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New York, Los Angeles, and Miami are primate immigrant centers within the U.S. metropolitan system, attracting new immigrant arrivals as well as serving as focal points for internal migrants. Using the segmented assimilation framework as a foundation, this paper emphasizes the role of geography and migration within the assimilation process. Focusing upon selected origin groups, migrant selectivity and the determinants of migration are evaluated and compared, highlighting the differential role of primate centers. While the New York and Miami metropolitan centers clearly dominate Dominican and Cuban migration systems respectively, the role of primate centers is less clear among other national origin groups. [ABSTRACT FROM AUTHOR]

Segmentation and object-oriented processing of single-season and multi-season Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data was utilized for the classification of wetlands in a 1560 km2 study area of north central Florida. This segmentation and object-oriented classification outperformed the traditional maximum likelihood algorithm (MLC) in accurately mapping wetlands, with overall accuracies of 90.2% (single-season imagery) and 90.8% (multi-season imagery), compared to overall accuracies for the MLC classifiers of 78.4 and 79.0%, respectively. Kappa coefficients were over 1.5-times greater for the segmentation/object-oriented classifications than for the MLC classifications, and producer and user accuracies were also higher. The producer accuracies of the segmentation/object-oriented classifications were 90.8% (single-season) and 91.6% (multi-season), compared to 70.6 and 74.4%, respectively, for the MLC classifications. User accuracies were 73.9 and 73.5% for the single-season and multi-season segmentation/object-oriented classifications, respectively, compared to 54.1% (single-season) and 55.0% (multi-season) for the MLC classifications. The use of multi-seasonal data resulted in only a slight increase in overall accuracy over the single-season imagery. This small increase was primarily due to better discrimination of riparian wetlands in the multi-season data. Segmentation and object-oriented processing provides a low-cost, high-accuracy method for classification of wetlands on a local, regional, or national basis. [ABSTRACT FROM AUTHOR]

We review the literature on segmented assimilation and alternative theoretical models on the adaptation of the second generation ; summarize the theoretical framework developed in the course of the Children of Immigrants Longitudinal Study [CILS]; and present evidence from its third survey in South Florida bearing on alternative hypotheses. We find that the majority of second-generation youths are moving ahead educationally and occupationally, but that a significant minority is being left behind. The latter group is not distributed randomly across nationalities, but corresponds closely to predictions based on immigrant parents’ human capital, family type, and modes of incorporation. While it is clear that members of the second generation , whether successful or unsuccessful will assimilate – in the sense of learning English and American culture – it makes a great deal of difference whether they do so by joining the mainstream middle-class or the marginalized, and largely racialized, population at the bottom. Narratives drawn from the ethnographic module accompanying the survey put into perspective quantitative results and highlight the realities of segmented assimilation as it takes place today in U.S. society. [ABSTRACT FROM AUTHOR]