================================================================================ SUPPLEMENTARY MATERIAL — PHASE I MASTER CANDIDATE CATALOG New River Valley, Belize — Maya Pottery Sherd Detection Study University of Cincinnati, Department of Geography & GIS Author: Benjamin Britton ================================================================================ ASSOCIATED ARTICLE ------------------ Britton, B. (2026). A Hue-Weighted Two-Phase Workflow for Automated Detection of Maya Pottery Red Sherds in UAV Imagery. Remote Sensing (MDPI). CONTENTS OF THIS ARCHIVE -------------------------- geom4999_enriched.csv 177,148-row Phase I master candidate catalog run_geom_full_4999.py Reproduction script that generated the catalog README_Phase1_Master_Catalog.txt This file WHAT THIS DATASET IS --------------------- geom4999_enriched.csv is the output of the Two-Phase Workflow's Phase I stage: a full geometry-only inference pass across all 100 UAV survey images using a Cascade Mask R-CNN model with ViTDet backbone (checkpoint model_0004999.pth). No chromatic filtering has been applied. This file represents every candidate object the geometric detector found, with all hue and saturation metrics pre-computed and attached. It is the reproducible asset from which the Phase II chromatic filter is applied to yield the final 1,647 detections reported in the article. As noted in the article: any re-parameterization of the Phase II chromatic thresholds can be applied to this 177,148-candidate set in approximately 1.2 seconds per iteration, enabling rapid sensitivity analysis without repeating the computationally intensive inference stage (~14 GPU-hours). PROVENANCE ---------- Dataset: 100-image UAV survey, New River Valley, Belize Sensor: DJI drone, DNG raw imagery, 100 m AGL Image resolution: 5280 x 3956 px Tiling: 512 px tiles, 384 px stride, 128 px overlap Model: Cascade Mask R-CNN, ViTDet backbone Checkpoint: model_0004999.pth (C:/d2/Outputs/output5_pseudo_rgb_transfer/) Confidence threshold: 0.05 (permissive — all geometry candidates retained) No deduplication applied in Phase I (tile-overlap duplicates preserved; cluster density is a quality signal exploited in Phase II scoring) UTM correction: +0.5 px half-pixel centre offset applied to all centroids CRS: EPSG:32616 (UTM Zone 16N, WGS84) Run date: 2026-03-18 Script version: geom_full_4999_v1 COLUMN DEFINITIONS (36 columns) --------------------------------- EVT_Rank Integer rank by Geometric_Score (1 = highest confidence) Object_ID Unique detection identifier (Flight_ID + Tile + Sherd) Flight_ID Source DNG image identifier (e.g. DJI_0016) Tile_Num Tile index within the flight image Sherd_Num Detection index within the tile Combined_Confidence Raw model confidence score (0–1) Gold_Score Composite score: 0.70 × Color_Score_Raw + 0.30 × Geom_Norm Geometric_Score Normalised geometric confidence (0–1) Geom_Norm Geometry score normalised within flight Color_Score_Raw Chromatic similarity score, centred on 32.0° hue Color_Score_Penalized Color score after limestone penalty (hues 40–45°) Hue_Deg Mean hue of detection mask (degrees, 0–360) Saturation Mean saturation of detection mask (0–100 scale) Value Mean brightness of detection mask (0–100 scale) BBox_X Bounding box left edge (pixels, image coordinates) BBox_Y Bounding box top edge (pixels, image coordinates) BBox_W Bounding box width (pixels) BBox_H Bounding box height (pixels) BBox_Area Bounding box area (pixels²) Size_Category Ordinal size class (Small / Medium / Large) Cluster_Size Number of tile detections within dedup radius UTM_Easting Detection centroid easting, EPSG:32616 (metres) UTM_Northing Detection centroid northing, EPSG:32616 (metres) Latitude WGS84 decimal degrees Longitude WGS84 decimal degrees Notes Processing flags or anomaly notes Chip_Filename Filename of 128 px chip image (chips not included here; chips for 1,647 final detections available separately) RLE_Mask Run-length encoded binary segmentation mask (COCO format) CIRC_HUE Circular mean hue (atan2 method, degrees) MED_HUE Median hue of mask pixels (degrees) STD_HUE Circular standard deviation of hue (degrees) MEAN_SAT Mean saturation of mask pixels (0–1 normalised) MED_SAT Median saturation of mask pixels (0–1 normalised) MEAN_VAL Mean brightness of mask pixels (0–1 normalised) MASK_PX Total pixel count of segmentation mask HUE_SRC Source of hue measurement ('mask' or 'bbox') REPRODUCTION INSTRUCTIONS -------------------------- Requirements: Python 3.8+, PyTorch 1.9+ with CUDA, Detectron2 (ViTDet build), numpy, opencv-python, scikit-image, pyproj, rawpy Steps: 1. Place run_geom_full_4999.py in the same directory as run_evt_locked_mpr01.py (the core MPRDetector pipeline). 2. Ensure model_0004999.pth is at: C:/d2/Outputs/output5_pseudo_rgb_transfer/model_0004999.pth (or update WEIGHTS_PATH in the CONFIG dict). 3. Ensure pre-processed HSV arrays are at G:/100pix/hsv_arrays/ (one *_hsv_raw.npy per flight image). 4. Run: python run_geom_full_4999.py 5. Output writes to G:/100pix_EVT_geom4999/geom4999_summary.csv (727,991 rows, all tile votes). The enriched 177,148-row file is produced by the downstream deduplication and enrichment step in the Phase II pipeline. Approximate runtime: 12–14 hours on a single NVIDIA GPU (RTX class). Re-running Phase II chromatic filtering only (from this catalog): ~1.2 sec. NOTES ------ - HSV arrays are stored normalised 0–1 (float32), NOT 0–65535. - The 727,991-row summary retains all tile votes (no dedup); the 177,148-row enriched file has duplicate tile-overlap detections collapsed to unique object centroids at 0.01 m radius. - This catalog preceded the HITL adjudication step. The adjudicated validation dataset (FP_detections.shp, 786 records) is a separate supplementary file. LICENSE / CITATION ------------------- These data are released as supplementary material to the above article. Please cite the article if you use this dataset or the associated code. ================================================================================ End of README ================================================================================