Biology: Remote Sensing Data Science Module

Contributors: Andy Bean ('23), May Oo Khine ('23), Emma Nguyen ('25), David Guerra (Professor of Physics, Saint Anselm College), Jay Garaycochea (Professor of Biology, Goucher College), Professor Petra Bonfert-Taylor (Professor of Engineering, DIFUSE PI), and Professor Lorie Loeb (Professor of Engineering, DIFUSE PI)

This module was developed through the DIFUSE project at Dartmouth College and funded by the National Science Foundation award IUSE-1917002.

	This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Module Objective

Provide students an opportunity to create and test a hypothesis about their area of study in land-use or biology without requiring data skills.

Learning Objectives

1. Interpret and describe data detailing biological factors in nature to understand what each value and its units mean in context
2. Create and evaluate a hypothesis about an interaction between land-use data and population data using Principal Component Analysis to reduce factors and then a k-means test to classify groups of data
3. Interpret and draw conclusions from plots of data to make decisions about the trend of a biological interaction, and whether it is beneficial or detrimental

Module Description

These courses intersect in the interactions between anthropological land use and the ecosystems that develop on that land. This module teaches data analysis and visualization on a data set in this domain: land use in Massachusetts, Connecticut, Maryland, and New Hampshire, and basic weather data, White-Tailed Deer Population, and the incidence of Lyme disease. Students are introduced to the data set and the goals of analysis in the pre-lab, and then are walked through the data in table format, map format, and PCA and k-means plots in the main lab assignment. These plots are interactively produced through the use of a Google Colab file running python script, while the lab and pre-lab assignments are Canvas quizzes which live in Canvas Commons.

Schedule and Links

Use this page to get an idea of the timeline of the module, what components are involved, and what documents are related to each component. This is the schedule intended for module deployment by the DIFUSE team, though instructors are welcome to modify the timeline to fit their course environment.

Date	In/Out of Class	Assignment Description	Assignment Files (Linked to Repository Contents)
Day 1	In or out of class	Pre-Lab Assignment: introduction to the data, PCA and K-means analysis	Pre-Lab
Day 2	Start in class, finish out of class	Lab Assignment: analyzing and visualizing data, testing hypothesis and drawing conclusions	Lab

Course Information

Professor Guerra's course, Remote Sensing, introduces students to working with ArcGIS and processing satellite imagery. Professor Garaycochea's course, Explorations in Biology I, introduces students to biological and ecological interactions. These are introductory courses, so no prerequisites are expected of students for this module. Students of PS/CS 211 likely have taken some other computer science classes, and students of BIO 102 may have taken other biology classes.

	This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

For instructors and interested parties, the history of this repository (with detailed commits), can be found here.