MULTIPLE-SCATTERING IN THE REMOTE-SENSING OF NATURAL SURFACES

Radiosity models, working at scales much greater than the wavelength o f light, predict the amount of light scattered many times (multiple sc attering) among scene elements in addition to light interacting with a surface only once (single scattering). Such models are little used in remote-sensing studies because they require accurate digital terrain models and, typically, large amounts of computer time. We have develop ed a practical radiosity model that runs relatively quickly within sui table accuracy limits, and have used it to explore problems caused by multiple scattering in image calibration, terrain correction, and surf ace roughness estimation for optical images. We applied the model to r eal surfaces spatial scales of 30m and 1 cm, separating multiple-scatt ering effects into those resolved by the Landsat TM and unresolved sub pixel effects. Calculated radiosities were used to estimate quantitati vely the magnitude of the multiple-scattering effects for different so lar illumination geometries, surface reflectivities, sky illuminations and surface roughnesses. At the 30-m scale, multiple scattering can a ccount for as much as similar to 10 per cent of the radiance from sunl it slopes, and much more for shadowed slopes; at the 1-cm scale, the m ultiple scattering can locally account for as much as similar to 70 pe r cent. Because the amount of multiple scattering increases with refle ctivity as well as roughness, multiple scattering effects will distort the shape of reflectance spectra as well as changing their overall am plitude. Our results have significant implications for determining ref lectivity and surface roughness in remote sensing and for energy-balan ce calculations.