- Participants at a recent technology summit examined the challenges and opportunities for applying and scaling up emerging technologies to monitoring forests and preventing illegal logging.
- Unmanned aerial vehicles, ground sensors, satellite imagery, and crowdsourcing apps can all empower people to monitor and defend forests in ways that were previously impossible.
- Better information must lead to action, including increasing funding, engaging local communities and governments, communicating results, and understanding the local context to identify and apply the most cost-effective tools.
Forest defenders—from indigenous groups to government authorities—continue to struggle in stopping illegal logging. Faced with scant resources, rampant corruption and vast tracts of difficult terrain to monitor, being an effective forest manager is often an impossible task.
So they’re turning to a growing suite of forest-monitoring technologies. These tools, which are in various stages of development and deployment, are providing bird’s eye forest views and remote detection that was the stuff of science fiction just 10 years ago.
World Resources Institute (WRI)* recently hosted a technology summit, “Perimeter Defense: Innovative Technologies for Detecting and Preventing Illegal Logging”, in San Francisco to examine the challenges of monitoring forests and preventing illegal logging, as well as how to scale up effective deployment of technology. Participants discussed some of the most cutting-edge technologies with current and potential application to forest monitoring, including:
Unmanned Aerial Vehicles (UAVs)
Better known as “drones,” UAVs have endless non-military applications, including wildlife conservation, traffic and natural disaster management, territory mapping and forest carbon stock measurement. Guatemala’s National Council of Protected Areas (CONAP), for example, has been exploring the use of drones to monitor and enhance patrolling of the country’s protected areas. Indigenous communities in Peru and in Guyana, with the help of Digital Democracy, are using drones to map their territory and detect illegal logging and mining activities.
Trailguard and AmbushCam are security systems that use visual and thermal cameras and infrared sensors to capture photos of intruders into protected areas, and immediately transmit these photos to authorities. The devices, which are used for detecting wildlife poachers, are strategically placed at chokepoints and in areas of known traffic and can help authorities to take immediate action.
Similarly, Rainforest Connection has developed an audio detection device from repurposed cellphones and solar panels that can be hidden in tree canopies to pick up errant noises, such as chainsaws, trucks and motorcycles. The device is paired with an alert system that instantaneously notifies users when a suspect noise is detected. The system is still undergoing development, but has shown success in pilot tests in Indonesia, Cameroon and Brazil.
Global Forest Watch, a 60-partner-strong initiative convened by WRI, is an online forest monitoring system designed to improve the accessibility of forest information on a global scale. The premier dataset on GFW comes from satellite data analysis performed at the University of Maryland, detailing annual tree cover change globally at a resolution of 30 meters by 30 meters. GFW then integrates this data with complementary data sets on forest concessions, intact forest locations, and other layers, and allows the public to submit stories from the field. All of these features combined allow anyone with an internet connection to track tree cover change in near-real time.
UrtheCast, a Vancouver-based company, is perhaps best-known for streaming high-definition video of Earth from the International Space Station. However, the company will soon launch a constellation of 16 satellites that, when combined, can see all parts of the globe, even through cloud cover. The data will allow users to see not just forest cover, but also the structure of tree canopy beneath, thus enabling the detection of forest degradation earlier than ever before.
Some initiatives garner the power of the masses to report observations and contribute data, which are then aggregated and used to inform the public or alert authorities. TIMBY, or “This is My Backyard,” is a set of reporting tools first developed to target illegal logging in Liberia. TIMBY’s simple reporting app allows community groups to report illegal deforestation activities and upload images, videos and audio using a smartphone. Stories built from aggregated reports and analysis can then be shared publicly to hold government officials responsible for taking action against illegal loggers.
Moabi, based on OpenStreetMap, is a mapping platform that encourages collaboration across user groups to share and refine spatial data to monitor natural resource use and improve land use planning. The platform, currently focused on the Democratic Republic of the Congo, allows users to access a database of maps, including forest, protected areas, indigenous lands, concessions, roads, and others, and also contribute and edit datasets. Similar technologies allow communities to report illegal logging on their mobile phones.
These technologies can empower people to monitor and defend forests in ways previously impossible. However, as emphasized repeatedly during the recent Perimeter Defense Summit, technology can only be a part of the solution.
Wildtech.mongabay.com aims highlight these and other emerging technologies and their innovative use in forest and wildlife conservation and management, but increased information and transparency is only useful if translated into action.
This requires increasing resources for forest monitoring and enforcement, engaging with local communities and governments, communicating results and ideas to others, and understanding the local context to identify and apply the most cost-effective tools. There is no “one-size-fits-all” solution – technological tools must be adapted to local realities.
*WRI is a partner of wildtech.mongabay.com.