Giter Site home page Giter Site logo

smedeiros-academic / mangrove_roughness_2023 Goto Github PK

View Code? Open in Web Editor NEW
1.0 1.0 0.0 972 KB

Processing codes and links to data associated with my paper "Hydraulic bottom friction and aerodynamic roughness coefficients for mangroves in southwestern Florida, USA"

Jupyter Notebook 100.00%
lidar mangroves python tls voxel

mangrove_roughness_2023's Introduction

Hydraulic bottom friction and aerodynamic roughness coefficients for mangroves in southwestern Florida, USA

Journal of Marine Science and Engineering

2023

This repository contains the processing codes used in the above-referenced paper. You should clone the conda environment called 'mangrove' prior to running any of the Jupyter Notebooks for point cloud processing. If you have conda installed on your system, use the command:

conda env create -f environment.yml

The point cloud data are too large to be included in the repository so they can be downloaded at:

https://www.dropbox.com/scl/fi/gxl02oz0ea1d96bbt8mdm/mangrove_roughness_raw_pointcloud_data.tar.gz?rlkey=jgbyyzz9fjc7hswdpygab66q1&dl=0

You can extract the point clouds in your local repository but I recommend first adding *.txt and *.gz to your .gitignore file.

The first step is to process the data using PDAL and the pipeline files provided here. After you have installed PDAL (or cloned the conda environment as descirbed above), the command would look like:

pdal pipeline -i pipeline_CKEY_TLS.json

If you would like to skip these steps and get access to the processed point clouds used for analysis in the paper, you can download them at:

https://www.dropbox.com/scl/fi/pe7f4p8v2ie74kg1s7r05/mangrove_roughness_processed_pointcloud_data.tar.gz?rlkey=cdu0h59wbvneuvh5zdysqyzsg&dl=0

Then, you can run the Jupyter Notebooks to calculate z0 from the processed point clouds (the ones ending in .xyzch):

  • z0_from_TLS-CKEY_max.ipynb
  • z0_from_TLS-IEPK_max.ipynb
  • z0_from_TLS-PKEY_max.ipynb

The Leave-One-Out Cross-Validation procedure for training the random forest with and without the mangrove sites is in Mangrove_LOOCV.ipynb.

Lastly, the notebook used to plot the point cloud figures is z0_Figures.ipynb.

If you use any of the processing scripts, notebooks, or the point clouds, please cite the following paper:

Citation forthcoming...

mangrove_roughness_2023's People

Contributors

smedeiros-academic avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.