Discriminatory development policies have systematically relegated certain populations to undesirable locations including low elevation areas at risk of flooding. As the climate changes, many properties will no longer be inhabitable and others, especially houses in floodplains, will suffer damage due to more frequent and significant flooding. Current U.S. federal policy funds flood risk mitigation measures, such as property acquisition, relocation and retrofitting, however depending on various factors at the sub-county level, these actions can have disproportionate benefit to high income areas and not extend to vulnerable populations. We investigate patterns related to potential disproportionate availability and access to government linked programs, exploring different types of climatic factors using flood insurance claims data from NFIP. Work with the intern will build off existing research on programmatic wide and event specific analysis in the Carolinas to explore patterns that may be of interest specifically to state and county level decision makers to evaluate how communities are benefiting from existing programs and to ensure equity. We plan to publish an event specific research article using high resolution data on the distribution of risks and benefits following a major disaster.

This is an UNPAID research project.

Faculty Advisor

  • Professor: Dr. Carolynne Hultquist
  • Center/Lab: CIESIN
  • Carolynne Hultquist is a Postdoctoral Research Scientist at the Center for International Earth Science Information Network (CIESIN) and the Lamont-Doherty Earth Observatory of Columbia University. Hultquist has 14 years of experience in Geographic Information Systems (GIS) and 10 years experience in large-scale computing for remote sensing and other geospatial data analysis. Hultquist received a PhD in 2019 in geography and social data analytics from the Pennsylvania State University while a member of the Geoinformatics and Earth Observation Lab. Her research focuses on developing computational methods to integrate diverse data and assess flood risk by highlighting the socially vulnerable.

Project Timeline

  • Earliest starting date: 3/1/2022
  • End date: 8/31/2022
  • Number of hours per week of research expected during Spring/Summer 2022: ~10
  • Number of hours per week of research expected during Summer 2022: ~10

Candidate requirements

  • Skill sets:
    • Statistical programming experience (such as in Python or R)
    • Familiarity with geospatial data or techniques preferred
    • Experience and/or interest in disaster risk reduction and/or policy
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Academic Credit Possible: No
  • Additional comments: Given sufficient contributions, involvement in this project may result in co-authorship on an academic research paper.