Show how the project develops.
Five milestones make the research process visible—from the first defensible plan to a final paper that integrates technical evidence with environmental policy.
Research proposal
The proposal defines the project before full implementation. It should establish the research question, motivation, literature and policy context, proposed data, research design, and analysis plan. The precise format, scope, and timing will be set with the instructor.
Research Kick-off Report
Due Tuesday, October 20, 2026—one week after Fall Break.
The Research Kick-off Report turns the proposal into evidence that the study can be carried out. It should include:
- a refined research question and concise statement of the policy stakes;
- a focused map of the relevant literature and debate;
- source, license, coverage, unit of observation, and provenance for each dataset;
- a reproducible data intake plus a short data-quality audit;
- at least one research-motivated exploratory figure and, when geography matters, a preliminary map;
- the proposed baseline, any machine-learning extension, the validation design, and the metric—or a reasoned explanation of why machine learning would not help the question; and
- the principal risks, limitations, and next four weeks of work.
The report is a feasibility checkpoint, not a demand for polished results. Its purpose is to expose data, design, and scope problems early enough to solve them.
Progress report
The progress report explains what has been completed and what the work has revealed so far. It should make data preparation and analytical decisions visible, present a coherent sequence of early figures or maps, report baseline and model-validation evidence where appropriate, identify obstacles or limitations, and set out the remaining plan. The precise format, scope, and timing will be set with the instructor.
Final comprehensive exam
There is no midterm exam. The comprehensive final exam evaluates the ability to synthesize and apply the research and data-science methods developed during the course: critique environmental graphics and maps, choose a defensible design and validation strategy, interpret model evidence, distinguish prediction from causal claims, and connect analysis to policy. It will be held during the December 9–15 final-examination period; the exact date, time, and format are TBD.
Research paper
The research paper integrates the complete study: research question, relevant literature and policy context, data, research design, analysis, findings, limitations, and implications. It should include publication-ready static figures, a transparent baseline and question-appropriate model comparison when machine learning is used, and spatial diagnostics when location matters. An interactive map or dashboard may accompany the paper when it adds real analytical value, but it does not substitute for interpretation. The precise format, scope, and timing will be set with the instructor.
Evaluation criteria
| Criterion | What it emphasizes |
|---|---|
| Technical implementation in R | Effective use of data transformation, visualization, spatial analysis, and machine learning |
| Grasp of the research question | Engagement with relevant literature and key debates in environmental and natural resource policy |
| Research paper | Quality of research design, analysis, writing, and integration of findings with the policy context |
| Comprehensive exam | Synthesis and application of research and data-science methods covered during the course |
Grade weights and any due dates not fixed on this site will be established with the instructor and communicated through Brightspace.