Quick answer
Interpretation of color-coded values across a solar site, checking the mapped quantity, units, time period, reference and model assumptions before using the results for design decisions.
Answer: Heat map analysis uses a color scale to interpret values across a roof or site. In solar design, the mapped quantity may be irradiance, accumulated irradiation, solar access, shading loss or modeled electrical yield. Read the legend, units, time period and reference before choosing panel locations. A bright zone is not proof of electrical output, structural suitability or permit approval.
What does a solar heat map show?
A heat map places numerical values on a surface and represents them with colors. It helps a designer see contrasts that are difficult to spot in a table, particularly around dormers, chimneys, trees, parapets and rooftop equipment. The colors have no universal meaning: red can represent high values in one display and a loss or warning in another.
Heat mapping of irradiance describes one specific mapped quantity. Heat map analysis is the reading and comparison step: identify what the values mean, check whether the model represents the site, and determine which design decision they can support.
Aurora’s shading overview distinguishes irradiance maps for solar-potential assessment from a shade simulator for visualizing shadows. That distinction is useful regardless of the software: a shadow picture and an annual solar-energy map answer different questions.
Start with the legend, not the roof color
| Displayed quantity | Example units | Question it can answer | What it does not establish alone |
|---|---|---|---|
| Instantaneous irradiance | W/m² | How intense is modeled sunlight at this instant? | Annual energy |
| Accumulated irradiation | kWh/m² for the stated period | How much solar energy reaches this surface? | Electrical kWh delivered |
| Solar access | % relative to a defined unshaded reference | How much incident solar energy remains with shading? | Full electrical shading loss |
| Shaded area or shadow state | % area or a shaded/unshaded display | Where is a shadow at a chosen time? | Irradiance-weighted annual loss |
| Modeled electrical yield | kWh per module, zone or system, with boundary stated | What output does this complete model predict? | A measurement or guarantee |
The site-workflow inputs include: geometry from imagery, LiDAR, drone or manual measurements; obstruction heights and locations; sun position; weather; and the model’s time and spatial resolution. Record imagery dates and verify changes on site. A fine grid does not repair incorrect roof or tree geometry.
Calculate solar access on a matching reference
Aurora’s solar-access definition and limitations compare incident solar energy with shading against incident solar energy without shading. The ratio is not a comparison against the best-oriented roof anywhere on the site.
Solar access (%) = 100 × shaded-period irradiation / matching unshaded-period irradiation
Use the same location, orientation, weather period and modeling assumptions for the two cases, changing the shading condition. Verify the particular tool’s implementation and whether diffuse and reflected components are included.
Hypothetical example: an unshaded reference has 1,600 kWh/m² for the modeled year; the matching shaded result is 1,360 kWh/m². Solar access is 85%, and the irradiation deficit is 240 kWh/m², or 15% of that reference. It does not follow that electrical AC energy is exactly 15% lower.
PVsyst’s shading documentation separates irradiance losses from electrical mismatch losses. To evaluate a layout, consider actual module locations, bypass-diode behavior, strings and inverter inputs as appropriate. Similar annual irradiation totals can conceal very different shadow timing; grouping modules solely by annual map color does not establish a good string design.
Compare layouts using the same scale and assumptions
Auto-scaled legends can make two roofs or variants look equally bright despite different values. Export the legend with every view, and compare numeric values using a common scale where available. Keep the model revision, weather dataset and period visible.
Retain both a raw surface overlay and the proposed panel layout. Review annual and relevant seasonal or hourly outputs: the annual total already includes the modeled winter contribution, but it does not show the timing relevant to winter loads, time-of-use tariffs or an individual shade event.
Hypothetical scale example: zone A has 1,500 kWh/m² over a year and zone B has 1,200 kWh/m². B receives 20% less irradiation than A on these declared values. If each image independently stretches its highest value to the brightest color, both zones can appear “best.” The numerical difference remains; the color comparison was misleading.
Avoid a universal rule that all panels must exceed 75%, 80% or 90% solar access. Whether a marginal panel makes sense depends on modeled incremental output, installation cost, electrical configuration, usable area, safety constraints and the customer’s objectives. The highest specific yield is not always the largest total energy or best-value layout.
Turn the map into a documented design decision
Designers: check model geometry, small obstructions and coordinate/orientation settings before comparing variants. Record why a zone is included or excluded. Check structural, fire-access and other applicable constraints separately; favorable solar exposure does not make a roof area available for installation.
Installers: compare the overlay with the current site and report new construction, vegetation changes or missing equipment before installation. Save the map’s revision with the project records so discrepancies can be traced to the actual model.
Sales teams: explain the mapped quantity and legend before pointing to “good” and “bad” zones. Present simulated values as estimates, and describe the assumptions behind a tree-removal or growth scenario. Do not turn a color overlay into a production or accuracy guarantee.
For a workflow evaluation, review SurgePV’s shading page and ask for a demonstration of the outputs needed for your project. Confirm the actual map quantities, export options and model inputs rather than assuming every platform provides the same capabilities.
Frequently asked questions
Does red always mean the best solar location?
No. Read the legend. Colors are visualization choices, and scales may change between images. Compare the actual mapped values and units.
How accurate is a solar heat map?
There is no universal percentage. The answer depends on what was validated, the site geometry, input dates, weather, model method and resolution. A clear image alone is not validation evidence.
Can a heat map show tree shading?
A modeled tree can contribute shadows and shading losses if represented by the tool. Check canopy geometry, seasonal assumptions and input date; do not assume automatic growth forecasting.
Can a heat map replace an electrical production model?
An irradiation or solar-access map cannot. Electrical output also depends on module behavior, wiring, operating conditions, conversion and losses. Check the scope of a map labeled “yield” before using its values.
Related Glossary Terms
About the Contributors
CEO & Co-Founder · SurgePV
Keyur Rakholiya is identified by SurgePV as its CEO and a company co-founder. His SurgePV author page lists only role information that can be tied to the public profile below; credentials, project totals, testing claims, media appearances, and speaking engagements are not asserted without retained evidence.
Editorial contributor · SurgePV
Rainer Neumann is credited as an editorial contributor on SurgePV content. This profile does not assert engineering credentials, project totals, software-testing experience, education, speaking engagements, or media citations because independent verification evidence is not retained in the publication record.
