{
  "id": "AIBD-0348",
  "title": "Amazon Mining Watch's convolutional-network detector maps gold-mining scars basin-wide; 496,000 ha of protected and Indigenous lands affected 2018–2025, with no documented enforcement action",
  "summary": "AI mining detector (Earth Genome, Amazon Conservation, Pulitzer Center) maps mining scars basin-wide; 496,000 ha in protected areas 2018–2025 reported Apr 2026; no attributable enforcement event.",
  "date_observed": "2026-04-24",
  "date_basis": "unassessed",
  "date_precision": "unassessed",
  "benefit_status": null,
  "source_collection": null,
  "source_entry": null,
  "account": "Amazon Mining Watch is a public platform built by the Pulitzer Center's Rainforest Investigations Network, Amazon Conservation Association and Earth Genome. In its own words, it leverages artificial intelligence to map the impact of gold mining. Its code repository describes the detector as an ensemble of convolutional neural networks (CNNs) trained on hand-labeled Sentinel-2 patches. The detector is run over the 8.2 million km2 Amazon basin, with detections recomputed yearly for 2018–2025 and quarterly from 2025. The repository reports specificity 0.976 and sensitivity 0.991 on a Venezuelan geographic holdout for the cumulative 2024 detections. Mongabay reported on 24 April 2026, on the platform's quarterly report. That report found about 6,000 hectares of mining deforestation in protected areas and Indigenous territories in the last three months of 2025. It found 496,000 hectares affected between 2018 and 2025. The enforcement operations on record are documented by the same tool maker without any AI role. MAAP #104 (4 August 2019) attributes a 92% fall in gold-mining deforestation at La Pampa to Peru's Operation Mercury of February 2019. That analysis used satellite imagery (ESA, Maxar, Sentinel-1) with no mention of machine learning. No cited source documents an enforcement action taken on an Amazon Mining Watch detection.",
  "category": "general benefit",
  "unexpected": false,
  "purpose": "Automated detection and mapping of artisanal gold-mining scars in satellite imagery. The users are journalists, researchers, civil society and policymakers. The mapping is the intended use.",
  "system": "Amazon Mining Watch gold-mine detector (ensemble of convolutional neural networks on Sentinel-2 imagery)",
  "model_version": "48px_v4.10b-18d-20g-21a-22bc-ensemble (July 2026 production model, per the repository README)",
  "developer": "Earth Genome (model), with Amazon Conservation Association and the Pulitzer Center's Rainforest Investigations Network",
  "deployer": "Amazon Mining Watch partnership (public web platform)",
  "location": "Amazon basin (Brazil, Peru, Guyana, Venezuela and other basin countries)",
  "domain": "Environmental monitoring: illegal gold mining in tropical forest",
  "segment": "Non-profit remote-sensing platform for journalism and conservation",
  "benefit_type": "Improved Knowledge Discovery",
  "taxonomy_note": null,
  "registry_ids": {},
  "ratings": [
    {
      "group": "personal",
      "depth": null,
      "reason": "No individual beneficiary documented."
    },
    {
      "group": "organizational",
      "depth": null,
      "reason": "Journalists and non-governmental organizations (NGOs) use the maps, but no organization's decision is documented as changed by a detection."
    },
    {
      "group": "societal",
      "depth": null,
      "reason": "Basin-wide statistics exist, but no enforcement or policy outcome is attributed to the tool in a cited source."
    }
  ],
  "ai_role": {
    "status": "assessed",
    "statement": "The AI system produces the maps and area statistics themselves. The makers' repository describes an ensemble of convolutional neural networks on Sentinel-2 patches, with reported holdout specificity 0.976 and sensitivity 0.991. Mongabay independently describes the platform as training AI algorithms to recognize mining scars. No cited source links a detection to an enforcement action. Mongabay remarks that the platform is useful for cross-border work, citing 2025 Brazil-Colombia operations on the Pure River. It does not state that those operations used its detections. MAAP's Operation Mercury analysis, by the same maker, used satellite imagery without machine learning."
  },
  "evidence": [
    {
      "kind": "news report",
      "citation": "Malleret, C. (2026). AI tool tracks spread of illegal gold mining in Amazon protected areas. Mongabay, 24 April 2026.",
      "title": "AI tool tracks spread of illegal gold mining in Amazon protected areas",
      "url": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/",
      "date": "2026-04-24",
      "written_by": "independent",
      "quote": "496,000 hectares (1.2 million acres) of Indigenous territories and protected areas were affected by mining between 2018 and 2025."
    },
    {
      "kind": "news report",
      "citation": "Malleret, C. (2026). Same article, method sentence.",
      "title": "AI tool tracks spread of illegal gold mining in Amazon protected areas (method)",
      "url": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/",
      "date": "2026-04-24",
      "written_by": "independent",
      "quote": "Amazon Mining Watch trains artificial intelligence algorithms to recognize mining scars in satellite images."
    },
    {
      "kind": "press release",
      "citation": "Amazon Mining Watch (n.d.). About. amazonminingwatch.org.",
      "title": "Amazon Mining Watch: About",
      "url": "https://amazonminingwatch.org/en/about",
      "date": null,
      "written_by": "makers",
      "quote": "Amazon Mining Watch is a collaborative platform developed through a partnership between the Pulitzer Center's Rainforest Investigations Network, Amazon Conservation Association, and Earth Genome."
    },
    {
      "kind": "other",
      "citation": "Earth Genome (2026). Gold Mine Detector, README (August 2026 updates and Methodology). GitHub repository earthrise-media/mining-detector.",
      "title": "Gold Mine Detector README (Methodology)",
      "url": "https://github.com/earthrise-media/mining-detector",
      "date": null,
      "written_by": "makers",
      "quote": "The mine detector is an ensemble of convolutional neural networks trained to discriminate mines from other terrain using hand-labeled examples in Sentinel-2 L1C imagery."
    },
    {
      "kind": "other",
      "citation": "Earth Genome (2026). Same README, Persistence section, evaluation of cumulative 2024 detections.",
      "title": "Gold Mine Detector README (Persistence)",
      "url": "https://github.com/earthrise-media/mining-detector",
      "date": null,
      "written_by": "makers",
      "quote": "Venezuela holdout: specificity 0.976, sensitivity 0.991"
    },
    {
      "kind": "report",
      "citation": "Finer, M. et al. (2019). MAAP #104: Major Reduction in Illegal Gold Mining from Peru's Operation Mercury. Monitoring of the Andean Amazon Project, Amazon Conservation, 4 August 2019 (no mention of machine learning or AI).",
      "title": "MAAP #104: Major Reduction in Illegal Gold Mining from Peru's Operation Mercury",
      "url": "https://www.maapprogram.org/lapampa_opermercury/",
      "date": "2019-08-04",
      "written_by": "makers",
      "quote": "The gold mining deforestation decreased 92% between 2018 (900 hectares) and 2019 (67 hectares)"
    }
  ],
  "replication": {
    "produced_by": [
      "Free Sentinel-2 imagery composited on Google Earth Engine",
      "Hand-labeled training set of 23,463 patches built from earlier human surveys with journalists",
      "Ensemble CNN detector run over the whole basin yearly and quarterly",
      "Public release of detections and code for journalists and NGOs"
    ],
    "must_hold": [
      "Cloud-free composites over the period monitored",
      "Mining scars visually distinct from sandbars, braided rivers and aquaculture ponds",
      "Continued labeling and corroboration across years to limit false detections",
      "A user, agency or newsroom willing to act on detections, which no cited source documents"
    ],
    "echoes": [
      {
        "date": "2019-08-04",
        "setting": "MAAP #104, La Pampa, Peru: 92% drop in mining deforestation after Operation Mercury, analyzed from satellite imagery without AI",
        "model_version": null,
        "outcome": "unknown",
        "source": "https://www.maapprogram.org/lapampa_opermercury/"
      },
      {
        "date": "2026-04-24",
        "setting": "Quarterly “Panorama” report, Q4 2025: about 6,000 ha of mining deforestation in protected areas and Indigenous territories (Mongabay)",
        "model_version": null,
        "outcome": "recurred",
        "source": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/"
      }
    ]
  },
  "paired_incident": null,
  "headline": "Amazon Mining Watch maps 496,000 ha of mining in protected areas",
  "metric": "496,000 hectares affected between 2018 and 2025",
  "comparator": {
    "against": "hand-labeled Sentinel-2 patches (Venezuela geographic holdout)",
    "before": null,
    "after": "specificity 0.976, sensitivity 0.991",
    "basis": "measured",
    "quote": "For 2024, the last period with confirmed detections at time of writing, the cumulative detections return the following scores with respect to the evaluation locations used above: Venezuela holdout: specificity 0.976, sensitivity 0.991",
    "url": "https://github.com/earthrise-media/mining-detector"
  },
  "later": {
    "status": "persisted",
    "date": "2026-08-01",
    "note": "Earth Genome published a full rebuild of the Amazon Mining Watch models and data in August 2026, continuing the platform after the April 2026 report.",
    "quote": "In August 2026 we published a full rebuild of Amazon Mining Watch models and data, to improve model sensitivity and to account for monitoring conditions on shorter time intervals (especially, increased cloud cover).",
    "url": "https://github.com/earthrise-media/mining-detector"
  },
  "value": null,
  "developer_country": "United States",
  "deployer_country": null,
  "unrated_because": null,
  "brief_notes": null,
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  "revisions": [
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      "date": "2026-10-20",
      "change": "Record drafted from the cited sources.",
      "source": null,
      "editor": "AIBD"
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    {
      "date": "2026-10-21",
      "change": "Added what happened since from the cited sources.",
      "source": "https://github.com/earthrise-media/mining-detector",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.",
      "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Country of the developer added from the organization's own site or a registry.",
      "source": "https://projects.propublica.org/nonprofits/organizations/472935807",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.",
      "source": null,
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
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  ],
  "confidence": "reported",
  "shade": "medium",
  "claim_status": "Independently reported",
  "claim_basis": "Sources: one independent news report, the makers' report, the makers' press release and the makers' other. The cited evidence includes no independent study or report and no finding by a regulator or court.",
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        "review_state": "not_assessed",
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        "value": {
          "kind": "record_fields",
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              {
                "group": "personal",
                "reason": "No individual beneficiary documented."
              },
              {
                "group": "organizational",
                "reason": "Journalists and non-governmental organizations (NGOs) use the maps, but no organization's decision is documented as changed by a detection."
              },
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              }
            ]
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        "review_state": "not_assessed",
        "coverage": "partial"
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        "state": "value_present",
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          "kind": "record_fields",
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        },
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          "kind": "record_fields",
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              },
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                "editor": "AIBD"
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              ]
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                  "outcome": "recurred",
                  "source": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/"
                }
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                "kind": "report",
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          "fields": {
            "summary": "AI mining detector (Earth Genome, Amazon Conservation, Pulitzer Center) maps mining scars basin-wide; 496,000 ha in protected areas 2018–2025 reported Apr 2026; no attributable enforcement event.",
            "account": "Amazon Mining Watch is a public platform built by the Pulitzer Center's Rainforest Investigations Network, Amazon Conservation Association and Earth Genome. In its own words, it leverages artificial intelligence to map the impact of gold mining. Its code repository describes the detector as an ensemble of convolutional neural networks (CNNs) trained on hand-labeled Sentinel-2 patches. The detector is run over the 8.2 million km2 Amazon basin, with detections recomputed yearly for 2018–2025 and quarterly from 2025. The repository reports specificity 0.976 and sensitivity 0.991 on a Venezuelan geographic holdout for the cumulative 2024 detections. Mongabay reported on 24 April 2026, on the platform's quarterly report. That report found about 6,000 hectares of mining deforestation in protected areas and Indigenous territories in the last three months of 2025. It found 496,000 hectares affected between 2018 and 2025. The enforcement operations on record are documented by the same tool maker without any AI role. MAAP #104 (4 August 2019) attributes a 92% fall in gold-mining deforestation at La Pampa to Peru's Operation Mercury of February 2019. That analysis used satellite imagery (ESA, Maxar, Sentinel-1) with no mention of machine learning. No cited source documents an enforcement action taken on an Amazon Mining Watch detection."
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "summary",
            "account"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].autonomy_permissions": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].component_role": {
        "state": "value_present",
        "value": {
          "kind": "text",
          "text": "The models detected mining activity in satellite images and calculated its extent."
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.",
          "record_fields": [
            "system",
            "ai_role"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].deployment_configuration": {
        "state": "value_present",
        "value": {
          "kind": "text",
          "text": "The repository identified the July 2026 production model as 48px_v4.10b-18d-20g-21a-22bc-ensemble."
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.",
          "record_fields": [
            "model_version",
            "system",
            "ai_role"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].inputs_outputs": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].model_name": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].model_version": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "model_version": "48px_v4.10b-18d-20g-21a-22bc-ensemble (July 2026 production model, per the repository README)"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "model_version"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial",
        "display": {
          "answer": "48px_v4.10b-18d-20g-21a-22bc-ensemble.",
          "editor_note": ""
        }
      },
      "systems[].product_name": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "system": "Amazon Mining Watch gold-mine detector (ensemble of convolutional neural networks on Sentinel-2 imagery)"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "system"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].provider": {
        "state": "value_present",
        "value": {
          "kind": "structured",
          "data": {
            "application_developer": "Earth Genome (model), with Amazon Conservation Association and the Pulitzer Center's Rainforest Investigations Network"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Mapped from the existing case description without a new external source review.",
          "record_fields": [
            "developer"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "taxonomy_crosswalks[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "title": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "title": "Amazon Mining Watch's convolutional-network detector maps gold-mining scars basin-wide; 496,000 ha of protected and Indigenous lands affected 2018–2025, with no documented enforcement action",
            "headline": "Amazon Mining Watch maps 496,000 ha of mining in protected areas"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "title",
            "headline"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "version": {
        "state": "value_present",
        "value": {
          "kind": "identifiers",
          "identifiers": [
            "65329a090a51f990f3856c3ff0e717fac09db0cac334467ef2bdf8968a426135"
          ],
          "role": "SHA-256 of normalized original case data"
        },
        "provenance": {
          "kind": "curatorial",
          "basis": "Deterministic content version assigned by the local migration.",
          "record_fields": [],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "complete"
      },
      "workflow": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "account": "Amazon Mining Watch is a public platform built by the Pulitzer Center's Rainforest Investigations Network, Amazon Conservation Association and Earth Genome. In its own words, it leverages artificial intelligence to map the impact of gold mining. Its code repository describes the detector as an ensemble of convolutional neural networks (CNNs) trained on hand-labeled Sentinel-2 patches. The detector is run over the 8.2 million km2 Amazon basin, with detections recomputed yearly for 2018–2025 and quarterly from 2025. The repository reports specificity 0.976 and sensitivity 0.991 on a Venezuelan geographic holdout for the cumulative 2024 detections. Mongabay reported on 24 April 2026, on the platform's quarterly report. That report found about 6,000 hectares of mining deforestation in protected areas and Indigenous territories in the last three months of 2025. It found 496,000 hectares affected between 2018 and 2025. The enforcement operations on record are documented by the same tool maker without any AI role. MAAP #104 (4 August 2019) attributes a 92% fall in gold-mining deforestation at La Pampa to Peru's Operation Mercury of February 2019. That analysis used satellite imagery (ESA, Maxar, Sentinel-1) with no mention of machine learning. No cited source documents an enforcement action taken on an Amazon Mining Watch detection.",
            "replication": {
              "produced_by": [
                "Free Sentinel-2 imagery composited on Google Earth Engine",
                "Hand-labeled training set of 23,463 patches built from earlier human surveys with journalists",
                "Ensemble CNN detector run over the whole basin yearly and quarterly",
                "Public release of detections and code for journalists and NGOs"
              ],
              "must_hold": [
                "Cloud-free composites over the period monitored",
                "Mining scars visually distinct from sandbars, braided rivers and aquaculture ponds",
                "Continued labeling and corroboration across years to limit false detections",
                "A user, agency or newsroom willing to act on detections, which no cited source documents"
              ],
              "echoes": [
                {
                  "date": "2019-08-04",
                  "setting": "MAAP #104, La Pampa, Peru: 92% drop in mining deforestation after Operation Mercury, analyzed from satellite imagery without AI",
                  "outcome": "unknown",
                  "source": "https://www.maapprogram.org/lapampa_opermercury/"
                },
                {
                  "date": "2026-04-24",
                  "setting": "Quarterly “Panorama” report, Q4 2025: about 6,000 ha of mining deforestation in protected areas and Indigenous territories (Mongabay)",
                  "outcome": "recurred",
                  "source": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/"
                }
              ]
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "account",
            "replication"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      }
    },
    "summary": {
      "total": 91,
      "addressed": 91,
      "known": 31,
      "reviewed": 0,
      "record_mapped": 31,
      "not_assessed": 60,
      "complete": false,
      "by_state": {
        "value_present": 31,
        "not_reported": 0,
        "unresolved": 0,
        "not_assessed": 60,
        "not_applicable": 0,
        "withheld": 0,
        "source_unavailable": 0
      }
    }
  }
}