As the emergence of high spatial resolution (e.g., TM or SPOT) and high temporal resolution (e.g., NOAA AVHRR/METEOSAT) satellite imagery afford opportunities to explore nature-society relationships at spatial scales consistent with social science theory and concepts, as well as the creation of other social science spatial databases, and as advances in GIS provide unprecedented abilities to analyze these data more social scientists are beginning to use these data and technologies. But there still remains a fundamental question for the social sciences: will RSD and GIS affect problem solving and theory development in the social sciences as profoundly as they have the natural and, to a lesser degree, applied sciences?
The challenges to the social sciences are theoretical, empirical, and methodological. For example, now that spatial data are increasing, a series of issues about the methods to best make use of them must be addressed. The subfield of spatial econometrics, for example, is rapidly expanding to meet the needs of modelers, but much more research is needed on spatial estimation tools to test the hypotheses derived from theory. I am a Principle Investigator or Co-Principle Investigator in two large projects, that are involved in an interdisciplinary framework to advance this frontier focused on land-use/land-cover change.
The first is the Southern Yucatán Peninsular Region (SYPR [NASA-LCLUC]) project in cooperation with Harvard Forest and El Colegio de Frontera Sur (Mexico). This interdisciplinary project aims: to understand, through individual household survey work, the behavioral and structural dynamics that influence land managers’ decisions to deforest and intensify land use; model these dynamics and link their outcomes directly to TM imagery through GIS; model from the imagery itself; and, determine the robustness of modeling to and from the RSD. Several critical social science themes are addressed: how can decisions based on market and subsistence be integrated in one model; how robust are decision based models in the face of volatile, exogenous forces; and what is the value added of using GPS and GIS in survey research to investigate how the individual chooses land-use practices and how these explicitly vary over space and time.
The second interdisciplinary project, the Patuxent Watershed of Maryland (EPA/NSF) collaborative with the University of Maryland, focuses on the links and feedbacks between human decisions on land development and ecological consequences. Econometric model predicts the probably of land-use change in the watershed as a function of both economic and ecological spatial variables. These economic models, when linked with any number of ecological models, allows the effects of both direct land-use change through human actions and indirect effects through ecological change to be evaluated. This project is unique in that it is the most spatially explicit and dissaggregated model of individual human behavior that currently merges RSD and GIS in economic modeling.
For a fuller description of these two projects, see Geoghegan et al., (1998). Central to the framework of both of these projects is the attempt to insert human spatial and human-environment processes into our analysis by way of RSD and GIS, not only to provide insights about spatial outcomes but to inform and evaluate the basic theoretical concepts underpinning the substantive questions.
National Research Council, 1998. People and Pixels: Linking Remote Sensing and Social Science. National Academy Press, Washington DC.