Fall 2016 Colloquium Series
Spatial technologies are not merely impartial and benign tools, but are instead artifacts that embody social and political imperatives and ways of knowing. This has been shown in phenomena from GIS to Big Data, from Google Maps’s search algorithm to Tweets, from securitzed airport spaces to digital neighborhood boundary geometries. Data, software, and hardware reflect social relations, values, hopes, and fears. In recent disaster response efforts such as the 2010 and 2015 earthquakes in Haiti and Nepal, respectively, crowdsourcing, social media, and new mapping platforms - in such contexts commonly called “digital humanitarianism” - were heralded as “revolutionary” to relief efforts, purportedly improving democratic decision-making and empowering citizens. Concurrently, cities, regional planning agencies, and states are opening their spatial datasets to the public under similar discourses and with reference to “transparency” and “accountability”.
In this presentation I draw on ethnographic research conducted 2012-2013 to understand the social and political processes underwriting new uses of spatial technologies and data. I elucidate the politics and struggles around how people, knowledge, and places come to be encoded as data in digital humanitarianism, and the political-economic contexts in which its emergence is situated.
Lastly, building on this research I begin to chart continuities with the “open data” and “smart cities” movements. I will show that many of the lessons from digital humanitarian research can be leveraged to theorize open data and smart cities. As both digital humanitarianism and smart cities increasingly impact socio-spatial relations, it is important for geographers to illuminate their geographies, modalities, and politics.
Arthur Getis Distinguished Lecture Series
Scientists are often beset by lack or paucity of longitudinal data that are essential when dealing with space-time pattern shift. Current space time analysis methods are largely designed for longitudinal data analysis, where the same subjects are measured over multiple times. We develop a unique framework that is empowered to reveal the intrinsic (often hidden) temporal trend behind multi-time, subjects-varying data without spatial or organizational aggregation. This framework starts with a space-time optimization model that generates pseudo-longitudinal data that best fit the empirical statistical distributions of other independently sampled subjects (units) at multiple times. Then the framework employs a latent trajectory modeling (LTM) approach with spatial filters to analyze the so-generated pseudo-longitudinal data, revealing each subject’s (unit) temporal trajectory and potential causes behind such trajectory. This framework builds on the Ghanaian Population and Household Survey (DHS) data collected in 1993, 1998, 2003, 2008, and 2014, each of which features around 1,000 randomly sampled, but temporally-different women. The significance of this research lies in the ease and usefulness of this framework for deciphering the temporal trend and related mechanisms behind such trend based on multi-time, subjects-varying data. Equally useful is this framework’s capability of making use of spatially explicit, yet autocorrelated data, adding a spatial dimension that is seldom available in traditional longitudinal data analysis.
Anthropogenic watershed disturbance by deforestation, agriculture, and urbanization alters sediment loads to nearshore environments, enhancing sediment stress on corals near the outlets of impacted watersheds. Few studies have developed an integrated understanding of sediment sources, transport processes, and deposition in small, reef-fringed embayments and many are outside the scope of local environmental managers in remote islands like at the study site, Tutuila, American Samoa. Integrating field measurements and models of suspended sediment yield from the watershed, water circulation over the reef, and sediment accumulation in traps on the reef showed that the predominant anthropogenic sediment source was a small gravel quarry, and water circulation patterns deflect the flood-supplied terrigenous sediment from the stream over the northern reef where it caused enhanced sediment stress on corals. This work provides an example of how a scientific, process-oriented Ridge to Reef study of sediment dynamics can answer critical scientific and management-oriented questions about the source, transport, and fate of sediment in the near-short environment.
Numerous studies have highlighted that water resources and hydrologic extremes are sensitive to climate change. An interesting research question is what the role of climate change is in occurrence of extreme events. More importantly, how climate extremes may change under future climate conditions and emission scenarios. Therefore, there exists a strong need to study water resources and hydrologic cycle under different climate change scenarios at the global scale. In the past decades, numerous methods and models have been developed for assessing climate change impacts on water resources. However, there are still major research gaps from uncertainties in climate model simulations to limitations in the current large scale water cycle (or global hydrologic) models. Some of the current research gaps include: (I) high uncertainty of climate model simulations; (II) limitations and high uncertainties of the global hydrologic model simulations because of calibration challenges at the global scale; and (III) lack of frameworks for accounting for the local resilience and man-made infrastructure in climate impact assessment studies. The overarching goal of this study is to address the above mentioned research gaps. In this study, several novel evaluation metrics are introduced that can be used for evaluation of errors and biases in input data which is a key factor in the overall uncertainty of climate change studies. Furthermore, this study suggests a better representation of the hydrologic cycle at the global scale through a comprehensive multi-objective calibration framework for global hydrologic models. Then, a modeling framework is presented for accounting for local resilience in climate change studies. Finally, this study outlines a framework for combining top-down and bottom-up approaches for climate change impact assessment.
This talk examines the politics around water supply in California, particularly focusing on the diversion and transfer of water from rural and agricultural areas to urban places. This research has focused on the discourses, policies, and laws that have been used to justify and to contest water transfers and diversions, which can carry externalized social and environmental costs. The research compares three cases of highly contested rural-to-urban water transfers and diversions at three lakes in California— Owens Lake, Mono Lake, and the Salton Sea.
Alida Cantor received her PhD from Clark University in 2016. Her research, grounded in political ecology, focuses on legal and political dimensions of water resources management in California.