Fauna & Flora

Business benefits

• PoC showed that remote sensing and machine learning could effectively detect cardamon cultivation in satellite imagery in certain circumstances
• Development of an AI Solution could, in principle, help stop further degradation of the forest that is home to critically endangered species like the western black gibbon

About the project

SoftwareOne's Artificial Intelligence and remote sensing technologies detect unauthorized cardamon cultivation in Vietnam.

Conservation work is a challenging and often thankless task, requiring long treks in difficult terrain and grappling with limited resources while the world's biodiversity continues to shrink. These are just a few of the challenges faced by Fauna & Flora the world's oldest international wildlife conservation organization, established in 1903 to protect the diversity of life on Earth.

In Vietnam, Fauna & Flora faced the challenge of habitat degradation due to cardamon crop planting in protected reserves, particularly in the fragile ecosystem of Mu Cang Chai forest, home to highly endangered primates, including the western black gibbon and the Indochinese grey langur.

Aiforgood Asia, an international NGO focused on AI and technology for environmental and social governance (ESG) projects, approached Fauna & Flora to explore innovative and cost-effective solutions to track changes in the forest and measure the extent of habitat degradation. By mapping the locations most affected by cardamom, Fauna & Flora together with its government partners will be better able to devise and target strategies to reduce the degradation of this most sensitive of habitats.

Aiforgood Asia’s ESG-as-a-Service helps match local NGOs and community leaders with corporations looking to run AI-related ESG projects, leveraging AI and remote sensing technologies to improve health and welfare, reduce inequality, fight climate change, and preserve our oceans and forests.

To address the challenge in Mu Cang Chai forest, Aiforgood Asia partnered with SoftwareOne, an IT service specialist with expertise in data and AI, to develop a Proof-of-Concept (PoC) computer vision-based solution that utilized remote sensing and machine learning to detect cardamon crops in satellite imagery. The PoC was tested in the northern “core” region of the conservation area, with the outcomes evaluated based on feasibility and cost.

The results of the PoC showed that remote sensing and machine learning could, in principle, effectively detect cardamon crops in satellite imagery, providing that the quality of the satellite image was sufficient. This is the first step towards providing Fauna & Flora with a platform that can be scaled to support their conservation activities in the Mu Cang Chai forest and across Vietnam. The study also revealed that the image resolution necessary for detecting cardamon and acquiring ground-truthing data was an essential factor in the cost of the project.

The partnership between Aiforgood Asia and SoftwareOne highlights the potential of AI and remote sensing technologies in supporting conservation efforts and addressing complex environmental challenges. Through ESG-as-a-Service, organizations can collaborate to create innovative solutions that help preserve our planet's biodiversity, protect endangered species, and ensure sustainable development.

The northern “core” region was designated as a test area for the development of a Proof-of-Concept (PoC) computer vision-based solution. The outcomes were evaluated on the investigation of feasibility and cost:

 Feasibility:

• Can cardamon be detected using remote sensing?
• What image resolution is necessary to detect cardamon?

Cost:

• What image resolution is necessary?
• What is the effort needed for acquiring ground truth?

The team faced a significant challenge when they began their project: how to source the most cost-efficient remote sensing data for their model. Their ideal source was Sentinel-2, a satellite constellation launched by the European Space Agency that provides a wide range of services and applications, including agricultural monitoring and emergency management. Images from Sentinel-2 are free to access and have a regular frequency, providing more opportunities to obtain a cloud-free image.

However, it became clear that cardamom production was not visible in low and medium-resolution satellite images, including Sentinel-2 and Landsat. To gather the necessary ground truth data for training their model, the SoftwareOne team had to rely on experts to gather GPS locations of cardamom crops during field expeditions.

Fortunately, the Fauna & Flora team was able to provide ground truth data for the project with the help of a grant from the Darwin Initiative. They used geo-referenced and orthomosaiced drone images gathered during their ground truth expeditions to accurately label the cardamom areas. Data were processed in DroneDeploy software, as part of a partnership with Fauna & Flora.

The team also purchased high-resolution images from EarthImages to train the model on. The Mu Cang Chai forest, where the project was taking place, presented additional challenges, such as frequent cloud cover and the need for ortho-rectifying to ensure the labels were accurate.

To build the model, the team used a U-Net architecture, a widely used classification architecture. They found that the color gradient within the cardamom area was smaller than in other forested areas due to the plants’ size and homogeneous canopy.

About Fauna & Flora

Fauna & Flora is an international conservation charity and non-governmental organization dedicated to protecting the diversity of life on Earth. Fauna & Flora works closely with local conservation partners around the world to save nature, together. Protecting habitats, reviving the ocean, reducing extinctions, stopping illegal wildlife trade, combatting climate change. Using our collective expertise to inspire positive change. Founded in 1903, it is the world's oldest international conservation organization.

Photograph of Western black crested gibbon family: ©Fan Pengfei. Flora & Fauna