Abstract

Abstract. Precise and detailed digital elevation models (DEMs) are essential to accurately predict overland flow in urban areas. Unfortunately, traditional sources of DEM, such as airplane light detection and ranging (lidar) DEMs and point and contour maps, remain a bottleneck for detailed and reliable overland flow models, because the resulting DEMs are too coarse to provide DEMs of sufficient detail to inform urban overland flows. Interestingly, technological developments of unmanned aerial vehicles (UAVs) suggest that they have matured enough to be a competitive alternative to satellites or airplanes. However, this has not been tested so far. In this study we therefore evaluated whether DEMs generated from UAV imagery are suitable for urban drainage overland flow modelling. Specifically, 14 UAV flights were conducted to assess the influence of four different flight parameters on the quality of generated DEMs: (i) flight altitude, (ii) image overlapping, (iii) camera pitch, and (iv) weather conditions. In addition, we compared the best-quality UAV DEM to a conventional lidar-based DEM. To evaluate both the quality of the UAV DEMs and the comparison to lidar-based DEMs, we performed regression analysis on several qualitative and quantitative metrics, such as elevation accuracy, quality of object representation (e.g. buildings, walls and trees) in the DEM, which were specifically tailored to assess overland flow modelling performance, using the flight parameters as explanatory variables. Our results suggested that, first, as expected, flight altitude influenced the DEM quality most, where lower flights produce better DEMs; in a similar fashion, overcast weather conditions are preferable, but weather conditions and other factors influence DEM quality much less. Second, we found that for urban overland flow modelling, the UAV DEMs performed competitively in comparison to a traditional lidar-based DEM. An important advantage of using UAVs to generate DEMs in urban areas is their flexibility that enables more frequent, local, and affordable elevation data updates, allowing, for example, to capture different tree foliage conditions.

Highlights

  • 1.1 Urban drainage modellingDensely urbanised areas, where most economic activities take place, face higher probability of flood occurrence due to (i) the large percentage of impervious areas, which increase the runoff volume; and (ii) alterations of natural water streams and existence of sewer systems, which increase flow velocities, reducing catchments’ time of concentration and duration of the critical rainfall events

  • In this study we evaluated whether digital elevation models (DEMs) generated from unmanned aerial vehicles (UAVs) imagery are suitable for urban drainage overland flow modelling

  • We first present the results of the influence of parameters on DEM quality, and second the results from the comparison of the UAV DEM to the lidar DEM

Read more

Summary

Introduction

Urbanised areas, where most economic activities take place, face higher probability of flood occurrence due to (i) the large percentage of impervious areas, which increase the runoff volume; and (ii) alterations of natural water streams and existence of sewer systems, which increase flow velocities, reducing catchments’ time of concentration and duration of the critical rainfall events. Climate change may increase rainfall intensity and frequency in some regions of the globe, which will affect ecosystems and human life. These more frequent extreme conditions can increase the probability that urban drainage system capacity is exceeded, which may lead to higher urban flood risks (when flood consequences are maintained). Urban drainage models should be represented by coupling the sewer system (one-dimensional model, 1-D) with the overland flow system (1-D or 2-D).

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call