The Potential of UAV Data as Refinement of Outdated Inputs for Visibility Analyses

Abstract

Visibility analyses in geographical information systems (GIS) are used to quantify the visible and non-visible parts of the landscape. This study aims to evaluate the changes in viewshed outputs after the unmanned aerial vehicle (UAV) data refinement for the near surroundings of the observer. This research accounts for the influence of data age, mainly due to vegetation growth, and the impact of the input data quality on the final study output. The raw data that were used for UAV refinement were publicly available data (one dataset at the global level, two datasets at the national level of the Czech Republic) and airborne laser scanning (ALS) data. Three localities were selected in order to compare the viewshed evaluation that was processed over ten raster elevation models. The comparison was performed using the kappa coefficient, which considers not only the matching visible pixels, but also false visibility and invisibility. Over the span of five years (2013–2018), the visible area at two sites has decreased by more than 7%. Although with some variations (kappa coefficient varied from 0.02 to 0.92), all the study sites showed a decreasing trend of the visible area with the data aging, which was caused by the vegetation growth or landscape changes. The results showed the effect of data aging in forested areas on the resulting visibility within a couple of years. At all the sites, major changes in visibility were observed after three years (2021 vs. 2018) due to vegetation growth, forest management, and natural phenomena, such as windfalls. This study concludes that UAV data will increase the accuracy of visibility analysis, even when using freely available low-resolution data, and may also help us to update obsolete input data. The results of this research can be used to refine visibility analysis when current digital surface model (DSM) data is not available.