Using a data cube to monitor forest loss in the Amazon

Forests maintain an enormous quantity of Earth’s terrestrial carbon and play an essential function in offsetting anthropogenic emissions of fossil fuels. Since 2015, the world’s tropical forests may be noticed commonly at an unprecedented six to 12 day interval due to the Copernicus Sentinel-1 mission.

Hundreds of thousands of gigabytes of artificial aperture radar (SAR) information are acquired each day and night time, no matter cloud cover, haze, smoke or aerosols, permitting deforestation and forest degradation to be monitored at the least biweekly.

The problem, nevertheless, lies find sufficient strategies to extract significant indicators of forest loss from the huge quantities of incoming radar information, such that anomalies within the time-series may be commonly and persistently detected throughout tropical forests.

Such forest-monitoring strategies ought to be clear and simply comprehensible to the broader public, enabling confidence of their use throughout varied private and non-private sectors.

The Sentinel-1 for Science: Amazonas mission presents a easy and clear strategy to utilizing Sentinel-1 satellite radar imagery to estimate forest loss. The mission makes use of a space-time information dice design (also referred to as StatCubes), the place statistical data related to determine deforestation is extracted at every level within the radar time-series.

With this strategy, the mission demonstrates the usage of Sentinel-1 information to create a dynamic deforestation evaluation over the Amazon basin. The staff had been in a position to detect forest lack of over 5.2 million hectares from 2017 to 2021, which is roughly the scale of Costa Rica.

Neha Hunka, distant sensing knowledgeable at Gisat, commented, “What we’re seeing from space is over 1,000,000 hectares of tropical moist forests disappearing annually within the Amazon basin, with the worst 12 months being 2021 in Brazil. We are able to monitor these losses and report on them transparently and persistently each 12 days henceforth.”

Billions of pixels from the Sentinel-1 satellites from early-2015 to December 2021, every representing a 20 x 20 m of forest, are harmonized beneath the StatCubes design, and a easy thresholding strategy to detect forest loss is demonstrated within the first model of the outcomes.

The biggest problem within the mission was the huge quantity of knowledge dealing with and processing. The staff used a number of user-friendly software program instruments to entry the information effectively—processing over 450 TB of knowledge to create the forest loss maps.

Anca Anghelea, open science platform engineer at ESA, added, “By offering open entry information and code by ESA’s Open Science Information Catalog, and openEO Platform, we goal to allow researchers around the globe to collaborate and contribute to the development of information about our world forests and the carbon cycle.

“Thus, within the final phase of the mission, a key focus will probably be on Open Science, reproducibility, long-term upkeep and evolution of the outcomes achieved within the Sentinel-1 for Science: Amazonas Venture.”

Following on from the mission, the following aim is to attain a product of carbon loss from land cowl modifications, working along with ESA’s Local weather Change Initiative staff—a aim that may contribute to ESA’s Carbon Science Cluster.

The present outcomes of the mission at the moment are out there by clicking here. Sentinel-1 for Science Amazonas is applied by a consortium of 4 companions—Gisat, Agresta, Norwegian College of Life Sciences and the Finnish Geospatial Analysis Institute. The staff uniquely combines complementary and powerful backgrounds in forestry and carbon assessments, multi-temporal SAR evaluation and information fusion, and large-data processing capabilities.