Development and validation of a new efficient SRTM DEM-based horizon model combined with optimization and error prediction methods

Abstract

Several post-processing methods have been developed over the last years in order to take into consideration topography within satellite-based solar radiation maps using digital elevation models (DEM). If the main part of these procedures is to estimate the obstructed horizon around each DEM point of a given region so as to consider terrain-based shading effects, the size of the area can also limit this implementation. That is why we have developed a new efficient horizon model based on the DEM retrieved during the Shuttle Radar Topography Mission (SRTM). In order to be usable at any world location with the same expected accuracy, this model is only derived from mathematical statements without any kind of empirical approximation. Validation against in situ horizons and comparison with some other models have finally shown this one presents both better accuracy (RMSE of 1.555• against 1.712• or more) and lower computation time (at least 4 times faster).Furthermore, in the case of very large areas, we propose an optimization procedure allowing the user to knowingly alter the modeling error in order to reduce processing time. Finally, using in situ data, we have also developed a method for predicting the repercussion of the original SRTM DEM error on the final horizon precision.

HORAYZON v1.2: an efficient and flexible ray-tracing algorithm to compute horizon and sky view factor

“…In line with other algorithms (Dozier et al, 1981;Dozier and Frew, 1990;Pillot et al, 2016), we compute the horizon for a location by splitting the azimuth angle into discrete sectors and sample along the centrelines. By default, we use 360 sectors.…”

“…We consider two reference horizon algorithms to evaluate the computational performance and accuracy of our method: the first is the algorithm described in Pillot et al (2016), which is available as a MATLAB implementation (Pillot, 2016).…”

“…The horizon is then estimated by combining the near-and far-distance horizons. Finally, Pillot et al (2016) present a horizon algorithm that closely follows the initial, non-accelerated concept of Dozier et al (1981). In contrast to many earlier studies, they do not assume a planar DEM grid and account for the curvature of the Earth's surface.…”

“…In many studies (Pillot et al, 2016;Zhang et al, 2018;Marsh et al, 2020), horizon algorithms are still based on the conventional concept, in which all terrain information along a finite centreline is scanned to find the highest elevation angle. These algorithms typically perform sufficiently for DEMs with coarse resolutions and/or small sizes.…”

Accuracy Verification and Correction of D-InSAR and SBAS-InSAR in Monitoring Mining Surface Subsidence

“…The specific parameters are presented in Table 2. In addition, the digital elevation model (DEM) data was used to simulate and remove the topographic phase contribution, which was from the Shuttle Radar Topography Mission-3 (SRTM) DEM at a spatial resolution of 90 m provided by the American National Aeronautics and Space Administration (NASA) and National Imagery and Mapping Agency (NIMA) [25].…”