Visual Causes of Thermal Anomalies

In the article you will learn more about the different visual causes that are linked to the thermal anomaly.

Updated over a week ago


This article provides an in-depth explanation of the different visual causes of the thermal anomalies in your Solar Thermography and Solar Thermography Pro data product.

If you are looking for more information on the Solar Thermography Pro or the Solar Thermography data product, please check the support article here.

Visual (RGB) Causes Overview


Sometimes you may see some dirt on the module in the visual (RGB) dataset and it usually goes along with a hotspot or a multiple hotspot in the thermal dataset.

There may not be anything to see in the visual (RGB) dataset, but you are able to determine that it is soiling because of the pattern of the hotspots at the bottom of a PV module. This is because of the inclination of the PV module. The dirt will tend to settle in the bottom sections of the PV module resulting in a build-up.

The soiling problem is easy to solve via cleaning.

The following examples are showing some soiling build-up in the bottom corner from the PV module.

Physical or Physical (Suspected)

When there is an obvious issue on the thermal data, but nothing visible on the RGB data we mark the cause of this anomaly as a physical issue. This cause is most common in anomalies such as bypasses where there is most likely a physical defect within the PV module that needs to be fixed.


If there is vegetation visible in the RGB orthomosaic at the same location as a hotspot on the thermal layer, the cause of the anomaly will be marked as vegetation. An important distinction is that this cause is used for small obstructions to PV modules, for example, a tree creating a shadow over the PV module would not be vegetation, but shadowing.


Shadowing occurs when an object creates a shadow on the PM module. It is recognised by a hotspot or a multiple hotspot in the thermal dataset. It's important to note that this shadowing may not be there all the time, so our analysis will be based on the moment in time in which the images were captured.

In the following real examples you can identify a hotspot and a single bypassed diode. This is because the bypass diode in the PV module protects the array from the destructive effects caused by partial shading. Therefore the affected substring is bypassed.

Often the shadow is caused by tall objects around or between the PV modules. But sometimes it is also possible that the adjacent row of PV modules causes the shading on the previous or next row of PV modules. This is called Self Shading.

Self shading can impact the PV module in a couple of ways. In the adjacent visual (RGB) image you see a thin shadow on the edge of the PV modules. In the thermal image the shadow is seen as a black line. This is clearly visible in the following example.


The droppings cause is used when bird droppings are clearly noticeable on the visual (RGB) data. In this example you can clearly see the dropping in both visual and thermal images. However, sometimes a dropping visible in the visual dataset is not visible in the thermal dataset. In that case, we only mark what we see in thermal. That anomaly would be labelled as hotspot. Please note that droppings are much harder to clean than soiling issues.

The following examples are showing some bird droppings.


Sometimes birds can be present on the PV modules. This is a temporary thing, as the birds will disappear after some time. This example will be labelled as a multi hotspot anomaly type with a birds (alive) cause.

Removable Object

Very often we spot a UFO on the PV module. No, not a flying one 😀 , but an Unidentified Field Object, like for example a notepad left on the PV module, or a glove that is left behind after a maintenance job on site. This thermal anomaly would be labelled as a hotspot type with a removable object cause.

Visible Unknown

There are occasions when it is not clear from the visual (RGB) images what the cause of the anomaly is, but there is something visible and 'unknown' on the PV module which causes the anomaly. In these situations we use the cause Visible Unknown.

In the following example two labels were placed on the PV module, one for the single bypassed diode anomaly and another one for the hotspot which has a Visible Unknown cause.

Broken Glass

The front glass panel of a solar module represents the first line of defence against the weather elements, like rain, dust, sand, hail. The glass panel can get broken by an impact from any other object, like for example the cleaning car driving in between the PV modules. Broken glass makes PV modules more susceptible to environmental effects, like water ingression. When the glass is broken, not only the light absorbed by the panel will diminish, foreign elements such as water and dust can go under the glass to shade solar cells and impact energy output. Water which goes in the PV module might result in internal corrosion (rusting). The following example shows the impact of a hailstorm on a PV site.


PV modules must be air- and water-tight. In order to achieve this, the components of modules (the glass layer, the solar cells and the back sheet) are laminated under vacuum. However, if the lamination process has been not done properly or was too short, this can lead to delamination during operation. Delamination is the detachment of the laminated components.

Delamination can cause moisture to penetrate or bubbles to occur. Moisture leads to corrosion, which becomes visible as darker spots on the panel. This phenomenon often starts at the edge of the PV module and can spread across the rest of the module.

Please keep in mind that the delamination require high resolution data to be identified in the visual (RGB) imagery and is not detectable with the standard parameters of the Thermography data products.

Snail Trails

A snail trail is a discolouration of the PV module which usually only manifests itself after a couple of years of production. The snail trail is the result of an unwanted chemical process that releases silver oxide, acetic acid (vinegar) and hydrogen. The effect of this reaction is fed from the back of the PV module to the front of the PV module, and causes a chemical breakdown on the front of the PV module. This becomes visible as ‘snail trails’, resulting in a reduction in the panel’s performance. The snail trails can also arise as a result of microscopic cracks in the panel. The following example shows a PV module affected by snail trails.

Please keep in mind that the snail trails require high resolution data to be identified in the visual (RGB) imagery and is not detectable with the standard parameters of the Thermography data products.

Micro Cracks

Micro cracks in crystalline PV module are microscopic cracks in the solar cells. They can occur during PV modules production, but also during shipping or due to careless handling practice during installation. Micro cracks do not necessarily result in immediate production loss, but can grow over time, for example due to thermal stress fatigue over time. Larger micro cracks will damage the solar cells, and this will lead to production loss. The following example shows a PV module affected by micro cracks.

Please keep in mind that the micro cracks require high resolution data to be identified in the visual (RGB) imagery and is not detectable with the standard parameters of the Thermography data products.

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