Geobosques alerts and paid patrols may have slowed Amazon forest loss

In a randomized trial in 76 Peruvian Amazon communities, deforestation alerts with trained, paid monitors cut forest loss by an imprecise 8.4 ha per community in the first year.

  • 2 society

    Communities in the program lost an estimated 8.4 ha less tree cover each in the first year, about half the control average, though the confidence interval includes zero.

Depth runs from 1, a convenience or time saved, to 5, a life or a livelihood preserved.

Status
Reported and intended benefits.
Evidence

foundstudiedreportedclaimed

An independent peer-reviewed study supports the benefit.

Compared with

37 control communities without the monitoring program. Measured.

The system’s part
Not isolated. The trial compared communities with and without the whole program, which combined alerts with training and paid patrols, so the alerts' own share is not isolated. The paper calls the alerts Landsat-based Global Forest Watch data and does not describe how they are produced or show that a model that learns from data makes them.
Limits
Not yet checked.
Costs and harms
Not yet checked.
Later
Not yet checked.

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Benefit type
Improved Environmental Sustainability
System
Geobosques deforestation alerts based on Landsat-based Global Forest Watch tree cover loss data
Made by
Global Forest Watch (Landsat-based tree cover loss data), delivered through Peru's national Geobosques platform
Used by
Rainforest Foundation US with the indigenous federation ORPIO, in 39 communities in Loreto, Peru
Where
Loreto, Peru (Napo and Amazon river basins)
Stage
In a pilot
Date
, when the source was published
Kind
Aggregate result
Broad benefit
Monitoring Processes, Materials, or Surroundings, Identifying Objects, Actions, and Events
Collections
Cross-border records
Last revised
31 October 2026

Sources

  1. Peer-reviewed study, by authors with no tie to the system.

    Slough T, Kopas J, Urpelainen J. Satellite-based deforestation alerts with training and incentives for patrolling facilitate community monitoring in the Peruvian Amazon. Proc Natl Acad Sci U S A. 2021;118(29):e2015171118. doi:10.1073/pnas.2015171118. The authors declare no competing interest. Rainforest Foundation US designed and ran the program, and no author works for it.

    We estimate a reduction of 8.4 ha per community in the first year (95% CI [-19.4, 2.6]) and 3.3 ha in the second year (95% CI: [-13.6, 7.0]) of monitoring.

Details

AI system

Workflow

Three monitors per community received monthly alerts on a smartphone mapping application. Monitors were trained and paid for monthly patrols, and communities responded directly or by alerting state authorities.

Follow-up

Conditions for replication

Alerts must reach the community in time to act on them. Monitors must be trained and paid to patrol, since the alerts were not tested alone.

Entry details

Sector

Forest protection.

Purpose

Peru's Geobosques platform built its monthly deforestation alerts from Landsat-based Global Forest Watch data to show where tree cover is being lost.

Not yet checked: model, release, provider, role, configuration, inputs and outputs, autonomy, human oversight, AI contribution, beneficiaries, reach, distribution and access, duration, every measurement question, every money question, ownership and control, dependencies, cross-border connections, geopolitical implications, replication attempts, availability, institutional decision, grounds, action and result, success criterion, every evidence question, observed or intended, alternative assessments, related entries, other identifiers, category mappings.

Cite this record

Peter H. Vartanian. (2026). Geobosques alerts and paid patrols may have slowed Amazon forest loss (AIBD-0867). Artificial Intelligence Benefits Database, edition of 31 October 2026. https://petervartanian.xyz/aibd/records/AIBD-0867.html (archived at https://doi.org/10.7910/DVN/AADSII, version 4.0)

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