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Workflow Playbook
Normalize coordinate formats, verify locations, calculate distance and bearing, then convert GeoJSON, KML, OSM, and GPX data for downstream mapping work.
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Normalize coordinate formats, verify locations, calculate distance and bearing, then convert GeoJSON, KML, OSM, and GPX data for downstream mapping work.
Use this guide to turn the stated scope into a reviewable result. Keep the source, intermediate outputs, and decisions together so the next person can understand what was checked and why.
Known source coordinates: You have at least one source coordinate pair, route, or exported map file to check.
Target format: You know whether the final output must stay in decimal degrees, DMS, UTM, Geohash, Maidenhead, GeoJSON, KML, OSM, or GPX.
Reference context: You know the region, waypoint order, or destination system so validation decisions can be grounded in a real use case.
Decision: Resolve notation mismatches first. If the source mixes decimal degrees and DMS notation, normalize everything before any distance or direction calculation.
Decision: Choose the right distance model. Use great-circle calculations for long-range travel and bearing checks; reserve rhumb-line style thinking only when a constant heading is the real operational need.
Decision: Match the destination format. Pick the output format based on the receiving platform: KML for Google Earth style tooling, GeoJSON for web maps, OSM for OpenStreetMap pipelines, and GPX for tracks or waypoints.
Convert every source latitude and longitude into a single consistent notation so later calculations do not mix decimal, DMS, and grid-style values. Use coordinate-converter-dms, utm-zone-calculator, coords-to-maidenhead, maidenhead-to-coords.
Encode a representative point as a geohash and decode it back to confirm the coordinate lands in the intended area before you trust downstream measurements. Use geohash-generator, geohash-decoder.
Run distance, bearing, and midpoint checks between key points so you can catch swapped coordinates, reversed waypoint order, or unrealistic travel spans. Use great-circle-distance, bearing-calculator, midpoint-calculator.
Transform the route or feature file into the exchange format your mapping stack expects, keeping geometry review tied to the validated coordinates from earlier steps. Use kml-to-geojson, geojson-to-kml, osm-to-geojson, geojson-to-osm, gpx-to-geojson.
Workflow playbook
Convert every source latitude and longitude into a single consistent notation so later calculations do not mix decimal, DMS, and grid-style values.
Encode a representative point as a geohash and decode it back to confirm the coordinate lands in the intended area before you trust downstream measurements.
Run distance, bearing, and midpoint checks between key points so you can catch swapped coordinates, reversed waypoint order, or unrealistic travel spans.
Transform the route or feature file into the exchange format your mapping stack expects, keeping geometry review tied to the validated coordinates from earlier steps.
If the source mixes decimal degrees and DMS notation, normalize everything before any distance or direction calculation.
Use great-circle calculations for long-range travel and bearing checks; reserve rhumb-line style thinking only when a constant heading is the real operational need.
Pick the output format based on the receiving platform: KML for Google Earth style tooling, GeoJSON for web maps, OSM for OpenStreetMap pipelines, and GPX for tracks or waypoints.