Raincoat Take-home Exercise

Overview

This is a take-home exercise for Raincoat. In Raincoat, we often work with remote sensing data in order to understand the world around us.

Instructions

• Fork this repository
• Use directory structure prepared for you to implement your solution
• Use Google to find answers to questions you don't know! At the end of the day, this how we solve the problems.
• Describe your approach in a markdown file in the SOLUTION.md file

Review Criteria

We understand that this is a take-home exercise with open-ended questions. We will be evaluating your submission based on the following criteria:

• For more candidates with scientific backgrounds, we will be looking for a strong understanding of the scientific concepts behind the questions. For candidates with more engineering backgrounds, we will focus on a strong understanding of the engineering concepts behind the questions.
• We will be looking for an understanding of the scientific Python ecosystem, including libraries such as xarray, numpy, pandas, scipy, matplotlib, scikit-learn, rasterio, geopandas, shapely, fiona, etc.