Established foundation
Precision Conservation
Plan conservation practices for water quality and wider landscape benefits.
Environmental science · Geography · Decision science
Md Bodrud-Doza
PhD in Geography · Postdoctoral Scholar
Department of Geography, Environment and Geomatics
University of Guelph, Canada
I study how agricultural landscapes can sustain food production while protecting water, soil, and ecosystems.
I bring together geospatial analysis, environmental monitoring, machine learning, and process-based modelling to understand environmental risks and support better landscape-management decisions.
Research theme
Resilient Agricultural Landscapes
and Sustainable Food Production
From understanding spatial risk to evaluating interventions and building practical decision tools.
- What I study
- Agricultural landscapes · Water quality · Food-system resilience
- How I work
- Monitoring · Geospatial analysis · Machine learning · Modelling
- Why it matters
- Better conservation planning · Resilient landscapes · Informed decisions
Research through REAL Decision Lab
REAL Decision Lab · Developing research program · View current projects →
Emerging methods
Earth Observation & GeoAI
Use Earth observation and GeoAI (AI for geographic data) to understand agricultural and environmental change.
Developing direction
Food-System Resilience
Explore how early stress signals and capacities to absorb shocks can inform timely adaptation.
Updates
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Public writing · Development and Cooperation
More than just survival ↗
My article on protecting livelihoods and addressing salinisation between cyclones in Bangladesh.
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Research story · University of Guelph
Following the Flow: Exploring the Geography of Cleaner Water ↗
A reflection on my doctoral research connecting watershed science, precision conservation, and local knowledge.
Selected publications
Operationalizing precision conservation: Aligning best management practice prioritization with local needs in agricultural watersheds
International Soil and Water Conservation Research · 2026
Contribution: Connects best management practice prioritization with local needs in agricultural watersheds.
Read paper / DOI →Advancing precision conservation through machine learning for field-level prioritization of agricultural best management practices
International Soil and Water Conservation Research · 2026
Contribution: Examines machine learning for field-level prioritization of agricultural best management practices.
Read paper / DOI →Evaluating best management practices for nutrient load reductions in tile-drained watersheds of the Laurentian Great Lakes Basin: A literature review
Science of The Total Environment · 2025
Contribution: Synthesizes evidence on nutrient-load reductions in tile-drained Great Lakes watersheds.
Read paper / DOI →Explore the complete publication record →
Let’s connect research with practice.
I welcome research collaborations, grant development, graduate student research, and applied environmental initiatives.
Collaboration interestsTeaching and mentoring →Google Scholar ↗