GIS Electric Network Mapping Setup
Budget: $30 – $250 USD
I’m compiling a GIS model of our electrical network for research and analysis, and accuracy is everything. The project is strictly geospatial: I need properly referenced layers that show how power lines, substations, and transformers relate to one another across the study area. Attribute tables must include IDs, capacities or voltage classes where available, and any other fields you feel are essential for solid analytical work later on.
Preferred tools are ArcGIS Pro or QGIS; choose whichever lets you deliver clean topology and straightforward metadata. If you work in another platform, export to an open format (GeoPackage or shapefile) so that it drops straight into our existing workflows.
Deliverables
• Geo-referenced layers for power lines, substations, and transformers
• A project file (or map document) that displays these layers ready for analysis
• Metadata describing coordinate system, data sources, and field definitions
• Brief notes on the methodology you used so I can replicate or extend the work
Acceptance criteria: every feature must fall within the correct coordinate system, snap logically at intersections, and carry complete attribute data. If anything is derived or interpolated, flag the confidence level in the notes.
Once the files open flawlessly in my environment and pass a quick topology check, we’re done. Looking forward to a solid, analysis-ready dataset.
Preferred tools are ArcGIS Pro or QGIS; choose whichever lets you deliver clean topology and straightforward metadata. If you work in another platform, export to an open format (GeoPackage or shapefile) so that it drops straight into our existing workflows.
Deliverables
• Geo-referenced layers for power lines, substations, and transformers
• A project file (or map document) that displays these layers ready for analysis
• Metadata describing coordinate system, data sources, and field definitions
• Brief notes on the methodology you used so I can replicate or extend the work
Acceptance criteria: every feature must fall within the correct coordinate system, snap logically at intersections, and carry complete attribute data. If anything is derived or interpolated, flag the confidence level in the notes.
Once the files open flawlessly in my environment and pass a quick topology check, we’re done. Looking forward to a solid, analysis-ready dataset.