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CanoPy is the Python module for the Georgia Canopy Analysis 2009 project sponsored by the Georgia Forestry Commission (GFC). For further information about this project, please refer to the CanoPy page.

This document outlines the uses and methodology of the functions contained within the CanoPy module. To learn how to use this module, please read the</description>
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This project will improve the speed of flow accumulation.

MEFA



Preliminary results

	*  Systems
		*  Linux 4.14.39 with SSD and 16GB RAM on Yoga 370
		*  ArcGIS on UNG Windows with SSD and 32GB RAM

	*  Data: Texas drain raster from</description>
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Workspace



This project is sponsored by the Georgia Forestry Commission (GFC). The project aims to assess statewide tree canopy coverage using the National Agriculture Imagery Program (NAIP) imagery and machine-learning software. It is a follow-up project to the 2015 statewide canopy assessment project conducted by UNG faculty and students in 2016. We will assess 2009 and 2019 statewide tree canopy and determine canopy changes from 2009 to 2019.</description>
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Reproducibility and replicability

Understanding Reproducibility and Replicability

	*  Reproducible: “Obtaininig consistent results using the same input data; computational methods, and code; and conditions of analysis”
	*  Replicable: “Obtaining consistent results across studies aimed at answering the same scientific question, each of which has obtained its own data</description>
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This page defines the filename and directory naming conventions used in lab repositories. These conventions apply to new repositories and new files. Existing repositories are not retroactively renamed unless there is a strong practical reason to do so.</description>
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Workspace



Abstract from the 25th UNG Research Conference

projects</description>
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