Benchmarking stereo-derived DSMs to lidar by land cover and slope for resource development in northern Ontario, Canada

ABSTRACT

Topographic and elevation data are essential in the development of supporting infrastructure around mining sites. The de facto standard for acquiring elevation data is through light detection and ranging (lidar). The high labour and monetary cost of acquiring lidar has fostered more cost-effective approaches for creating elevation models that use stereo photogrammetry. To assess the accuracy of stereo-photogrammetry-derived elevation models and their potential application, we benchmark satellite (Worldview-2) and aircraft (South Central Ontario Orthoimagery Project; SCOOP) stereo-derived digital surface models (DSMs) against a lidar-derived DSM. Our results show that both stereo-derived DSMs have strong monotonic correlations with lidar across a range of land-cover types and slopes. The overall vertical accuracy of Worldview-2 and SCOOP DSMs are similar and do not meet the United States National Digital Elevation Program (NDEP) standards. However, accuracy assessment across land-cover types and slope categories show that specific land cover types (i.e. grass, row crops/pasture, sparse vegetation and marsh) on gently sloping terrain compare well to lidar data and meet NDEP accuracy standards. We situate the presented research in the context of northern resource development and discuss opportunities to improve the vertical accuracy of stereo-derived DSMs, for example, through unmanned aerial systems.

Acknowledgements

The authors would like to thank Steve Leney from the Ontario Ministry of Natural Resources and Andrei Balulescu from University of Waterloo for providing us with the DSMs and ortho images. The authors would also like to thank Kent Todd, Aneitha Mohammed, and Dave Nesbitt for providing metadata. Finally, the authors thank Nick Chaulk for his contributions to the land cover map digitization.

Disclosure statement

No potential conflict of interest was reported by the authors.