New techniques for information extraction from multispectral data require physical modeling to understand the energy transfer at the atmosphere/surface interface and to develop appropriate inversion procedures, in combination with advanced processing techniques. A multi-step procedure is proposed in this work: the first step implies a binary decision about the second step to be applied in each case. If the pixel is considered as being a `pure' pixel, through a spectral/spatial classification procedure based on multiresolution techniques, then numerical inversion techniques, based on a multiple-scattering reflectance model, are used to extract parameters representing specific surface properties, which can only be defined for homogeneous pixels. If the pixel is considered from the first step as being a mixture of different elements, a linear unmixing approach is used to extract the amount of each component. For such heterogeneous pixels, effective values for the parameters are defined. Multiresolution techniques are applied to improve information extraction algorithms. The relation between spectral and spatial integration effects is discussed. Broad-band spectral integration is analyzed taking into account spatial integration over heterogeneous areas. The problem of the spatial scale is also considered, as the development of these techniques is closely related to the spatial/spectral resolution of the data. Applications of these algorithms to AVIRIS/TMS and Landsat TM/NOAA AVHRR data are an illustration of the capabilities and limits of such approaches.