CanopyWatch – Enhancing Deforestation Monitoring and Conservation in the Congo Basin using Machine Learning

Application Deadline: February 8

Enhancing deforestation monitoring and conservation in the Congo Basin rainforest through improved detection algorithms, expanded deforestation types, and increased frequency of satellite image analysis. In this 8-week challenge, you will join a collaborative team of 50 AI engineers from all around the world.

The problem

The Congo Basin is home to the world’s second-largest tropical rainforest, spanning 2.5 million square kilometers over six countries. With over 1,000 threatened species, it is also the world’s last tropical carbon sink. Environmental efforts receive up to €300 million per year, but biodiversity loss, deforestation, and carbon emissions continue unabated.

This Omdena-Project Canopy challenge aims to address several critical problems in the Congo Basin rainforest and provide actionable insights for decision-makers. Here are the main issues being targeted:

Biodiversity Loss: The Congo Basin rainforest is known for its exceptional biodiversity, hosting numerous plant and animal species, many of which are found nowhere else on Earth. However, the region is experiencing significant biodiversity loss due to various factors such as habitat destruction, poaching, and illegal wildlife trade. This project seeks to address this problem by providing insights and recommendations to decision-makers on how to protect and preserve the diverse ecosystems and species in the Congo Basin.
Deforestation: Deforestation poses a severe threat to the Congo Basin rainforest. Large-scale clearing of land for agriculture, logging, and infrastructure development is contributing to the loss of forest cover. This not only impacts the ecosystem and biodiversity but also affects local communities that depend on the forest for their livelihoods. The project aims to tackle deforestation by offering insights into sustainable land use practices, reforestation efforts, and policies that can help reduce deforestation rates and promote responsible forest management.
Carbon Emissions and Climate Change: The Congo Basin rainforest plays a crucial role in mitigating climate change as it acts as a carbon sink, absorbing significant amounts of carbon dioxide from the atmosphere. However, deforestation and forest degradation release carbon emissions, contributing to global warming. By addressing deforestation and promoting sustainable practices, the project seeks to mitigate carbon emissions and preserve the Congo Basin rainforest’s role as a vital carbon sink. The insights provided can assist decision-makers in formulating effective climate change mitigation strategies.

The impacts of the project can be significant:

Preservation of Biodiversity: By providing actionable insights, decision-makers can implement conservation measures that help protect the unique and diverse species in the Congo Basin. Preserving biodiversity has ecological, economic, and cultural benefits and contributes to the overall health and resilience of the rainforest ecosystem.
Sustainable Development: The project can guide decision-makers in promoting sustainable development practices in the Congo Basin. Balancing economic activities with conservation efforts can ensure the long-term well-being of local communities while preserving the natural resources they rely on. This can include initiatives such as sustainable agriculture, responsible logging, and eco-tourism, which can provide livelihood opportunities while minimizing negative impacts on the environment.
Climate Change Mitigation: By addressing deforestation and promoting sustainable land use practices, the project can help reduce carbon emissions from the Congo Basin rainforest. This contributes to global efforts in mitigating climate change and meeting targets set under international agreements like the Paris Agreement. Preserving the rainforest’s role as a carbon sink is crucial for maintaining a stable climate and minimizing the impacts of climate change on a global scale.

In summary, this project aims to address biodiversity loss, deforestation, and carbon emissions in the Congo Basin rainforest. By providing actionable insights, decision-makers can implement measures that preserve biodiversity, promote sustainable development, and contribute to climate change mitigation. The impacts of this project include protecting unique species, supporting local communities, and contributing to global efforts in combating climate change.

The project goals

The main goal of the project is to create the next iteration of the Community Deforestation Tracker (CDT), an application that combines satellite imagery and machine learning to detect deforestation in the Congo Basin rainforest, by type of deforestation.

The objectives of this Omdena-Project Canopy Challenge are:

Develop an Advanced Deforestation Tracker System: Utilize satellite imagery and machine learning to accurately detect and categorize types of deforestation in the Congo Basin, including logging, slash-and-burn, mining, and industrial agriculture.
Enhance ML Algorithms for Increased Precision: Improve the precision in detecting logging and slash-and-burn deforestation.
Expand Deforestation Detection: Include additional types of deforestation such as industrial agriculture, mining, and habitations, aiming for over 80% precision and recall.
Improve Algorithms for Cloud-Free Optical Band Imagery: Enhance the methods used to secure and process cloud-free optical band imagery from Sentinel-2.
Develop Automated Imagery Processing Pipeline: Create a pipeline for the automated processing of imagery, increasing the frequency of complete Area of Interest image pulls, with a preference for annual pulls starting from the beginning of Sentinel-2 service in 2016.
Recommend Cost-Effective Display Solutions: Suggest alternatives to the current front-end display service, focusing on cost-effectiveness and user-friendliness.
Increase Final Accuracy with Post-Processing Workflows: Implement workflows to eliminate false positives and distinguish different types of roads using Open Street Map metadata, thereby increasing the accuracy of prediction results.
Integrate SAR Imagery from Sentinel-1: Augment the array of optical band imagery from Sentinel-2 with SAR (radar) imagery from Sentinel-1 to enhance deforestation detection capabilities.

Why join? The uniqueness of Omdena AI Innovation Challenges

A collaborative experience you never had in your working life! For the next eight weeks, you will not only build AI solutions to make a real-world impact but also go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join a global and collaborative team of changemakers. Omdena AI Challenges are not a competition or hackathon but a real-world project that will take your experience of what is possible through collaboration to a new level.