Spatial Data

Spatial data (also called geospatial data) is information that describes the location, shape, size, and spatial relationships of geographic features on or near the Earth's surface. It is the fundamental data type used in GIS and mapping applications.

Types of spatial data

• Points: Discrete locations (e.g., sample sites, well locations, claim monuments)
• Lines: Linear features (e.g., roads, streams, vein traces, boundaries)
• Polygons: Area features (e.g., mining claims, lease boundaries, land parcels)
• Stored as coordinates with associated attribute tables

• Grids: Regular arrays of cells with values (e.g., elevation models, geochemical surfaces)
• Imagery: Satellite and aerial photographs
• Surfaces: Continuous data representations (e.g., slope, aspect, grade models)
• Stored as rows and columns of pixels with values

Common spatial data formats: - Shapefile (.shp) - Esri vector format - GeoJSON - Web-friendly vector format - File Geodatabase (.gdb) - Esri database format - GeoTIFF - Georeferenced raster imagery - KML/KMZ - Google Earth format - GeoPackage (.gpkg) - Open standard database format

Coordinate systems: - Geographic (latitude/longitude) - Projected (UTM, State Plane) - Datum (NAD83, WGS84)

Applications in mining: - Mining claim boundary mapping - Drill hole location databases - Geological mapping and modeling - Land ownership and title visualization - Environmental monitoring

Spatial data quality depends on accuracy, precision, completeness, and currency of the underlying measurements.