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Perspective on Current Results NSF funded a three year project (#9817743) from 1999 to 2003 (one year no cost extension) to develop a way, using remote sensing, to create an accurate sampling framework to study large urban centers in the developing world. The project used satellite imagery from the early 1980s through 1999 to create a classification system for urban habitation in six cities (Marrakech Morocco, Dakar Senegal, Bamako Mali, Niamey Niger, Dodoma Tanzania, and Gaborone Botswana). The use of multiple images makes it possible to create urban classes such as squatter settlement present in 1982, low income housing present in 1992 but not in 1982, or villas appearing after 1992. Multiple urban classes based on date of appearance and quality of housing plus the ability, using the latest image, to sample from all residential areas and to know how much housing fits into each class makes it possible to design a sampling framework to study an important number of urban issues. The original project was primarily a methodological project designed to see if using this technology we would indeed find strong correlations between quality and date of appearance of housing and a variety of socio-economic variables and environmental concerns. NSF also funded a project conference (#0138217) held in Dakar, Senegal (5-10 January 2002) to which project participants from Morocco, Senegal, Mali, Niger, Tanzania and Botswana contributed papers and powerpoint presentations. In addition a delegation of five senior government figures and university scholars from Mauritania attended and presented an exceedingly well researched powerpoint presentation on Nouakchott focusing on urban growth and environmental issues that was intended to highlight the value of implemting our methodology in Mauritania. Many representatives from various administrative levels (federal and municipal) in Dakar also attended and made presentations. A number of the papers have been published (Lesetedi 2003, Lupalo 2003, Mjahed and Christopherson 2003, Park and Baro 2003, Sardier 2003) but the majority of the power point presentations of GIS results have not yet been reworked into articles. The clear statistical evidence that the core project expectation of a tight relationship between habitation quality, location, and date of construction was not only reasonable but well supported are provided in Park and Baro (2003, this issue). This article asked first if the methodology was accurately picking out housing that had less in-class variation than between class variation (referring to the urban classes developed using satellite imagery). Then it asked if there was nevertheless value in selecting members of each class from a variety of neighborhoods and locales around the city. Using a Kruskal Wallis analysis we concluded that not only were variations in the housing variables (room size, construction material, provision of urban services, rent, number of rooms and other variables) consistently picked up by the classification system but additional variation could be captured within each class by selecting points based on location within the city fabric. Using a similar approach we also examined the degree to which the sampling framework captured homogeneity in a variety of socio-economic variables (income, expenses per capita, monthly expenses, number of persons in the household, ratio of producers to consumers, and others) within each class and across the city. In both the case of the socio-economic variables and the housing variables the probability of the null hypothesis (that the classification system does not effectively group households into homogenous units both in terms of habitation variables and socio-economic ones was extremely small (see Table 1). This paper thus provides the core analysis substantiating the value of the methodology but also supports a secondary component of the methodology which was to not rely entirely on the classification system but to combine it with location so that households in a single habitation class are drawn from the maximal spatial extent of that class in order to capture the full range of variability within the class (Marsh et al 2003, this issue). The small modules on a variety of topics included in the six city surveys were not intended to collect definitive data, in fact they were entirely designed to test the utility of the new methodology. The PI (Park) in conjunction with two graduate students (Mjahed and Cisneros) also created an agent based model (using the modeling software REPAST) to address a question of interest to researchers in Africa: why is there such enormous variation in household size in African cities. The starting premise of this model was that there may be several viable economic strategies within the urban space of African cities and these make it reasonable to have small, intermediate

This paper provides a statistical evaluation of the methodology of the NSF funded Six Cities Project. The project develops a methodology for surveying densely inhabited areas by processing diachronic remote sensing imagery to create habitation strata or urban classes. These classes become part of a sampling strategy which gives every pixel associated with habitation a specified chance of selection and then draws a representative sample of pixels. These pixels become center points for household surveys which can study a variety of issues including health, environment, livelihood strategies, demographics and household labor, expenditures and income. The methodology lends itself to GIS construction and the generation of data that can be easily compared and can be of maximal use to municipalities, governments, scholars and NGOs. It also provides a long term basis for inexpensive surveys that can have a high claim to reliability and representativity. Key words: remote sensing, urbanism, survey methodology, National Science Foundation, health, environment, livelihood strategies, demographic, household labor, expenditures, income, Africa, Middle East, Morocco, Senegal, Mali, Niger, Tanzania, Botswana, Marrakech, Dakar, Bamako, Niamey, Dodoma, Gaborone.

This paper examines rural livelihood systems in Haiti from both a political and ecological perspective. While political developments in Haiti have taken center stage in most analyses, the environmental impacts of population growth, highly varied livelihood strategies, and migration opportunities appear to have played a major role in the current tragic situation. Illegal migration not only seems to alleviate short term poverty but also appears to benefit households long term as revenues from migration improve households' land holding situation. Nevertheless, the steadily declining ecological situation may already be exceeding the creative livelihood strategies of Haitian producers. Key words: Haiti, political economy, political ecology, livelihood strategies, households, livestock, agriculture, migration.