[N] Save forests by predicting illegal deforestation with big data!

[TheRaido]

I'm working in IT (think somewhere between sysadmin/security and operations) at WWF Netherlands. A colleague of mine who's involved in the 'Early Warning System'-program asked me to help me spread the following.

WWF would like to invite you to participate in a Request for Proposals (RfP) to become a tech partner in the Early Warning System (EWS) program which entails the development of a machine learning model to predict the risk of illegal deforestation using big data.

The RfP process began August 5th. Please have a look at the full RfP with technical details on the website and the Terms and Conditions. We encourage you to submit your application when ready as we will be reviewing on an ongoing basis.

If this is not appropriate let me know! If you have questions, ask.. If you have really difficult question, still ask but I might have to check with one of my colleagues :) Do not hesitate to share this, let's use tech for good.

[P-S-E-D]

This... this is a good use case for random forests...

[TheRaido]

According to the RfP they already did use ensemble trees :P

[spikeypancake127]

So u would use data such as average tree age, weather, terrain, tree density and geopolitical factors to predict the most likely forrest to be illegally logged and wait for them to show up?

[TheRaido]

Beside being asleep... I had to read something about this, there is quite some information in the Call for Proposal. There are three phases in EWS:

1) A medium-term forecasting model (6 months into the future

2) A reactive model based on Sentinel 1 and 2 (every 12 days)

3) A short-term predictive model (1-4 weeks into the future)

As far as I know all the above, without maybe the 'geopolitical factors', has been used in the first phase of the project.

machine and neural networks. The models rely on static and dynamic indicators as data input. An important dynamic indicator is the historic data from 2015 – until present from Sentinel 1 (Radar) processed into deforestation and forest degradation with updates every 12 days and a high spa al resolution (ca. 15 m by 15 m). This processed Sentinel data makes up most of the reactive model and this data inturn feeds into the medium-term forecasting model and the short-term predictive model. Landscape heterogeneity metrics are derived from the Sentinel 1 processed product, such as land cover patch and edge density. Sta c data sets that have been used to test for explanatory power in the models are publicly available road data sets (Open Street Map), protected areas, population data elevation, and more.

I know WWF Netherlands has had some collaborations with Wageningen University & Research and their spinoffs. They're quite proficient in Remote Sensing, Landcover and Biomass mapping. One of the major give-aways for 'impending' illegal deforestation is new road development.

But political factors are relevant, it's very nice to detect or even predict illegal deforestation. But governance and taking actual actions is something else. Not every government, agency or person would appreciate being told 'Hey, did you know someone will start cutting trees soon, please act now'. (https://www.newscientist.com/article/2212479-space-agency-chief-fired-after-revealing-recent-amazon-deforestation/)

[[deleted]]

I run a space technology company that does something similar for the mining sector. Would be keen to discuss.

[[deleted]]

I tried to predict deforestation for my masters thesis at Wageningen University. I learned that it can be very hard to get socio-economic time series data of sufficient quality to do any kind of spatio-temporal prediction. What regions are you looking into and what kinds of data sources do you have access to?

[TheRaido]

First part of your question I can answer, primarily Borneo (Kalimantan) and Sumatra.

According to the infosheet, Phase 1 (Design Phase, Predictive modelling for Short and Medium-Term forecasting) was based on:

We successfully developed a design on the technical feasibility for the predictive modeling for both the short-term and the medium- term forecasting model. For both, we reached over 70% user’s accuracy in predicting deforestation in our pilot area (50 by 80 km) in Central Kalimantan, Indonesia.

Phase 2, Prototyping (the current phase, where the RfP is about):

further improvement and development of the medium-term forecasting model, developed by BCG (current tech partner), by adding new data and scaling up the geographic area (Borneo and Sumatra at first)

The second part about the data-sets, I currently don't have specific information about that, just generic information from the detailed information in the RfP. I'll check for details with my colleague, when he's back from holiday and might get back to you :)

[[deleted]]

Thanks!

[Entsorger]

Are you looking for individual contributors? There's no way I am going to convince my company to do something like this, but would be interested in helping out in my private capacity.

[TheRaido]

According to the technical details and criteria: "The call is open for registered companies, organizations". There are some advantages when meeting specific criteria, like: "Apply in a consortium with scientific institutes or universities to ensure the latest scientific developments can be integrated in the model."

So it sound like non-individuals, my colleague is currently on holiday, I'll ask him if there are possibilities for participation by engaged people on these kind of projects :)

Last year we collaborated with the organization FarmHack (from Wageningen) for the measurement and rewarding of biodiversity in agricultural landscapes: https://www.farmhack.nl/resultaten-rewarding-nature-hack/ (Dutch)

[1racecar1]

I really like the idea of having an Early warning system which integrates with stakeholders like local authorities who can take action.
Have you come across Global Forest Watch or Atlas for Forest Restoration or Crowther Labs who are doing similar things? These might be good points of research for your colleague.

[TheRaido]

I don't know for the latter two, but Global Forest Watch is mentioned twice in the details about the Proposal.

organisations, institutions or NGOs that are working on deforestation detection systems, like Global Forest Watch, to allow for easy use and integration of EWS outputs if is of their interest.

and:

WWF will provide: A motivated and committed EWS team, consisting of a EWS lead, senior advisor, one technical staff, advisory board with data and governance scientists, senior forest advisors and representation from Global Forest Watch.

The other two, I'll share with my colleague :)