Semi-Automatic Classification Plugin

Semi-Automatic Classification Plugin: A Python tool for the download and processing of remote sensing images in QGIS - Published in JOSS (2021)

https://github.com/semiautomaticgit/semiautomaticclassificationplugin

Science Score: 93.0%

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

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 6 DOI reference(s) in README and JOSS metadata
  • Academic publication links
    Links to: joss.theoj.org, zenodo.org
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
    Published in Journal of Open Source Software

Scientific Fields

Earth and Environmental Sciences Physical Sciences - 40% confidence
Last synced: 6 months ago · JSON representation

Repository

Basic Info
Statistics
  • Stars: 149
  • Watchers: 15
  • Forks: 53
  • Open Issues: 13
  • Releases: 6
Created almost 12 years ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

Semi-Automatic Classification Plugin

SCP The Semi-Automatic Classification Plugin (SCP) is a free open source plugin for QGIS that allows for the supervised classification of remote sensing images, providing tools for the download, the preprocessing and postprocessing of images.

The overall objective of SCP is to provide a set of intertwined tools for raster processing in order to make an automatic workflow and ease the land cover classification, which could be performed also by people whose main field is not remote sensing.

Search and download is available for Landsat, Sentinel-2 images. Several algorithms are available for the land cover classification. This plugin requires the installation of Remotior Sensus, GDAL, OGR, Numpy, SciPy, and Matplotlib. Other dependencies are optional for specific functions. For more information please visit https://fromgistors.blogspot.com .

Plugin installation

The SCP is available for QGIS version 3.x. The SCP is developed with Python 3 and requires the installation of Remotior Sensus, GDAL (OGR), NumPy, SciPy and Matplotlib.

For the installation of QGIS and SCP on different operating systems please follow this guide.

Using the plugin

If you are new to SCP, please follow this tutorial.

Web site

All the SCP information is available from the SCP website.

Documentation

Check the user manual or the online tutorials available.

Videos are also available.

Contributing to the development

If you find some issue that you are willing to fix, code contributions are welcome. Please read the development notes before contributing.

Authors

  • Luca Congedo

License

This plugin is distributed under a GNU General Public License version 3.

How to cite

Congedo, Luca, (2021). Semi-Automatic Classification Plugin: A Python tool for the download and processing of remote sensing images in QGIS. Journal of Open Source Software, 6(64), 3172, https://doi.org/10.21105/joss.03172

DOI

Code on Zenodo

DOI

Owner

  • Name: Luca Congedo
  • Login: semiautomaticgit
  • Kind: user

Environmental engineer, PhD. Developer of the open source Semi-Automatic Classification Plugin for QGIS and Remotior Sensus package Python. Opinions are own.

JOSS Publication

Semi-Automatic Classification Plugin: A Python tool for the download and processing of remote sensing images in QGIS
Published
August 27, 2021
Volume 6, Issue 64, Page 3172
Authors
Luca Congedo ORCID
Independent Researcher
Editor
Kristen Thyng ORCID
Tags
Remote sensing Supervised classification Image processing Land cover

GitHub Events

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  • Create event: 2
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  • Issues event: 23
  • Watch event: 12
  • Issue comment event: 40
  • Push event: 2
  • Fork event: 3
Last Year
  • Create event: 2
  • Release event: 2
  • Issues event: 23
  • Watch event: 12
  • Issue comment event: 40
  • Push event: 2
  • Fork event: 3

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 314
  • Total Committers: 13
  • Avg Commits per committer: 24.154
  • Development Distribution Score (DDS): 0.185
Past Year
  • Commits: 2
  • Committers: 1
  • Avg Commits per committer: 2.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
semiautomaticgit s****r@g****m 256
luca l****a@d****P 25
GITHUBAntoineDENIS 4****S 12
luca l****a@d****s 10
SPeillet p****b@g****m 2
Andrea Giudiceandrea a****a@l****t 2
lim-on-air p****e@g****m 1
enzopolo v****e@g****m 1
Simone Parmeggiani 7****g 1
Sayantan Majumdar m****r@g****m 1
Karthikeyan Singaravelan t****i@g****m 1
Jorge Gustavo Rocha j****r@d****t 1
Donovan Cameron s****n@g****m 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 99
  • Total pull requests: 3
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 3 days
  • Total issue authors: 73
  • Total pull request authors: 1
  • Average comments per issue: 2.25
  • Average comments per pull request: 1.67
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 20
  • Pull requests: 0
  • Average time to close issues: 12 days
  • Average time to close pull requests: N/A
  • Issue authors: 20
  • Pull request authors: 0
  • Average comments per issue: 0.75
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Pull Request Authors
  • agiudiceandrea (3)
Top Labels
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enhancement (8) Mac (4) question (3) invalid (2) wontfix (2) server_issue (1) waiting_feedback (1) bug (1) duplicate (1)
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