Impact of UAV Surveying Parameters on Mixed Urban Landuse Surface Modelling

Abstract

Unmanned Aerial Vehicles (UAVs) as a surveying tool are mainly characterized by a large amount of data and high computational cost. This research investigates the use of a small amount of data with less computational cost for more accurate three-dimensional (3D) photogrammetric products by manipulating UAV surveying parameters such as flight lines pattern and image overlap percentages. Sixteen photogrammetric projects with perpendicular flight plans and a variation of 55% to 85% side and forward overlap were processed in Pix4DMapper. For UAV data georeferencing and accuracy assessment, 10 Ground Control Points (GCPs) and 18 Check Points (CPs) were used. Comparative analysis was done by incorporating the median of tie points, the number of 3D point cloud, horizontal/vertical Root Mean Square Error (RMSE), and large-scale topographic variations. The results show that an increased forward overlap also increases the median of the tie points, and an increase in both side and forward overlap results in the increased number of point clouds. The horizontal accuracy of 16 projects varies from ±0.13m to ±0.17m whereas the vertical accuracy varies from ± 0.09 m to ± 0.32 m. However, the lowest vertical RMSE value was not for highest overlap percentage. The tradeoff among UAV surveying parameters can result in high accuracy products with less computational cost.

The Influence of Flight Configuration, Camera Calibration, and Ground Control Points for Digital Terrain Model and Orthomosaic Generation Using Unmanned Aerial Vehicles Imagery

“…Torres-Sánches et al (2018) analyzed the accuracy of generating a Digital Surface Model (DSM) and reached an optimum overlap rate of 95% of forward overlap and 60% side overlap at a height of 100 m. Frey et al (2018) confirmed that both altitude and image overlap are related to the accuracy of the resulting point cloud (best case scenario is 95% image overlap with a GSD smaller than 5.0 cm), in which is similar to the results obtained by (Dandois, Olano and Ellis, 2015). Chaudhry, Ahmad and Gulzar (2020) compared the effects of the image overlap variations (55-85% forward and sidelap) on the number of tie points, point cloud quality, and planialtimetric accuracy over an urban area with heterogeneity of land cover and topographic variations. The authors concluded that decreasing the overlap rate will lead to poorer RMSE values for the vertical component are obtained, on the other hand, the planimetric accuracy presented similar results.…”

“…Agüera-Vega (2017b) observed the same pattern as presented on Udin and Ahmad (2014), where the planimetric accuracy is not affected, on the other hand, vertical accuracy becomes worst with higher flight height. Dandois, Olano and Ellis (2015), Frey et al (2018), Torres-Sánches et al (2018 and Chaudhry, Ahmad and Gulzar (2020) studied the influence of image overlap on final product quality. A number of researches focused on this issue, although, few studies are applied to map urban environments and most of the studies focus on mapping vegetation areas.…”

Assessment of DSM Based on Radiometric Transformation of UAV Data

“…In geo-sciences applications, it is mainly encouraged for its capability of surveying small areas, which is unique as compared to other techniques. Photogrammetry has been developed as the most common surveying tool because of its more sophisticated and modern computing machines [ 13 ]. At present, UAVs are being used regularly for surveying, mapping at a high spatial resolution, generating 3D point cloud, producing orthomosaic and DSM/DTM generation [ 35 ].…”

“…At present, DSM is one of the important and basic photogrammetric data products used in a number of applications [ 12 ]. Surveyors have been producing topographic and relief maps for many years and most modern techniques for such types of mapping are aerial photographs, stereo pairs and digital photogrammetric processes [ 13 ].…”

Application of Fixed-Wing UAV-Based Photogrammetry Data for Snow Depth Mapping in Alpine Conditions

“…One of the most essential geospatial outputs of point cloud processing is the Digital Surface Model (DSM). DSM is a digital representation of the horizontal and vertical dimensions related to the Earth including all natural and manmade objects in a grid cell structure [38]. The basic framework for determination of snow depth via UAVs photogrammetry is based on DSM comparison on the principle of differentiating between temporally subsequent surfaces.…”