible and near-infrared portions of the spectrum, are calibrated using linear regression analysis to relate the measured surface reflectance of the target to its satellite-observed radiance. The visible and near-infrared reflectance were integrated into a measure of albedo by the use of a weighted average formula which incorporates the spectral reflectivity of the surface of interest and the spectral distribution of solar radiation. Three distinct formulae were employed for vegetated surfaces, nonvegetated surfaces, and snow-covered surfaces. Visible reflectance, near infrared reflectance, and albedo (for both snow-free and snow-cover observations) are presented according to 14 land use/and cover categories. The seasonal analysis (for snow-free observations only) was conducted by fitting periodic curves to the data to derive a 1-yr cycle of reflectance. Mean monthly values of reflectance and albedo were derived from the periodic curves. A diversity of albedo values exist in this type of environment, associated with land cover. Spectral reflectances are significantly different (particularly for vegetation), which precludes estimation of albedo from a single narrowband measurement. Many land-cover categories display a seasonal dependence. The intracategory seasonal differences are of comparable magnitude to intracategory differences. Key factors in determining albedo (and its seasonal dynamics) are 1) the presence (or absence) of vegetation and 2) canopy structure. The effect of snow cover on albedo is not only large, but also highly variable. Snow-cover/snow-free differences range from a few percent (urban land covers) to over 40% (low-canopy vegetation). Key factors appear to be vertical canopy structure and anthropogenic modification.