If we want to train a model or predict with a trained model we will need input data. ForestForesight has created a lot of features that can be used as input. We will use the ff_sync option or Cyberduck to download
Method 1: Using ff_sync
To use the ff_sync
function, you'll need to have R installed along with the ForestForesight package. Here's how to use it:
# Set your download folder download_folder <- "path/to/your/download/folder" # Choose an identifier (country code, tile ID, or SpatVector) identifier <- "PER" # Example: Peru identifier <- shape # Call the ff_sync function ff_sync( ff_folder = download_folder, identifier = identifier, download_model = TRUE, download_data = TRUE, download_predictions = TRUE, verbose = TRUE )
This will download the preprocessed data, model, and predictions for Peru or for the shape that you selected earlier in Loading the Area Of Interest (AOI) to the specified folder.
Method 2: Using Cyberduck
Cyberduck is a user-friendly FTP and cloud storage browser. Here's how to use it to download the ForestForesight data:
Download and install Cyberduck from https://cyberduck.io/
Open Cyberduck and click on "Open Connection"
Choose "S3 (Amazon Simple Storage Service)" from the dropdown menu
Enter the following details:
Server: http://s3.amazonaws.com
Access Key ID: (leave blank)
Secret Access Key: (leave blank)
More Options > Path: /forestforesight-public
Click "Connect"
You should now see the ForestForesight bucket structure. Navigate to the folders you want:
For preprocessed data: /preprocessed/input/ and /preprocessed/groundtruth/
For models: /models/
For predictions: /predictions/
Find the country or tile you're interested in and download the relevant files by dragging them to a folder on your computer.
Remember that the ForestForesight dataset is large, so downloading might take a while depending on your internet connection and how much data you're fetching.
Both methods will allow you to download the preprocessed data, models, or predictions. The ff_sync
function is more programmatic and can be easily integrated into R workflows, while Cyberduck provides a user-friendly graphical interface for browsing and downloading files manually.
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