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a python package to easily use, load and visualize lidar data points

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Python package for handling LIDAR data point cloud

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. The USGS recently released high resolution elevation data as a lidar point cloud called USGS 3DEP in a public dataset on Amazon. This dataset is essential to build models of water flow and predict plant health and maize harvest.

the task to produce an easy to use, reliable and well designed python module that domain experts and data scientists can use to fetch, visualise, and transform publicly available satellite and LIDAR data. In particular, your code should interface with USGS 3DEP and fetch data using their API.

Table of contents

General info

the package does the following task

  • Data Fetching and Loading
  • Visualization
  • Data Transformation

Technologies

  • sphinx for docs

Setup:

pip install -i https://test.pypi.org/simple/ lidar-pipeline==0.0.1
git clone https://github.com/sam23121/agritech.git
pip install -r requirements.py
python -m testing

the docs for the package is https://sam23121.github.io/docs/html/index.html

Code Examples

Show examples of usage:

pl = Fetch()
gdf = pl.fetch(polygon, "IA_FullState")

To-do list:

  • improve the modularity
  • let users choose from a list of states
  • adding a TWI column
  • vizuliaze it with more graphs
  • improve the docs

Status

Project is: in progress,

Contact

Created by [@sam23121] - feel free to contact me!

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a python package to easily use, load and visualize lidar data points

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