Laboratory

Each afternoon is spent learning-by-doing. Short, hands-on tutorials introduce new techniques, and students immediately translate these to practice. Each week you work closely with a group of peers and our course instructors to design, execute, and present a novel research project. Through this work you will both develop technical skills and gain experience with inferential and exploratory research approaches critical to many large-scale and meta-analytical studies.

Laboratory sessions introduce a range of tools and techniques, including:

• Best practices for data management
• Identifying, querying, and working with open data
• GIS and spatial data
• Scripting and spatial analysis in R
• Geostatistics
• Spatial modeling
• Bayesian methods
• Machine learning
• Interdisciplinary teamwork
• Presentation skills

Although SPATIAL focuses on data use, we also emphasize our dependence on data creation. Lab groups spend a day in the field collecting samples and measure their water isotope ratios with a laser analyzer. Through this we discuss anlaytical technologies, standardization of data and metadata, data archival.