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Far Shading – Horizon Data

Solar PV projects are increasingly being built in locations with undulating terrain and proximity to hills, mountains or canyons. Nearby topographical features such as valley walls or hills can block solar irradiance from reaching PV panels, especially in the early and late hours of the day. These irradiance and PV output losses are commonly referred to as far-horizon shading losses and can range anywhere from less than 1% in estuarine wetlands, to over 12% in evergreen forests. Some studies show that direct solar irradiance can be obstructed for most of the year on certain steep mountain slopes.1  

Figure 1 demonstrates the effect of horizon shading on irradiance. If the sun is below the horizon profile, the direct/beam component (Beamhorizontal) as well as the circumsolar diffuse component (DCS) are blocked entirely, whereas a fraction of the horizon brightening (DHB) and isotropic diffuse (Diso) components is blocked.

Figure 1: Effect of horizon shading on irradiance

Because local terrain is unique and solar angles vary constantly, the shadows must be considered for each sun position over an hourly, daily and monthly time interval. To estimate this, a site-specific shading horizon profile must be determined for the PV system. This horizon profile data is generally in the form of azimuth and corresponding elevation pairs, and it can be used to estimate the impact of terrain undulation on the solar resource and PV output.


SolarAnywhere offers far-shading data to support accurate PV performance modeling. The data is based on satellite observations from the NASA Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) dataset. The spatial resolution of this data is 30m x 30m nominal native resolution (1 arc-second resolution). 

For each user-provided coordinate, the surrounding terrain is scanned at a 1-degree angular resolution. Elevation angles are calculated at multiple distances from the origin, and the largest angle is chosen as the elevation angle of the horizon. 

SolarAnywhere far-shading data is available with SolarAnywhere versions 3.7 and newer in all geographic regions. All SolarAnywhere users can access this data through the SolarAnywhere data website and the API at no additional cost. 

Using SolarAnywhere Far-Shading Data

A study of terrain obstruction induced losses on the island of Oahu, Hawaii, found overall reduction in total yield of about 7% across the island. To learn more about far-shading and impact on PV generation, watch recorded the presentation.


Conventional approaches to estimating horizon shading, such as use of commercial shading analysis tools and raw fisheye images, tend to overestimate the direct beam shading.2 High-resolution satellite-derived shading data enables solar developers and contractors to generate horizon profiles on-demand, saving time spent in costly on-site visits to determine far shading impacts. 

In addition to obstructions farther in the horizon, SolarAnywhere far-shading data also accounts for the effect of nearby objects such as trees, buildings etc. Figure 2 shows how SolarAnywhere far-shading data accounts for near-object shading from trees at the test site when compared with PVGIS data.

Figure 2: Comparison of SolarAnywhere and PVGIS horizon shading data

Comparison of SolarAnywhere and PVGIS far-horizon shading data

SolarAnywhere far-horizon data is generated in the form of azimuth and elevation pairs for a given coordinate. Figure 3 shows the format of the Far-Shading output file.

Figure 3: Far-Shading Datafile

The file can be used with third-party PV modeling tools to estimate the impact of the horizon profile on irradiance and improve the accuracy of PV performance estimates. Figure 4 shows an example of the horizon profile generated on importing SolarAnywhere far-shading data in PVsyst.

Figure 4


1 Aguilar C, Herrero J, Polo MJ. 2010. Topographic effects on solar radiation distribution in mountainous watersheds and their influence on reference evapotranspiration estimates at watershed scale. Hydrololy and Earth Systems Sciences, 14(12), p 2479–2494. DOI: 10.5194/hess-14-2479-2010.

2 Mira DC, Bartholomaus M, Poulsen PB, Spataru SV. 2021. Accuracy Evaluation of Horizon Shading Estimation Based on Fisheye Sky Imaging. IEEE 48th Photovoltaic Specialists Conference (PVSC). DOI: 10.1109/PVSC43889.2021.9519063. Link