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Open Sustainable Technology

A curated list of open technology projects to sustain a stable climate, energy supply, biodiversity and natural resources.

UDef-ARP

Facilitate implementation of the Verra tool, VT0007 Unplanned Deforestation Allocation.
https://github.com/clarkcga/udef-arp

Category: Biosphere
Sub Category: Deforestation and Reforestation

Last synced: about 15 hours ago
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UDef-ARP was developed by Clark Labs, in collaboration with TerraCarbon, to facilitate implementation of the Verra tool, VT0007 Unplanned Deforestation Allocation (UDef-A).

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 Based on these evaluations, the selected procedure uses the full Historical Reference Period (HRP) to build a model and prediction for the Validity Period (VP).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.

Some important points:

  1. At present, UDef-ARP only supports Windows platforms.
  2. A Windows installer is available as an alternative to working with the Python code.
  3. At present, only limited bulletproofing has been done. Please read the UDef-A document carefully regarding required inputs.
  4. 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.

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Last synced: 7 days ago

Total Commits: 161
Total Committers: 5
Avg Commits per committer: 32.2
Development Distribution Score (DDS): 0.05

Commits in past year: 56
Committers in past year: 3
Avg Commits per committer in past year: 18.667
Development Distribution Score (DDS) in past year: 0.071

Name Email Commits
Yao-Ting 9****o 153
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

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Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 24
Total pull requests: 39
Average time to close issues: 9 days
Average time to close pull requests: 2 days
Total issue authors: 13
Total pull request authors: 4
Average comments per issue: 3.38
Average comments per pull request: 0.64
Merged pull request: 37
Bot issues: 0
Bot pull requests: 0

Past year issues: 16
Past year pull requests: 30
Past year average time to close issues: 9 days
Past year average time to close pull requests: 3 days
Past year issue authors: 10
Past year pull request authors: 3
Past year average comments per issue: 3.5
Past year average comments per pull request: 0.23
Past year merged pull request: 29
Past year bot issues: 0
Past year bot pull requests: 0

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Score: 5.10594547390058