AgriTech USGS LIDAR
A python module for data fetching and preprocessing from a lidar point cloud in a public dataset on Amazon.
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Public dataset on Amazon
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Table of Contents
About The Project
LIDAR systems allow scientists and mapping professionals to examine both natural and manmade environments with accuracy, precision, and flexibility. NOAA scientists are using LIDAR to produce more accurate shoreline maps, make digital elevation models for use in geographic information systems, to assist in emergency response operations, and in many other applications."
Agriculture, for example, 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.
Here's What this module can do:
- Fetch the data using PDAL pipeline
- Preprocess in the way through the pipeline
- .LAZ and .LAS files are served right away in the data folder for you to play with it 😄
A list of commonly used resources that I find helpful are listed in the acknowledgements.
Built With
Resoures that used in this project are :
Getting Started
You can get a local copy up and running follow these simple example steps.
Installation
- Clone the repo
git clone https://github.com/heavye/AgriTech---USGS-LIDAR-Challenge.git
- Install the setup.py
Usage
For more examples, please refer to the Documentation
Roadmap
See the open issues for a list of proposed features (and known issues).
Contributing
Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
License
Distributed under the MIT License. See LICENSE for more information.
Contact
Euel Fantaye - euelfantaye@gmail.com
Project Link: https://github.com/heavye/AgriTech---USGS-LIDAR-Challenge.git