Wadi Hasa Sample Dataset — GRASS GIS Location

Wadi Hasa Sample Dataset — GRASS GIS LocationVersion 1.0 (2025-09-19) Overview--------This archive contains a complete GRASS GIS *Location* for the Wadi Hasa region (Jordan), including base data and exemplar analyses used in the Geomorphometry chapter. It is intended for teaching and reproducible research in archaeological GIS. How to use----------1) Unzip the archive into your GRASSDATA directory (or a working folder) and add the Location to your GRASS session.2) Start GRASS and open the included workspace (Workspace.gxw) or choose a Mapset to work in.3) Set the computational region to the default extent/resolution for reproducibility: g.region n=3444220 s=3405490 e=796210 w=733450 nsres=30 ewres=30 -p4) Inspect layers as needed: g.list type=rast,vector r.info <raster_name> v.info <vector_name> Citation & License------------------Please cite this dataset as: Isaac I. Ullah. 2025. *Wadi Hasa Sample Dataset (GRASS GIS Location)*. Zenodo. https://doi.org/10.5281/zenodo.17162040 All contents are released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. The original Wadi Hasa survey dataset is available at: https://figshare.com/articles/dataset/Wadi_Hasa_Ancient_Pastoralism_Project/1404216 The original Wadi Hasa survey dataset is available at: https://figshare.com/articles/dataset/Wadi_Hasa_Ancient_Pastoralism_Project/1404216 Coordinate Reference System---------------------------- Projection: UTM, Zone 36N- Datum/Ellipsoid: WGS84- Units: meter- Coordinate system and units are defined in the GRASS Location (PROJ_INFO/UNITS). Default Region (computational extent & resolution)--------------------------------------------------- North: 3444220- South: 3405490- East: 796210- West: 733450- Resolution: 30 (NS), 30 (EW)- Rows x Cols: 1291 x 2092 (cells: 2700772) Directory / Mapset Structure----------------------------This Location contains the following Mapsets (data subprojects), each with its own raster/vector layers and attribute tables (SQLite): - Boolean_Predictive_Modeling: 8 raster(s), 4 vector(s) - ISRIC_soilgrid: 31 raster(s), 0 vector(s) - Landsat_Imagery: 3 raster(s), 0 vector(s) - Landscape_Evolution_Modeling: 41 raster(s), 0 vector(s) - Least_Cost_Analysis: 13 raster(s), 4 vector(s) - Machine_Learning_Predictive_Modeling: 70 raster(s), 11 vector(s) - PERMANENT: 4 raster(s), 2 vector(s) - Sentinel2_Imagery: 4 raster(s), 0 vector(s) - Site_Buffer_Analysis: 0 raster(s), 2 vector(s) - Terrain_Analysis: 27 raster(s), 2 vector(s) - Territory_Modeling: 14 raster(s), 2 vector(s) - Trace21k_Paleoclimate_Downscale_Example: 4 raster(s), 2 vector(s) - Visibility_Analysis: 11 raster(s), 5 vector(s) Data Content (summary)----------------------- Total raster maps: 230- Total vector maps: 34 Raster resolutions present: - 10 m: 13 raster(s) - 30 m: 183 raster(s) - 208.01 m: 2 raster(s) - 232.42 m: 30 raster(s) - 1000 m: 2 raster(s) Major content themes include:- Base elevation surfaces and terrain derivatives (e.g., DEMs, slope, aspect, curvature, flow accumulation, prominence).- Hydrology, watershed, and stream-related layers.- Visibility analyses (viewsheds; cumulative viewshed analyses for Nabataean and Roman towers).- Movement and cost-surface analyses (isotropic/anisotropic costs, least-cost paths, time-to-travel surfaces).- Predictive modeling outputs (boolean/inductive/deductive; regression/classification surfaces; training/test rasters).- Satellite imagery products (Landsat NIR/RED/NDVI; Sentinel‑2 bands and RGB composite).- Soil and surficial properties (ISRIC SoilGrids 250 m products).- Paleoclimate downscaling examples (CHELSA TraCE21k MAT/AP). Vectors include:- Archaeological point datasets (e.g., WHS_sites, WHNBS_sites, Nabatean_Towers, Roman_Towers).- Derived training/testing samples and buffer polygons for modeling.- Stream network and paths from least-cost analyses. Important notes & caveats-------------------------- Mixed resolutions: Analyses span 10 m (e.g., Sentinel‑2 composites, some derived surfaces), 30 m (majority of terrain and modeling rasters), ~232 m (SoilGrids products), and 1 km (CHELSA paleoclimate). Set the computational region appropriately (g.region) before processing or visualization.- NoData handling: The raw SRTM import (Hasa_30m_SRTM) reports extreme min/max values caused by nodata placeholders. Use the clipped/processed DEMs (e.g., Hasa_30m_clipped_wshed*) and/or set nodata with r.null as needed.- Masks: MASK rasters are provided for analysis subdomains where relevant.- Attribute tables: Vector attribute data are stored in per‑Mapset SQLite databases (sqlite/sqlite.db) and connected via layer=1. Provenance (brief)------------------- Primary survey points and site datasets derive from the Wadi Hasa projects (see Figshare record above).- Base elevation and terrain derivatives are built from SRTM and subsequently processed/clipped for the watershed.- Soil variables originate from ISRIC SoilGrids (~250 m).- Paleoclimate examples use CHELSA TraCE21k surfaces (1 km) that are interpolated to higher resolutions for demonstration.- Satellite imagery layers are derived from Landsat and Sentinel‑2 scenes. Reproducibility & quick commands--------------------------------- Restore default region: g.region n=3444220 s=3405490 e=796210 w=733450 nsres=30 ewres=30 -p- Set region to a raster: g.region raster=<raster_name> -p- Display (GUI): d.rast <raster_name>; d.vect <vector_name>- List by Mapset: g.list type=rast,vector mapset=*- Export examples: r.out.gdal input=<raster> output=<file.tif>; v.out.ogr input=<vector> output=<file.gpkg> format=GPKG Change log----------- v1.0: Initial public release of the teaching Location on Zenodo (CC BY 4.0). Contact-------For questions, corrections, or suggestions, please contact Isaac I. Ullah <[e-mail]>.