Two UMD Geography Doctoral students, Ana Sanchez-Rivera and Amanda Hoffman-Hall, recently participated in the 9th Race, Ethnicity, and Place Conference. The conference, co-sponsored by the Texas State and UT-Austin Geography Departments, was held at the Emma S. Barrientos Mexican American Cultural Center in Austin, Texas. The theme of the conference was “Engaged Scholarship: Fostering Civil and Human Rights.” 

Ana Sanchez-Rivera presenting her research at REP 2018Ana Sanchez-Rivera was the recipient of a REP 2018 Early Career Scholar Award. The Early Career Scholar Awards were selected through a competitive process and are given to outstanding graduate students and adjunct or tenure ­track scholars with an active research interest in the conference themes. The Award provided a strong professional development opportunity sponsored by the National Science Foundation for early career academics—meeting experts in the field, interacting with colleagues from other parts of the world, and creating networks and lasting connections. Sanchez-Rivera received free registration and hotel accommodation and special recognition during the conference.

Sanchez-Rivera also presented part of her dissertation research titled "Is it History or is it Place? Exploring How the Construction of Places through History influence identification with a racial/ethnic group in Puerto Rico." Abstract: Research in Puerto Rico, suggests that the historic colonial status has led to whitening strategies. However, they overlook the importance that the narrative of the Island as a “racially mixed country” or the “land of the Jibaro” has on this whitening. The study used a mixed methodology from a Social Constructivist ­approach to study the impacts that "technically imposed” places have on identity. Results suggest that narrative governments create around the place (e.g., countries) is an essential aspect to recognize because in PR, what began as an effort for national unity in 1955, has had distinct spatial impacts on the population. The results invite us to consider how created places can be part of oppressive structures of power or tools to educate the population and catalyze social integration to historically marginalized populations especially in those suffering from lack acknowledgment of the African heritage



Amanda Hoffman-Hall presented part of her dissertation research titled "Rural Population Mapping at Moderate Spatial Resolutions Using Geospatial Amanda Hoffman-Hall presents her research poster at REP 2018Data Fusion." Hoffman-Hall was selected as the First Place Winner in the Student Poster Competition. She received $350 and special recognition at the conference closing ceremony.

Abstract: Accurate and timely population distribution maps are critical to addressing health epidemics, coordinating natural disaster response, tracking global changes for environmental conservation, addressing human rights issues, and more. The satellite remote sensing community has made great strides in mapping populations – previously unattainable without conducting a resource intensive census. While great advances have been made in urban population mapping, large gaps still exist for rural and remote populations. These isolated groups tend to be the most vulnerable to environmental, economic, and socio­political change. Moderate resolution remote sensing data, such as Landsat, has generally been viewed as not sufficient for rural mapping given its coarseness. However, rural settlements can be mapped by combining Landsat data with freely available auxiliary geospatial data sensitive to regionally specific characteristics in a machine learning methodology. This paper presents an approach to detecting small rural settlements within Ann Township of Rakhine State, a remote region of Myanmar. Political unrest and limited resources have made census data collection in Rakhine State extremely challenging, leading to large uncertainties in population estimates as well as the distribution of population across the landscape. The resultant map has a classification accuracy of 86.5% on a per­ pixel basis and 93.1% on a location identification basis. Numerous small settlements (on the order of 2-3 structures in some cases) not previously mapped by other datasets are identified, revealing that the population of Ann Township is far more dispersed and isolated than previously mapped. This study concludes that by incorporating regionally specific characteristics, moderate resolution remotely sensed data can successfully map geographically marginalized communities so that services and aid are better able to reach them.

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