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Forest Monitoring, Reporting, and Verification; MRV) Expert

Job in Manhattan, Riley County, Kansas, 66502, USA
Listing for: Fao
Full Time position
Listed on 2026-10-30
Job specializations:
  • Research/Development
    Ecology
Salary/Wage Range or Industry Benchmark: 21000 - 31000 USD Yearly USD 21000.00 31000.00 YEAR
Job Description & How to Apply Below
Position: Forest Monitoring, Reporting, and Verification (MRV) Expert
Organizational Setting

Indonesia continues to strengthen its forest and land monitoring systems to support sustainable forest management, climate change mitigation, environmental reporting, restoration planning, and evidence-based decision-making. The Ministry of Forestry, through the Directorate of Forest Resources Inventory and Monitoring (IPSDH), is advancing the development and continuous improvement of national forest monitoring methodologies and systems, including the National Forest Monitoring System (SIMONTANA), the National Forest Inventory (NFI) 2.0, and related monitoring and reporting processes supporting national priorities such as FOLU Net Sink 2030, Nationally Determined Contributions (NDCs), REDD , forest governance, and access to climate finance.

FAO supports these efforts through complementary programmes, including Accelerating Innovative Monitoring for Forests (AIM4

Forests) and the MERANTI Project. AIM4

Forests supports Indonesia in introducing innovative monitoring methodologies and geospatial solutions, improving the availability and interoperability of forest datasets, strengthening MRV and climate‑finance readiness, and developing monitoring approaches that can support ecosystem restoration, and traceability systems for transparent commodities value chains. MERANTI complements these efforts through the strengthening of NFI 2.0, integration of field and remote‑sensing data, quality assurance and quality control, capacity development, and continued enhancement of SIMONTANA.

In this context, the assignment will support coherence and complementarity across these initiatives, particularly where they contribute to strengthening the NFMS, SIMONTANA and related monitoring methodologies and applications.

A key area of technical support is the improvement of land‑cover monitoring and estimation methodologies. This includes strengthening baseline and historical land‑cover information, improving accuracy assessment and uncertainty analysis, and applying statistically robust approaches to estimate areas of forest and land‑cover change. Such improvements are important for national forest monitoring, FOLU‑related reporting, REDD MRV, and emerging climate‑finance mechanisms.

At the subnational level, FAO is supporting the Government of Riau through the GREEN for Riau Initiative under the UN‑REDD Programme. The initiative aims to strengthen the technical and institutional conditions for REDD implementation, including the development of a subnational Forest Reference Emission Level (FREL), forest emission monitoring, activity data and emission‑factor development, data integration, and institutional capacity for MRV. Recent FAO‑supported activities have included technical training on forest data collection and uncertainty assessment and work to strengthen Riau’s subnational MRV system and climate‑finance readiness.

FAO is also supporting Indonesia’s broader forest and landscape restoration agenda through improved restoration planning and monitoring approaches. For example, FAO has introduced SE.PLAN, a spatially explicit restoration planning tool within the SEPAL/Open Foris ecosystem, and also FERM platform for monitoring, data collection and reporting on restoration initiatives. Such approaches provide opportunities to strengthen the link between restoration planning, implementation, and monitoring.

Against this background, FAO Indonesia seeks to engage a Forest Monitoring, Reporting, and Verification (MRV) Specialist for an eleven‑month period to provide technical and strategic advisory support services across the relevant FAO‑supported forest monitoring initiatives and to strengthen coherence between national and subnational monitoring approaches.

The assignment will contribute to…

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