Synthetic Reflections on Resource Extraction
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866913036160204800 |
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| author | Tammali, Sai Krishna Kumar, Vinaya Böhlen, Marc |
| author_facet | Tammali, Sai Krishna Kumar, Vinaya Böhlen, Marc |
| contents | This paper describes how AI models can be augmented and adapted to interpret landscapes. We present the technical framework of a Sentinel-2 satellite asset interpretation pipeline that combines statistical operations, human judgment, and generative AI models to produce succinct commentaries on industrial mining sites across the planet. To this end we introduce a novel bespoke landscape descriptor, the Urban Dwelling and Mining Index, and discuss how this metric can improve the performance of a multimodal language model in assessing the spatial distribution of mining operations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_09299 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Synthetic Reflections on Resource Extraction Tammali, Sai Krishna Kumar, Vinaya Böhlen, Marc Computers and Society This paper describes how AI models can be augmented and adapted to interpret landscapes. We present the technical framework of a Sentinel-2 satellite asset interpretation pipeline that combines statistical operations, human judgment, and generative AI models to produce succinct commentaries on industrial mining sites across the planet. To this end we introduce a novel bespoke landscape descriptor, the Urban Dwelling and Mining Index, and discuss how this metric can improve the performance of a multimodal language model in assessing the spatial distribution of mining operations. |
| title | Synthetic Reflections on Resource Extraction |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2602.09299 |