This project is a USGS Lidar challenge. The client is AgriTech. AgriTech is interested in how water flows through a maize farm field. This knowledge will help us improve our research on new agricultural products being tested on farms How much maize a field produces is very spatially variable. Even if the same farming practices, seeds and fertilizer are applied exactly the same by machinery over a field, there can be a very large harvest at one corner and a low harvest at another corner. We would like to be able to better understand which parts of the farm are likely to produce more or less maize, so that if we try a new fertilizer on part of this farm, we have more confidence that any differences in the maize harvest 9are due mostly to the new fertilizer changes, and not just random effects due to other environmental factors. Water is very important for crop growth and health. We can better predict maize harvest if we better understand how water flows through a field, and which parts are likely to be flooded or too dry. One important ingredient to understanding water flow in a field is by measuring the elevation of the field at many points.
An installable and easy to use python module that contains an implementation for data fetching, loading, transforming, and visualization.