https://github.com/ocsmit/canoclass

Open source canopy classification system
https://github.com/ocsmit/canoclass

canopy gdal gdal-python gis landcover-classification remote-sensing

Last synced: 2 months ago
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Open source canopy classification system

• Host: GitHub
• URL: https://github.com/ocsmit/canoclass
• Owner: ocsmit
• License: gpl-3.0
• Created: 2020-01-27T00:06:32.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2021-09-27T14:46:02.000Z (over 3 years ago)
• Last Synced: 2024-06-05T19:26:52.258Z (8 months ago)
• Topics: canopy, gdal, gdal-python, gis, landcover-classification, remote-sensing
• Language: Python
• Homepage:
• Size: 170 KB
• Stars: 7
• Watchers: 1
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# CanoClass

[![Documentation Status](https://readthedocs.org/projects/canoclass/badge/?version=latest)](https://canoclass.readthedocs.io/en/latest/?badge=latest)

[CanoClass gislab](https://gislab.isnew.info/open_source_canopy_classification)

## Overview

`CanoClass` is a python module created to process large amounts of NAIP

imagery and create accurate canopy classifications in an open source

framework. Need for an open source classification system arose during the

creation of the Georgia canopy dataset as tools that were being used

, ArcMap and Textron's Feature Analyst, will be phased out within the next

few years. Additionally need for open source arose out of the lack of

insight to the algorithms that were being used by the software to

process our data and no true method to tweak it to suit our needs.

At its core CanoClass is optimized to to solve canopy classification problems.

It is designed to be data agnostic with batch processing functions created to work with NAIP imagery, as scalable processing for NAIP imagery is necessary. 

## Dependencies

- GDAL 

- NumPy

- Scikit-learn

- Rindcalc

## Examples

![NAIP_CANOCLASS](https://user-images.githubusercontent.com/55674113/88116578-d8b4b880-cb86-11ea-8a3b-7dd43bf5a0d0.png) 

![ET_CANOCLASS](https://user-images.githubusercontent.com/55674113/88116531-be7ada80-cb86-11ea-85fb-a2c9777142a7.png)

## References

### Conference Proceedings

Owen Smith, Huidae Cho, August 2021. An Open-Source Canopy Classification System Using Machine-Learning Techniques Within a Python Framework. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLVI-4/W2-2021, 175–182. [doi:10.5194/isprs-archives-XLVI-4-W2-2021-175-2021](https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-175-2021).

### Conference Presentations

Owen Smith, Huidae Cho, September 30, 2021. [CanoClass: Creation of an Open Framework for Tree Canopy Monitoring](https://callforpapers.2021.foss4g.org/foss4g2021/talk/ZAXQUS/). Free and Open Source Software for Geospatial (FOSS4G) 2021 Conference. The Open Source Geospatial Foundation (OSGeo). Online.