Four decades of raw satellite archives handed to multimodal agents: top models finish most analyses but stumble on mapping land change
EarthRecord hands multimodal agents the raw 1984–2026 Landsat, MODIS, VIIRS and Sentinel-2 archives of 56 sites, leaving cloud masking and cross-sensor harmonization to the agent, and poses 238 land-change questions. Among twelve models, the four leaders score 81.0% to 85.4% pass3 on the 226 computable and recognition questions; six leading models reach 92.0% on questions computed from record variables but 61.1% on those needing a map from imagery. In instrument pairs, 53.5% of previously right answers follow the altered satellite data into error.