Visibility analysis plays a significant role in environmental assessments for the rollout of renewable energy production systems. Wind farms, large open-field photovoltaic installations, transmission pylons and biomass cultivation for bio-electricity often faces public resistance due to their impacts on the visual landscape. Visibility analysis assists in the process of determining proper locations for renewable energy plants to assess and subsequently minimize their visibility and hence their visual impact. As a basis for visibility analysis, digital terrain (DTM) and digital surface data (DSM) are required. As these data are still very costly in Germany, cheaper data with a lower accuracy are often used in practice, leading to inaccurate results of the visibility analyses. The cloud-based platform CLOUDEO offers the possibility to rent data and conduct visibility analyses on a virtual desktop, which is an affordable alternative to buying expensive data. In this paper we compare the results based on the NextMap DTM 5 and DSM 5 data offered by CLOUDEO with those based on the more expensive DTM 10 data using ATKIS-data for extruding landuse-heights and DTM / DSM 1 data (LIDAR) provided by state surveying authorities, to judge if the cloud-based platform is a valid alternative. Assuming that the DTM 1 and DSM 1 data lead to the most accurate results, it could be shown that the results of visibility analyses based on NextMap DTM 5 overestimate visibility in comparison to those based on DTM 1 and DTM 10 data. When using the digital surface data (DSM 5), which represents the more common and realistic alternative, it could be shown, that the visibility analyses based on DSM 5 only differ slightly from those based on DSM 1, whereas results based on DSM 10 show greater differences to those based on DSM 1. Summarizing, it can be stated that CLOUDEO offers an affordable and valid alternative to buying expensive data for visibility analysis of energy infrastructure.