The integration of Hyperion and Ikonos imagery are used to differentiate the subtle spectral differences of land-use/land-cover types on household farms in the Northern Ecuadorian Amazon (NEA) with an emphasis on secondary and successional forests. Approaches are examined that include the use of Principal Components Analysis to compress the Hyperion hyperspectral data to its most vital spectral channels; linear mixture modeling to derive subpixel fractions of land-use/land-cover types through the generation of spectral endmembers; and supervised and unsupervised classifications to map forest regrowth, agricultural crops and pasture, and other land-uses on 18 survey farms that are spatially coincident with the imagery. A longitudinal socio-economic and demographic survey (1990 and 1999) is used to characterize household farms; a community survey (2000) is used to assess nearby market towns and service centers; GIS is used to represent the resource endowments of farms and their geographic accessibility. Statistical relationships are examined using Spearman rank correlation coefficients to assess the linkages among a number of selected social, geographical, and biophysical variables and secondary and successional forest on household farms. Relationships suggest the importance of household characteristics, farm resources, and geographic access of secondary forests on surveyed household farms that were previously deforested and converted to agriculture through extensification processes. Results support the integrated use of hyperspectral and hyperspatial data for characterizing forest regrowth on household farms, and the use of multi-dimensional social survey data and GIS to assess plausible causes and consequences of land-use/land-cover dynamics in the NEA.