In order to achieve a better knowledge of the effect of the anthropogenic extents over the environment, extracting reliable and effective information by Earth observations (EOs) is crucial to help developing a sound human–environment interaction (HEI) assessment. In this sense, the use of future hyperspectral sensors for wide area characterization leads to the need of hyperspectral unmixing (HSU) architectures to recognize urban materials and structures. Further, as urban settlements are often characterized by geometrically and spectrally complex scenarios, the nonlinear reflectance interplay among the elements that constitute each scene must be very well detailed and described so that a thorough knowledge of the scenes can be carried out. In this paper, properly set higher order nonlinear mixture models are used to perform an accurate characterization of the anthropogenic settlements in several EO scenes acquired in different continents. Moreover, a brand new index for estimation of urban extents is provided. Experimental results show how the proposed approach is able to deliver accurate and reliable characterization of urban materials and extents.