The Landsat program provides more than three decades of decameter resolution multispectral observations of the growth and evolution of human settlements and development worldwide. While these changes are often easy to observe visually, accurate repeatable quantification at Landsat's resolution has proven elusive. In part, this is a consequence of the multi - scale heterogeneity and diversity of settlements worldwide. Efforts to map settlement extent are also confounded by the lac k of a single, physically - based, definition of what constitutes urban, suburban, peri - urban and other types of settlement. We attempt to resolve both of these challenges by characterizing built environments in terms of their distinctive physical properties . This can be accomplished by combining multi - temporal optical reflectance with synthetic aperture radar backscatter measurements to identify combinations of physical properties that distinguish built environments from other types of land cover. Three well - known examples include an abundance of impervious surface, persistent deep shadow between buildings and high density of corner reflectors at meter to decameter scales. At optical wavelengths, spectral properties of land cover can be represented using stan dardized spectral endmember fractions to represent combinations of the most spectrally and functionally distinct components of land cover soil and impervious substrates, vegetation, water and shadow. The spectral similarity of soils and impervious substra tes that makes thematic classifications error prone can be resolved by using multi - season composites of spectral endmembers to distinguish spectrally stable impervious substrates from temporally variable soil reflectance resulting from seasonal changes in moisture content (thus albedo) and fractional vegetation cover. By representing the diversity of anthropogenic land use as a continuous mosaic of land cover it is possible to quantify the wide variety of human settlements in a way that is physically consis tent, repeatable and scalable. We propose to develop and test algorithms to combine multi - season Landsat and Sentinel - 2 optical multispectral imagery with SRTM and Sentinel - 1 C - band radar backscatter imagery to produce a continuous Infrastructure Index (II ) to identify and map changes in the extent of anthropogenic built environments (e.g. urban, suburban, exurban, peri - urban) worldwide between 2000 and 2015. Rather than attempting to map specific features associated with built environments (e.g. impervious surfaces, buildings, roads), we will characterize the combined optical and microwave response of a wide range of built environments to identify the physical properties associated with these features (e.g. spectral stability, persistent shadow, anisotropic backscatter intensity). We will then use the most persistent of these properties to derive an index incorporating multiple characteristics measured by both optical and microwave sensors. The index will be calibrated using the full range of properties obse rved in a set of ~20 test sites spanning urban - rural gradients worldwide and vicariously validated using high spatial resolution (1 - 4 m) imagery and the DLR 8 m urban footprint product. As an independent comparison, we will use high resolution (sub - km) cen sus enumerations circa 2000 and 2010 to map changes in population density associated with the mapped changes in the infrastructure index at test sites in the USA, Brazil, Portugal, Malawi, South Africa and Sri Lanka.