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Geospatial AnalyticsGeoPandasQGISRenewable EnergySpatial Analysis

Solar Energy Site Suitability Analysis

A reproducible GIS analysis that integrates land use, elevation, protected lands, solar resource, and transmission infrastructure datasets to evaluate solar development suitability across Colorado.

Project Summary

Status
Completed
Timeline
April 2026
Visual proof
Spatial Layers -> Suitability Score

Placeholder visual

Featured case-study visual

Placeholder visual: Colorado suitability map with candidate zones and legend.

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Problem

Renewable energy planning requires combining geographic constraints, infrastructure proximity, and resource potential to narrow down realistic candidate locations.

Approach

Integrate multiple spatial datasets, harmonize coordinate systems, apply spatial joins and buffer analysis, and score candidate areas using suitability criteria.

Architecture

System flow and processing stages.

Stage 1

Land use, elevation, protected lands, solar resource, and transmission layers

Stage 2

Spatial cleaning and CRS harmonization

Stage 3

Constraint filtering and buffer analysis

Stage 4

Spatial joins and raster/vector processing

Stage 5

Multi-criteria suitability scoring

Stage 6

Candidate site maps and ranked outputs

Data Sources

  • Land-use datasets
  • Elevation data
  • Protected lands data
  • Solar resource data
  • Transmission infrastructure data

Methods

  • Spatial joins
  • Buffer analysis
  • Coordinate transformations
  • Suitability scoring
  • Cartography

Technologies

  • Python
  • GeoPandas
  • Shapely
  • PyProj
  • QGIS
  • GDAL

Evidence and Screenshots

Visual assets to replace placeholders.

Placeholder visual

Final Colorado suitability map

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Placeholder visual

Criteria layers for land use, elevation, protected lands, solar resource, and transmission

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Placeholder visual

Candidate site ranking table

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Results

  • Generated a suitability map for utility-scale solar planning in Colorado.
  • Integrated environmental, infrastructure, and resource constraints into one geospatial workflow.
  • Produced decision-support visuals and candidate site rankings.

Metrics and Evaluation Needed

  • Suitability score distribution
  • Excluded land by constraint type
  • Candidate sites by county
  • Distance-to-transmission histogram

Challenges

  • Spatial layers used different coordinate systems and resolutions.
  • Suitability criteria required balancing interpretability with domain constraints.
  • Map outputs needed to be useful for planning, not just visually attractive.

Lessons Learned

  • Geospatial analysis becomes powerful when it connects data layers to practical planning decisions.
  • CRS alignment and preprocessing strongly affect downstream results.
  • Transparent scoring rules make suitability models easier to evaluate.

Future Work

  • Add an interactive map with layer toggles.
  • Add weighting controls for suitability criteria.
  • Add transmission-distance sensitivity analysis.

Interactive Demo Ideas

  • Interactive suitability map
  • Layer toggle explorer
  • Criteria weighting simulator

What This Demonstrates

The hiring signal behind the project.

Geospatial analytics
Energy decision support
Spatial data engineering
GIS visualization