Abstract
Urban flood models that use Digital Elevation Models (DEMs) to simulate extent and depth of flood inundation rely on the accuracy of DEMs for predicting flood events. Despite recent advances in developing vegetation corrected DEMs, the effect of building height and density errors in global DEMs in urban areas are still poorly understood, and their correction remains a challenge. In this research we developed a methodology for building error correction that can be applied to any other case study, where building density data and a local reference DEM data are available. This methodology was applied to Nairobi, Kenya using six global DEMs (SRTM, MERIT, ALOS, NASADEM, TanDEM-X 12 m, and TanDEM-X 90 m DEM). Our results show building error at highest building density varying between 1.25 m and 5.07 m for the DEMs used, with the MERIT DEM showing the smallest vertical height error from the reference DEM. The six DEMs were corrected by deriving a linear relationship between building density and DEM error. Our findings show that the removal of building density error resulted in the improvement of the vertical height accuracy of the global DEMs of up to 45% for MERIT and 40% for ALOS. This methodology was also applied to the Central Business District (CBD) area of Nairobi, characterized by taller buildings and high building density. The error parameters in the CBD area resulted to be between 15 to 45% higher than those of the Nairobi city wide area for the six global DEMs, thus providing further insights into the contribution of building heights to errors in global DEMs. Building height data is still unavailable on a global scale and our results show that global DEMs can be usefully corrected for building density errors in urban areas, even where specific building height data are not available.
Highlights
Rapid urban growth puts strain on existing infrastructure and discourages the preservation of natural habitat in favour of new housing developments, shopping malls, urban infrastructure, etc. that can exacerbate the problem of urban flooding
Despite significant advances in developing vegetation-corrected Digital Elevation Models (DEMs), there is limited understanding of DEM errors that can be attributed to building heights and building density in urban areas
The results show that the Multi Error removed Improved Terrain (MERIT) and TanDEM-X 12 m & 90 m global DEMs have lower vertical height errors in comparison to the NASA DEM (NASADEM), Shuttle Radar Topography Mission (SRTM) & ALOS DEMs if the standard deviation (SD) metric only is considered
Summary
Rapid urban growth puts strain on existing infrastructure and discourages the preservation of natural habitat in favour of new housing developments, shopping malls, urban infrastructure, etc. that can exacerbate the problem of urban flooding. Rapid urban growth puts strain on existing infrastructure and discourages the preservation of natural habitat in favour of new housing developments, shopping malls, urban infrastructure, etc. That can exacerbate the problem of urban flooding. Flooding is the most prevalent natural disaster, often characterised as a high intensity event that requires rapid emergency service response in order to minimise substantial human and economic losses (Apel et al 2009). Topography has been identified as a key method of estimating flood extent (Horritt and Bates 2001) and many models of flood extent rely on DEMs in order to simulate paths of water flow, flood extent and depth. Errors in DEMs (DEMs) can substantially affect the results of flood models (Stephens et al 2012; Hawker et al 2018).
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