AmpScape

v1.0 generation in progress — shards are being added; index and card finalised on completion. Started 2026-09-15 on Georgia Tech PACE-ICE with streaming upload (each shard is validated, uploaded and checksum-verified before it appears here). Tier order S → M → L → XL → XXL. Until completion, index/<tier>.parquet and splits/full/*.parquet cover the shards uploaded so far and are re-published as tiers grow; the card, the Croissant file and the baseline tables are updated at the end. Pipeline tag: v1.0-pipeline.

AmpScape is a benchmark of circuit-theoretic landscape connectivity solved with the reference solvers Circuitscape.jl 5.17.1 and Omniscape.jl 0.6.2, for training and fairly comparing learned surrogates. Each sample pairs a resistance raster and a source configuration with the exact solver outputs (current-density maps, voltage maps, effective resistances, omnidirectional connectivity).

Honest framing. (1) The solver is the ground truth: outputs are stored raw (float32 maps, float64 effective resistances), never normalised, clipped or post-processed; every sample records solver versions, parameters, timings and residuals. (2) Real landscapes, synthesized resistance: real tiles are genuine covariate stacks (ESA WorldCover, Copernicus DEM, GRIP4 roads, HydroRIVERS, gHM), but the resistance surfaces are produced by resistance tables whose class ordering and term structure follow the literature (Zeller et al. 2012; Cushman et al. 2006; Koen et al. 2014; Spear et al. 2010; Brennan et al. 2022) while the numeric values are AmpScape's own — they are not species-calibrated and must not be read as ecological truth for any taxon. (3) Synthetic landscapes come from neutral landscape models and random fields with documented priors. (4) Omniscape is run with block_size = largest odd ≤ radius/10, a deliberate, documented approximation of the per-pixel (block 1) Omniscape whose fidelity was measured (≈ 2–5 % relative L2 at coarser blocks).

Dataset structure

• data/<tier>/<task_group>/shard-NNNNN.h5 — HDF5 shards, one group per sample, inputs + one configuration each (T1 = pairwise current/Reff, T1W = wall-to-wall, T1R = habitat-patch regions, T3 = advanced source/ground, T4 = Omniscape). Any single tier or task group can be downloaded alone. Schema: docs/schema.md in the code repository.
• index/<tier>.parquet — one row per (sample, configuration): identifiers, family, generator or resistance table, tile, K, placement, solver, timings, residuals, QC flags, split, OOD flags, subset membership (subset_mini, subset_core, subset_full).
• splits/<subset>/<split>.parquet — sample ids; subsets are nested (mini ⊂ core ⊂ full).
• stats/norm_stats.json — train-only normalisation statistics.
• croissant.json — Croissant 1.0 metadata (core + RAI fields).

Tiers: S 128² (100 m), M 256² (100 m), L 512² (200 m), XL 1024² (500 m), XXL 2048² (1 km). This mini release: tier S only, 250 landscapes (200 synthetic, 50 real), 1 270 solved configurations.

Splits and leakage

Real tiles are assigned by spatial macro-cells shared across tiers (equal-width 20° cells, one seeded assignment per cell), so S–XL test regions never overlap S–XL training regions at any resolution; synthetic landscapes by seed family. XXL is test-only and its footprints (2 048 km, 32 tiles covering ≈ 90 % of land) unavoidably overlap finer-tier training cells — for XXL, test_ood_scale therefore isolates resolution transfer, not spatial novelty; this is disclosed here and in the task specification. A strict subset, test_ood_scale_strict (≈ 6 XXL real tiles placed entirely inside non-training cells, zero overlap with any training tile at any tier, verified geometrically), isolates both. Region hold-outs are tile-level: a tile is ood_region when its own biome (Montane Grasslands & Shrublands, Mangroves) or realm (Australasia) is held out. Other OOD sets: held-out resistance table (forest_bird), held-out contrast (10⁶), held-out scale (XL/XXL for models trained ≤ L), and a synthetic→real flag. Pilot caveat: the mini's 50 real tiles over-represent the held-out regions (20 of 50) because the Phase 2 pilot sampled those strata for coverage; this is not a v1.0 property.

Metrics caveat

The domain-level metrics (top-q % high-flow IoU, pinch-point recall, corridor Dice) use thresholds that are not validated against ecological outcomes; we report them as comparative scores between models and make no claim that any level is sufficient for conservation practice.

Redistribution terms and attributions

AmpScape data are released under CC BY 4.0. The covariate channels and the published-resistance evaluation set are derived from the sources below; the sources themselves are not redistributed except where their licence permits and the derived channel is the source itself (the three published resistance rasters, re-tiled). Required attributions:

Source	Licence	Attribution / notice
ESA WorldCover 10 m 2021 v200 (land cover)	CC BY 4.0	© ESA WorldCover project 2021 / Contains modified Copernicus Sentinel data (2021) processed by ESA WorldCover consortium
Copernicus DEM GLO-30 (elevation, slope)	Copernicus WorldDEM-30 licence	"produced using Copernicus WorldDEM-30 © DLR e.V. 2010-2014 and © Airbus Defence and Space GmbH 2014-2018 provided under COPERNICUS by the European Union and ESA; all rights reserved". "The organisations in charge of the Copernicus programme by law or by delegation do not incur any liability for any use of the Copernicus WorldDEM-30".
GRIP4 global roads (distance, class)	stated as CC0 by PBL; catalogued as CC BY 4.0 elsewhere — attributed	Meijer et al. 2018, Environ. Res. Lett. 13:064006; PBL Netherlands Environmental Assessment Agency (GRIP4)
HydroRIVERS v1.0 (river distance, order)	CC BY 4.0 (HydroSHEDS licence)	Lehner & Grill 2013, Hydrol. Process. 27:2171–2186; www.hydrosheds.org
gHM v1 (human modification)	CC BY 4.0	Kennedy et al. 2019, Glob. Change Biol. 25:811–826; figshare 10.6084/m9.figshare.7283087
RESOLVE Ecoregions 2017 (stratification only; no raster stored)	CC BY 4.0	Dinerstein et al. 2017, BioScience 67:534–545
Eurac Alps landscape permeability (test_ood_published)	CC BY 4.0	Marsoner, Simion, Giombini, Egarter Vigl (Eurac Research) 2022, Zenodo 10.5281/zenodo.6602481
Northern raccoon resistance, Europe (test_ood_published)	CC BY 4.0	figshare 10.6084/m9.figshare.27311484.v1
Hawaiian gallinule resistance layers (test_ood_published)	CC0 1.0	Dryad 10.5061/dryad.p90b87p; paper 10.1002/ece3.4296

Not used and not redistributed: WDPA (restrictive terms), OpenStreetMap (ODbL). Synthetic landscapes are generated by AmpScape code (MIT). Solver outputs are produced by Circuitscape.jl 5.17.1 and Omniscape.jl 0.6.2 (MIT). The one unresolved point is the exact GRIP4 licence statement (CC0 vs CC BY 4.0 across catalogues); AmpScape attributes it and stores only non-reversible distance/class rasters. See docs/licenses.md in the code repository for the full verification log.

Collection process, preprocessing, uses, limitations, ethics, maintenance

To be completed for the full release from docs/dataset_plan.md, docs/licenses.md (upstream attributions and the Copernicus WorldDEM-30 notices, which are reproduced verbatim in LICENSE-DATA) and the generation statistics. Protected-area (WDPA) data are not used. Locations of real tiles are public land-cover/terrain products at ≥ 100 m; no personal data.

Citation

See CITATION.cff. Code: https://github.com/Xyrro/AmpScape (MIT). Data: CC BY 4.0 with upstream attributions.