udef-arp
UDef-ARP was developed by Clark Labs, in collaboration with TerraCarbon, to facilitate implementation of the Verra tool, VT0007 Unplanned Deforestation Allocation (UDef-A).
Science Score: 36.0%
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○CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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○DOI references
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✓Committers with academic emails
2 of 5 committers (40.0%) from academic institutions -
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○Scientific vocabulary similarity
Low similarity (14.3%) to scientific vocabulary
Keywords
Repository
UDef-ARP was developed by Clark Labs, in collaboration with TerraCarbon, to facilitate implementation of the Verra tool, VT0007 Unplanned Deforestation Allocation (UDef-A).
Basic Info
Statistics
- Stars: 33
- Watchers: 5
- Forks: 16
- Open Issues: 1
- Releases: 6
Topics
Metadata Files
README.md
Unplanned Deforestation Allocated Risk Modeling and Mapping Procedure (UDef-ARP)
UDef-ARP was developed by Clark Labs, in collaboration with TerraCarbon, to facilitate implementation of the Verra tool, VT0007 Unplanned Deforestation Allocation (UDef-A). It is used in conjunction with a raster-capable GIS for input data preparation and output display. Tools are provided for the development of models using the Calibration Period (CAL) and subsequent testing during the Confirmation Period (CNF). Based on these evaluations, the selected procedure uses the full Historical Reference Period (HRP) to build a model and prediction for the Validity Period (VP). The final output is a map expressed in hectares/pixel/year of expected forest loss.
Fitting and Prediction Phases and Chronology of the Testing and Application Stages (VT0007)
Some important points:
- At present, UDef-ARP only supports Windows platforms.
- A Windows installer is available as an alternative to working with the Python code.
- At present, only limited bulletproofing has been done. Please read the UDef-A document carefully regarding required inputs.
- UDef-ARP is still under development. Frequent updates are expected.
Requirements
Operating System
The UDef-ARP is currently operational exclusively on Windows systems.
Dependencies
Hardward Requirements
UDef-ARP was created with open source tools. In the current version, all raster inputs are stored in RAM during processing. Therefore, large jurisdictions will require substantial RAM allocations (e.g., 64Gb). The interface was developed in Qt 5. A minimum screen resolution of 1920 x 1080 (HD) is required. A 4K resolution is recommended.
Conda Environment Setup
Step 1: Download Anaconda
Download and install the latest version of Anaconda from https://www.anaconda.com/download
Step 2: Create a Virtual Environment
Open the Anaconda Prompt. Use the YAML file with the following command to create your virtual environment:
conda env create -f UDef-ARP_conda_env.yml
Activate the environment you just created:
conda activate udefarp
Before You Start
Step 1: Clone or Download the UDef-ARP Folder
Clone the repository or download the folder to your local directory.
Step 2: Open the GUI
1. Use your Python IDE to Open
Open the UDef-ARP.py file using any Python IDE.
2. Use Anaconda Prompt to Open
After activating your environment, change the directory to the folder directory:
cd your_folder_directory
Then, open the UDef-ARP.py file:
Python UDef-ARP.py
Step 3: Prepare Your Data
UDef-ARP accepts raster map data is either a Geotiff “.tif” or TerrSet “.rst” (binary flat raster ) format. Similarly, outputs can be in either format. All map data are required to be on an Equal Area Projection. All map inputs must be co-registered and have the same resolution and the same number of rows and columns.
COPYRIGHT AND LICENSE
©2023-2024 Clark Labs. This software is free to use and distribute under the terms of the GNU-GLP license.
Owner
- Name: Center for Geospatial Analytics
- Login: ClarkCGA
- Kind: organization
- Location: United States of America
- Twitter: ClarkCGA
- Repositories: 1
- Profile: https://github.com/ClarkCGA
Center for Geospatial Analytics at Clark University
GitHub Events
Total
- Create event: 2
- Release event: 2
- Issues event: 17
- Watch event: 8
- Issue comment event: 32
- Push event: 61
- Pull request event: 26
- Fork event: 3
Last Year
- Create event: 2
- Release event: 2
- Issues event: 17
- Watch event: 8
- Issue comment event: 32
- Push event: 61
- Pull request event: 26
- Fork event: 3
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Yao-Ting | 9****o | 154 |
| Andrew Copenhaver | a****r@v****g | 4 |
| tmorganbrown | 1****n | 2 |
| Tammy Woodard | t****d@c****u | 1 |
| Eli Simonson | e****n@c****u | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 26
- Total pull requests: 45
- Average time to close issues: 9 days
- Average time to close pull requests: 2 days
- Total issue authors: 14
- Total pull request authors: 4
- Average comments per issue: 2.73
- Average comments per pull request: 0.56
- Merged pull requests: 40
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 13
- Pull requests: 27
- Average time to close issues: 13 days
- Average time to close pull requests: 2 days
- Issue authors: 10
- Pull request authors: 1
- Average comments per issue: 2.54
- Average comments per pull request: 0.04
- Merged pull requests: 24
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- tawoodard (3)
- Tirtha19 (3)
- rnvllflores (2)
- agcopenhaver (2)
- JohnKilbride (2)
- vannateck168 (1)
- rafaelruas (1)
- gregorywaynepower (1)
- Diego-Barbulo (1)
- desmania (1)
- neurojunior (1)
Pull Request Authors
- YaoTingYao (55)
- tmorganbrown (6)
- agcopenhaver (4)
- ESimonson95 (1)