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ARIES for SEEA Explorer
Artificial Intelligence for Environment & Sustainability (ARIES), developed by researchers at the Basque Centre for Climate Change (BC3), is an integrated, open-source modelling platform for environmental sustainability, where researchers from across the globe can add their own data and models to web-based repositories.
Using ARIES technology, the ARIES for SEEA Explorer application allows users anywhere in the world to produce rapid, standardized, scalable and customizable ecosystem accounts for their area of interest that are consistent with the SEEA Ecosystem Accounting framework. ARIES for SEEA is available on the UN Global Platform, a cloud-service platform supporting international collaboration in the development of official statistics using new data sources and innovative methods.
Easy-to-use and readily available, the ARIES for SEEA Explorer lowers the barriers to compiling ecosystem accounts. The application can generate ecosystem accounts for any user-specified terrestrial area in the world (such as a country, administrative region, watershed, etc.), by using freely available global remote-sensing derived data and models, and rapidly computes these accounts online, using a web browser.
The current Explorer functionalities are restricted to assessing ecosystem 1. extent (based on the IUCN Global Ecosystem Typology), 2. condition (for forest ecosystem types), and 3. selected ecosystem services in physical and monetary units using basic models as a starting point. The outcomes can be analyzed and downloaded to further explore the results (either through a spreadsheet or GIS software).
The Explorer automatically generates a comprehensive ecosystem accounts report, fully documenting the data, models, coefficients and methods used.
Thanks to the use of artificial intelligence (AI) – specifically semantics and machine reasoning – the ARIES for SEEA Explorer automates data and model integration. A core component of ARIES is the use of a set of consistent semantics, which comprise uniform and unambiguous definitions for the data and models involved, and the relationships between them. These semantics are constructed using an intuitive language readable by both people and computers. For example, different datasets and models are consistently labelled with clear, uniform and unambiguous descriptors.
The Explorer thus automates model selection based on a user’s specific request. It chooses the “most appropriate” model for the location, spatiotemporal resolution and account specified (e.g., an ecosystem service or condition account for a given country and year) and depending on the models and data sources accessible to the system