Aggregate data and reproducibility code for spatial-support diagnostics in LuTan-1 and Sentinel-1 comparisons with leveling

This dataset contains 57 deidentified aggregate CSV tables and Python standard-library code supporting a fixed-cohort comparison of delivered LuTan-1 and Sentinel-1 time-series products with leveling. The primary comparison retains 20 targets in five survey groups and five 2024 windows at 25, 50 and 100 m extraction radii in eastern Beijing. The tables document spatial-support diagnostics, within-group contrasts, loss decomposition, reference-energy subsets, calendar and projection sensitivity, and anonymous trajectory-deletion summaries. All adverse outcomes and existing aggregate values are retained. Ten replay runners verify released aggregate arithmetic; an additional temporary-copy test confirms that a deliberately corrupted value is rejected. The software reproduces aggregate calculations, not extraction from raw radar products, survey adjustment, calibration independence or physical object correspondence. Conventional per-target RMS is an algebraic rescaling of the contrast-dimension-weighted statistic, not independent evidence. Raw radar exports, survey workbooks, target coordinates, point-level links, source imagery, manuscripts, reviews and credentials are excluded. Group labels and anonymous count/trial identifiers are retained for reproducibility; this is a deidentified release, not a claim that the study region is anonymous. The data and documentation are licensed under CC BY 4.0; Python source code is licensed under MIT. See LICENSE.md for the file-level scope. AI assistance in coding and manuscript preparation is disclosed in AI_Tool_Scope.md. This record supports the manuscript “Lower discrepancy need not indicate better correspondence: spatial support and contrast contraction in LuTan-1 and Sentinel-1 comparisons with leveling”.Funding: Common Application Support Platform for National Civil Space Infrastructure “13th Five-Year Plan” Land Observation Satellites (Grant No. 2017-000052-73-01-001735)