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Choices and Principles
Q: Why does Forest Foresight work on a 0.004°x0.004° (about 400x400m) resolution?
A: This was chosen together with our executive partners in Indonesia and Gabon as a workable scale. This means that it is not too large so that it cannot be easily covered in the field and not be too small so that there would be way too many predictions.
Q: Why was six months in the future chosen as the timeline?
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A: An Early Warning System is used as a general term in two instances: to alert before an event happens or to alert as soon as possible when an event has happened. Though the term Early Warning System is used way more often than our Predictive Warning System we have experienced that the term is mostly used to describe the latter (report as soon as possible after the fact). By changing the name of our System we want to differentiate ourselves from that.
Q: Can the predictions be used for monitoring purposes?
A: No, they are predictions and not events that have necessarily already happened. We suggest using an Early Warning System or yearly forest map classification for this purpose. We do develop a risk map along with our binary classification that can be used for risk analysis. However, we have no metrics on accuracy of this risk map, only on the binary classification that is done based on this risk map.
Q: Isn’t it so that with these predictions it could also help people who deforest to find the right areas of deforestation or to avoid patrols that would go to these areas?
A: This is a tough question to answer. We have written a document discussing this here
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Q: Can I use the tool for predictions of other phenomena than deforestation?
A: Yes! the software tool is data-agnostic, meaning that you can change the input features and groundtruth (on which it is trained) to something else and it will always try to predict the groundtruth with the input features. So you can make this anything you like as long as it follows the required data structure as explained here Preprocessing your own datasets .
Q: My question is not here! What to do?
A: Just get in touch! send an e-mail to ff@wwf.nl and we will respond as soon as possible
Technical Questions
Q: What hardware specifications are required to run the Forest Foresight package?
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A: In our experience it is very easy to package and install an R package. Other software packages, as opposed to for instance a python module with all its conflicting dependencieslike python, tend to have more issues with package dependencies and non-flexible memory issues (as opposed to lazy loading in R). We wanted to prevent the need of containerization because this would also increase the required level of programming skills needed to run the package.
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A: We find it more important that the user has full control over the scripts to make it their own than to give the easiest experience possible. For non-technical people we provide the pre-made predictions monthly that can be downloaded with a GUI. Do note that it requires very little scripting skills to get started with building and running a model, as explained here.
Q: what are the predictive features of Forest Foresight?
A: We have quite a few! They can be found on this page.
Q: Do you need to have scripting skills to add new features?
A: No, our package was built data-agnostic. In our case this means that the process will fetch all data from the data input folder, which does not require changing any of the functions or code of Forest Foresight.
Q: What is the license of the Forest Foresight package?
A: At the moment it is distributed under GNU-GPLv3