angelini75

Marcos Angelini

Marcos Esteban Angelini, PhD

Contact Information

Professional Narrative

With over 20 years of international experience, my career has been dedicated to advancing sustainable land management through innovative soil science, digital soil mapping, and remote sensing technologies. I earned my PhD from Wageningen University and ISRIC–World Soil Information in 2018, specializing in Structural Equation Modelling (SEM) for digital soil mapping. My research was recognized internationally when awarded the prestigious “Best Paper in Pedometrics” by the International Union of Soil Sciences.

Throughout my career, I have thrived in diverse international environments, leading multidisciplinary teams and fostering strategic partnerships. At the FAO, I have coordinated and contributed significantly to global initiatives such as the Soil Atlas of Asia, GSNmap, GBSmap, and the SoilFER project. My leadership in these projects has enabled the creation and improvement of national soil information systems across Asia, Central America, and the Caribbean. I have personally facilitated numerous workshops and trainings, notably in Bhutan, Vietnam, Guatemala, Honduras, and Trinidad & Tobago, directly impacting local capabilities in digital soil mapping, soil data management, and sustainable agricultural practices.

Recently, I have been leading the development of a novel AI‑powered decision support system that integrates soil spatial data with artificial intelligence to deliver actionable insights to farmers, advisors, and policymakers. This initiative, currently under the prototype stage, leverages cloud‑based geospatial platforms, national soil maps, and Large Language Models (LLMs) with Retrieval‑Augmented Generation (RAG) capabilities to provide natural‑language responses to soil management questions. By transforming complex environmental data into clear, location‑specific advice, this project enhances accessibility, decision‑making, and capacity in sustainable land management. The platform is being piloted with 13 countries in Asia and 8 in the Caribbean and is poised for broader application.

My global engagements have consistently emphasized collaboration with stakeholders from government ministries, international NGOs, and research institutions. Notably, my contributions include:

One of the most memorable and impactful professional experiences was organizing the Soil Information Systems workshop in Bhutan. I coordinated every detail—from agenda design and trainer coordination to visa & travel logistics for delegates from all 13 AFACI countries—and represented the Global Soil Partnership in high‑level meetings (including FAO’s DG Representative and EU donor delegates). The gratitude expressed by participants highlighted my solution‑oriented mindset and pragmatic approach under pressure.

Driven by a passion for sustainable agriculture and environmental stewardship, my mission remains clear: to bridge advanced scientific methodologies with practical, impactful land management solutions, ensuring sustainability and resilience for future generations.

Professional Summary

Core Competencies

Education

Professional Experience

Coordinator, SoilFER Project (Guatemala & Honduras)

FAO – Rome, Italy | 2022–Present

Consultant, Soil Information & Data Management

FAO – Rome, Italy | 2020–2022

Chair, Cartography & Land Evaluation Group

INTA – Argentina | 2018–2021

Postdoctoral Researcher

UMR LISAH – Montpellier, France | 2019–2020

Technical Skills & Key Achievements

Publications and Conferences

📌 Top 5 Selected Publications

Impactful, peer‑reviewed publications highlighting expertise in digital soil mapping, spatial analysis, and sustainable soil management:

  1. Angelini, M.E., Heuvelink, G.B.M., & Kempen, B. (2017)
    Multivariate mapping of soil with structural equation modelling.
    European Journal of Soil Science, 68(5), 575–591.
    • Impact: Awarded “Best Paper in Pedometrics 2017” by IUSS (108 citations).
    • Relevance: Introduces SEM for multi‑property soil mapping.
  2. Heuvelink, G.B.M., Angelini, M.E., Poggio, L., et al. (2020)
    Machine learning in space and time for modelling soil organic carbon change.
    European Journal of Soil Science, 72(4), 1607–1623.
    • Impact: Highly cited (102 citations).
    • Relevance: Applies quantile regression forest for soil carbon forecasting.
  3. Angelini, M.E., Heuvelink, G.B.M., Kempen, B., & Morrás, H.J.M. (2016)
    Mapping the soils of an Argentine Pampas region using structural equation modelling.
    Geoderma, 281, 102–118.
    • Impact: Early SEM application (68 citations).
    • Relevance: Benchmarks large‑scale DSM methods.
  4. Mousavi, S.R., Sarmadian, F., Angelini, M.E., et al. (2023)
    Cause‑effect relationships using SEM for soil properties in arid regions.
    Catena, 232, 107392.
    • Impact: Extends SEM to challenging arid environments (19 citations).
  5. Díaz‑Guadarrama, S., Lizarazo, I., Guevara, M., et al. (2022)
    Improving Latin American Soil Information Database…
    Earth System Science Data Discussions, pp 1–25.
    • Impact: Promotes FAIR data governance.

🎤 Notable Conferences and Workshops (selected)

Professional Memberships & Networks

References

Available upon request.

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