This course introduces learners to the role of data in understanding environmental systems and planetary health, including guiding conservation action. Through a combination of geospatial tools, remote sensing, field-based technologies, and emerging artificial intelligence approaches, learners explore how environmental datasets are collected, analyzed, and applied to real-world challenges.

• Describe how environmental data are generated, organized, and used to understand natural systems and support conservation and planetary health actions from local to global scales
• Identify and access environmental datasets (e.g., GIS, remote sensing, field observations) to explore patterns, trends, and relationships in ecosystems
• Interpret and apply basic geospatial and quantitative reasoning skills to analyze environmental data and investigate conservation-related questions using appropriate digital tools
• Evaluate the strengths, limitations, and appropriate use of technologies such as satellite imagery, drones, and generative AI for environmental monitoring and analysis
• Explain and apply principles of data ethics, governance, stewardship, and responsible use in cross-sector contexts
• Synthesize and communicate data-driven findings using visual, written, or oral formats to support informed decisions and engage with stakeholders
• Demonstrate basic use of geospatial and environmental data tools, Google Earth Engine, to examine and describe patterns in environmental datasets

This course appears on your transcript identically to how it appears on the transcript of an enrolled ASU student who has taken the course on one of ASU's campuses. Course attendance dates will be listed on your transcript. An on-demand course will appear on your transcript in the session you complete the course.

This course satisfies 3 credit hours at Arizona State University. It is strongly encouraged that you consult with your institution of choice to determine how these credits will be applied to their degree requirements prior to transferring your credit.

To be successful in this course, we recommend English language fluency and computer literacy. We also encourage you to make sure your laptop or desktop computer meets the technical requirements.