What was built A site suitability raster map classifying San Francisco by solar energy potential — from low-irradiance fog-prone areas to high-irradiance zones optimal for renewable energy investment — providing spatial prioritization for solar infrastructure development decisions.
Who it was for Urban energy planners and infrastructure investors evaluating solar installation viability and return on investment at the municipal scale.
Why it mattered Infrastructure investment in solar energy requires knowing not just that a city has potential, but exactly where that potential is concentrated. This analysis makes spatial variation in irradiance explicit — turning a policy question about solar viability into a spatially prioritized investment map at the city scale.

The Challenge

Renewable energy planning requires spatial specificity that aggregate statistics can't provide. A city-level average irradiance figure doesn't tell an infrastructure investor where to install panels — or a planner where to concentrate solar incentive programs. In San Francisco specifically, fog patterns, building density, and topography create pronounced neighborhood-level variation in solar output: the difference between high and low irradiance zones is the difference between a productive and an underperforming installation.

Global Horizontal Irradiance (GHI) data was classified into five zones, rendered as a gradient from low-irradiance areas to high-irradiance zones (red and orange). The output gives urban energy planners and infrastructure investors a spatially prioritized answer: where in San Francisco is solar installation most likely to produce meaningful returns on investment?

The value is in the decision support — not just showing where the sun hits hardest, but producing a five-class output at a resolution and classification that can actually drive infrastructure investment decisions and policy prioritization at the municipal scale.

This analysis supports renewable energy planning and solar infrastructure investment by identifying spatially prioritized development zones across San Francisco.

GHI Classification — 5 Zone Output
Zone 5 — Highest irradiance (optimal solar investment)
Zone 4 — High irradiance
Zone 3 — Moderate irradiance
Zone 2 — Low irradiance
Zone 1 — Lowest irradiance (fog-prone, shaded)

"The question wasn't 'does San Francisco get sun.' It was 'where does it get enough sun to make solar investment worthwhile.' That's a raster analysis problem."

Process

  1. 1
    Research Identified GHI dataset appropriate for municipal-scale solar analysis in San Francisco.
  2. 2
    Data Prep Processed raster data; established classification breaks for 5-class output.
  3. 3
    GIS Work Applied raster classification; designed five-class color gradient; verified spatial accuracy against known SF geography.
  4. 4
    Output Published five-class raster map identifying priority zones for solar energy investment across San Francisco — supporting renewable energy planning and infrastructure siting decisions at the municipal scale.
Principle 02
The map is for a person making a decision

A raster classification is only as useful as the decision it enables. The five-zone output wasn't chosen for aesthetic reasons — it was chosen because infrastructure investors and urban planners need discrete, actionable zones, not a continuous gradient that leaves the interpretation open.