Table of Contents
CanoPy
CanoPy is the Python module for the Georgia Canopy Analysis 2009 project sponsored by the Georgia Forestry Commission (GFC). To learn how to use this module, please read the user manual and tutorial. For technical details, refer to the technical manual.
Introduction
We developed this module to conduct the Georgia statewide canopy analysis study using the 2009 National Agriculture Imagery Program (NAIP) imagery data. To assess tree canopy, we needed four bands including red (R), green (G), blue (B), and near-infrared (NIR). The three-band RGB NAIP imagery data is available freely online at https://nrcs.app.box.com/v/naip. However, the four-band NAIP imagery is not available online and needs to be purchased from the United States Department of Agriculture (USDA). Since our study is statewide, there are a large number of NAIP quarter quad (QQ) imagery tiles—specifically, 3,913 GeoTIFF files across the entire Georgia—and it would not be feasible to manually pre-process these tiles before we feed them to a canopy classification algorithm. It is not only the number of input tiles, but also the number of output files that makes it challenging to complete this analysis efficiently. This module provides utility functions for pre-processing input tiles and post-processing output files to finally create the final seamless canopy raster for specified physiographic regions.
Documents
Project team
- Huidae Cho, Ph.D., Assistant Professor of Geospatial Science and Computing, IESA, UNG
- Principal investigator
- Python development
- Owen Smith, Undergraduate Student, IESA, UNG
- Python development
- Technical documentation
- Jennifer McCollum, Undergraduate Student, IESA, UNG
- Research about Feature Analyst
- Literature review
- Documentation
Acknowledgement
The work upon which this software is based was funded in whole or in part through an Urban and Community Forestry grant awarded by the Southern Region, State and Private Forestry, U.S. Forest Service and administered by the Georgia Forestry Commission.