pyfor

Tools for analyzing aerial point clouds of forest data.

https://github.com/brycefrank/pyfor

Science Score: 10.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
    2 of 6 committers (33.3%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (15.3%) to scientific vocabulary

Keywords

forest-inventory forestry las lidar
Last synced: 6 months ago · JSON representation

Repository

Tools for analyzing aerial point clouds of forest data.

Basic Info
  • Host: GitHub
  • Owner: brycefrank
  • License: mit
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 92.7 MB
Statistics
  • Stars: 95
  • Watchers: 8
  • Forks: 19
  • Open Issues: 10
  • Releases: 0
Topics
forest-inventory forestry las lidar
Created about 9 years ago · Last pushed about 6 years ago
Metadata Files
Readme Changelog License

README.md


pyfor

Documentation | Changelog | Request a Feature | Road Map

pyfor is a Python package that assists in the processing of point cloud data in the context of forest inventory. This includes manipulation of point data, support for analysis, and a memory optimized API for managing large collections of tiles.

Release Status

Current Release: 0.3.6

Release Date: December 1st, 2019.

Release Status: 0.3.6 is an adolescent LiDAR data processing package adequate for single tile processing and large acqusitions.

What Does pyfor Do?

and many other tasks. See the documentation for examples and applications.

What about tree segmentation? Please see pyfor's sister package treeseg which is a standalone package for tree segmentation and detection.

Installation

miniconda or Anaconda is required for your system before beginning. pyfor depends on many packages that are otherwise tricky and difficult to install (especially gdal and its bindings), and conda provides a quick and easy way to manage many different Python environments on your system simultaneously.

As of October 14th, 2019, we are proud to announce that pyfor is available on conda-forge, greatly simplifying the installation process:

conda install -c conda-forge pyfor

Collaboration & Requests

If you would like to contribute, especially those experienced with numba, numpy, gdal, ogr and pandas, please contact me at bfrank70@gmail.com

I am also willing to implement features on request. Feel free to open an issue with your request or email me at the address above.

pyfor will always remain a free service. Its development takes time, energy and a bit of money to maintain source code and host documentation. If you are so inclined, donations are accepted at the donation button at the top of the readme.

Owner

  • Name: Bryce Frank
  • Login: brycefrank
  • Kind: user
  • Location: Olympia, Washington

Software for forest biometrics, statistical analysis, lidar processing, and data visualizations.

GitHub Events

Total
  • Watch event: 5
Last Year
  • Watch event: 5

Committers

Last synced: 6 months ago

All Time
  • Total Commits: 508
  • Total Committers: 6
  • Avg Commits per committer: 84.667
  • Development Distribution Score (DDS): 0.026
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
brycefrank b****k@o****u 495
Bryce Frank b****0@g****m 5
bw4sz b****0@g****m 4
Paulo Viana p****v@y****r 2
Anirudh Bagri A****i@D****m 1
Frank f****r@o****u 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 57
  • Total pull requests: 22
  • Average time to close issues: about 1 month
  • Average time to close pull requests: about 3 hours
  • Total issue authors: 10
  • Total pull request authors: 4
  • Average comments per issue: 2.93
  • Average comments per pull request: 0.95
  • Merged pull requests: 19
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • brycefrank (31)
  • bw4sz (14)
  • jfprieur (3)
  • ccimarp (2)
  • EvasiZ (2)
  • Vicent-Ribas (1)
  • DavidEic (1)
  • Crghilardi (1)
  • ignacioi96 (1)
  • Chrissielxj (1)
Pull Request Authors
  • brycefrank (15)
  • bw4sz (4)
  • anirudhbagri (2)
  • paulo9mv (1)
Top Labels
Issue Labels
bug (14) enhancement (13) File I/O (5) normalization (5) documentation (4) rasterization (3) wontfix (3) good-first-issue (3) environment (2) collection (2) testing-suite (2) tree-detection (2) canopy-height-model (2) visualizitaion (1) help wanted (1)
Pull Request Labels
enhancement (1)

Packages

  • Total packages: 2
  • Total downloads:
    • pypi 11 last-month
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 1
    (may contain duplicates)
  • Total versions: 5
  • Total maintainers: 1
pypi.org: pyfor

Tools for forest resource LiDAR.

  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 11 Last month
Rankings
Dependent packages count: 7.4%
Stargazers count: 7.6%
Forks count: 8.6%
Average: 18.1%
Dependent repos count: 22.2%
Downloads: 44.8%
Maintainers (1)
Last synced: 6 months ago
conda-forge.org: pyfor

pyfor processes LiDAR and other point cloud data into useful metrics for forest inventory predictions.

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Stargazers count: 32.8%
Dependent repos count: 34.0%
Forks count: 34.7%
Average: 38.2%
Dependent packages count: 51.2%
Last synced: 6 months ago

Dependencies

environment.yml pypi
  • laspy *
  • laxpy *
  • plyfile *
  • python-coveralls *
  • sphinx_rtd_theme *
setup.py pypi
  • laspy *