Concepts
Understand the core concepts behind spatial data in Python before diving into tasks and workflows.
Every concept, A–Z
Page 11 — use the page links below, or browse by topic above.
- Tidal datums explained: which shoreline is the shoreline
- Time-Series Maps Explained: Events, Tracks, Snapshots and Fields
- Topological Coverage: What "Clean" Means for Adjacent Polygons
- Toxic Release Totals Explained: Air, Water, Land and Off-Site
- Trajectories Explained: What Makes a Track Different from Points
- Transit accessibility explained: why travel time depends on the minute you leave
- Transit frequency and headways explained
- TRI Form A Explained: Facilities That Report No Quantities
- Units, Buildings and Value in Building Permit Data Explained
- Urban Blocks Explained
- Urban Cooling and Green Space Explained
- Urban Extent Explained
- Urban Morphology Explained
- Vector Field Maps Explained
- Vector Tiles Explained: MVT, Layers and Why They Are Not GeoJSON
- Vector vs Raster Data in Python GIS: Key Differences
- Vegetation indices explained: NDVI, EVI, NDRE and when each fails
- Vertical Datums Explained: Why Your Elevations Are Off
- Visual Hierarchy Explained: What a Map Reader Sees First
- Weather Data Sources for Python, Explained: Stations, Reanalysis and APIs
- Weather Model Resolution Explained
- Weather Radar Reflectivity Explained: dBZ, Tilts and Beam Height
- Web Map Tiles Explained: XYZ, Zoom Levels and the Tile Pyramid
- What a Map App Can Afford to Send to the Browser
- What GDAL and OGR Actually Are (and Why Everything Depends on Them)
- What Is a GeoDataFrame? A pandas Table With Geometry and a CRS
- What Is a GIS Data Pipeline? The Anatomy Explained
- What Makes a Geometry Valid? The OGC Rules Explained
- What to Test in a GIS Pipeline (and What You Cannot)
- Where an Aircraft Is Registered Is Not Where It Flies: FAA Addresses Explained