Aridification and desertification threaten vast territories across Russia, Central Asia, and beyond. The Arid Ring of Eurasia project, led by the Centre for Digital Technologies in Nature-Based Solutions at HSE University, addresses this by turning land restoration into nature-based climate projects (NbCPs) — making tree planting not just an ecological act, but an economically sustainable solution.

Two tracks unite universities, researchers, and businesses. The scientific and educational track engages partner universities in joint research — from field studies on tree survival and growth to digital MRV development — and trains the next generation of climate-economy professionals. The business track guides landowners and investors from feasibility study to verified carbon credits ready for international markets, including CORSIA.

The physical tool is agroforestry — planting drought-resistant trees and shrubs to create windbreaks, stabilize soils, and restore ecosystems. But what makes this scalable is the NbCP framework: it transforms adaptation costs into carbon assets, creating a real economic incentive for large-scale action across countries.

The Centre provides full methodological support across the project cycle. The initiative aligns with the UNCCD and Paris Agreement.

Contact: Anton Fedin, Chief Analyst, Centre for Digital Technologies for Nature-Based Climate Projects, HSE University

afedin@hse.ru, +7(910)479-60-92

HSE Geographers’ Experience

Artificial intelligence and GeoAI are used in HSE University projects to address climate adaptation and mitigation challenges: from automated satellite imagery analysis to natural hazard modelling and the development of new geospatial databases.

In nature-based climate projects, machine learning methods are applied to Earth observation data to identify protective forest belts and assess their condition. For climate risk assessment, ML models are used to model wildfire hazards and permafrost degradation processes based on climatic, environmental, and infrastructure-related predictors.

Another area of focus is the use of large language models for the automated processing of large volumes of textual sources. Large Language Models (LLMs) extract information on hazardous natural events, including their locations, characteristics, and impacts, and transform unstructured text into structured, georeferenced databases.

The presentation is about specific use cases demonstrating how AI and GeoAI can transform heterogeneous satellite, geospatial, and textual data into practical tools for risk assessment, climate planning, and decision-making.

Contact: Tatiana Aniskina, Head of Geodata Centre, HSE University 

taniskina@hse.ru, +7(985)728-64-45

Our programme

The Master's programme in Low Carbon Development trains specialists in the field of climate strategies, policies and projects. Students gain fundamental knowledge of how ecosystems function, as well as skills in applying legal, financial and managerial tools for low carbon development in the corporate and public sectors.

Graduates of the programme will have comprehensive knowledge of modern methods and tools for measuring and monitoring greenhouse gas emissions, and will possess the relevant competencies to develop climate policy measures, implement climate projects and work in carbon markets.

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