13695138-227f-4d85-9049-0a9cba9e1867 English ISO/IEC 8859-1 (also known as Latin 1) dataset dataset NERC EDS Environmental Information Data Centre Lancaster Environment Centre, Library Avenue, Bailrigg Lancaster LA1 4AP UK info@eidc.ac.uk https://eidc.ac.uk/ EIDC website The Environmental Information Data Centre (EIDC) is the UK's national data centre for terrestrial and freshwater sciences. information pointOfContact 2025-11-13T16:17:31 UK GEMINI 2.3 WGS 84 / UTM zone 13N Digital Surface Models for the South Saskatchewan River, Canada 2019-10-29 publication https://catalogue.ceh.ac.uk/id/13695138-227f-4d85-9049-0a9cba9e1867 10.5285/13695138-227f-4d85-9049-0a9cba9e1867 doi: Ashworth, P., Nicholas, A., Parsons, D., Sambrook Smith, G. (2019). Digital Surface Models for the South Saskatchewan River, Canada. NERC Environmental Information Data Centre 10.5285/13695138-227f-4d85-9049-0a9cba9e1867 Data were collected in 2015, 2016 and 2017 to provide Digital Surface Models (DSM) for two sections of the South Saskatchewan River, Canada. DSMs were generated using aerial plane images with a 0.06m ground resolution, captured at a height of c. 1500 m from a fixed-wing aeroplane with an UltraCamXp sensor. DSMs were generated as part of NERC project NE/L00738X/1. DSMs were constructed using imagery obtained on four occasions (13th May 2015; 2nd Sept 2016; 8th June 2017; and 12th June 2017). The dataset consists of eight DSMs; one for each of the two river sections on each of the four dates. Full details about this dataset can be found at https://doi.org/10.5285/13695138-227f-4d85-9049-0a9cba9e1867 Ashworth, P. University of Brighton p.ashworth@brighton.ac.uk author Nicholas, A. University of Exeter a.p.nicholas@exeter.ac.uk author Parsons, D. University of Hull d.parsons@hull.ac.uk author Sambrook Smith, G. University of Birmingham g.smith.4@bham.ac.uk https://orcid.org/0000-0002-3707-1182 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Nicholas, A. University of Exeter a.p.nicholas@exeter.ac.uk pointOfContact NERC EDS Environmental Information Data Centre info@eidc.ac.uk custodian NERC Environmental Information Data Centre info@eidc.ac.uk publisher digital land model GEMET - Concepts, version 4.1.3 2019-01-28 creation Modelling Canada Saskatchewan River Digital Surface Models otherRestrictions no limitations otherRestrictions © Natural Environment Research Council otherRestrictions This resource is available under the terms of the Open Government Licence otherRestrictions If you reuse this data, you should cite: Ashworth, P., Nicholas, A., Parsons, D., Sambrook Smith, G. (2019). Digital Surface Models for the South Saskatchewan River, Canada. NERC Environmental Information Data Centre https://doi.org/10.5285/13695138-227f-4d85-9049-0a9cba9e1867 textTable 1500 English utf8 inlandWaters environment 2015-05-13 2017-06-12 -107 -107.1 51.5 51.6 txt NERC EDS Environmental Information Data Centre info@eidc.ac.uk distributor https://data-package.ceh.ac.uk/data/13695138-227f-4d85-9049-0a9cba9e1867 Download the data Download a copy of this data download https://data-package.ceh.ac.uk/sd/13695138-227f-4d85-9049-0a9cba9e1867.zip Supporting information Supporting information available to assist in re-use of this dataset information dataset dataset Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 DSMs were constructed to provide information on the morphology or the river, and changes in morphology through time (e.g. due to erosion and deposition of sediment). DSMs were constructed using imagery obtained on four occasions (13th May 2015; 2nd Sept 2016; 8th June 2017; and 12th June 2017). The dataset consists of eight DSMs; one for each of the two river sections on each of the four dates. The DSM was constructed from photogrammetric quality aerial plane images with a 0.06m ground resolution that were captured at a height of c. 1500 m from a fixed-wing aeroplane with an UltraCamXp sensor. The DSM was constructed from the images using a three stage process: (1) An orthomosaic was generated from the aerial photography (using up to 160 images) by automated image matching using the SfM program Pix4D (https://pix4d.com/) with the 'large frame' supplementary software package. Bundle adjustment was undertaken using Pix4D’s key point matching system optimised for aerial nadir imagery. Camera properties were specified using calibration certificates and were not allowed to vary during the calculation. A point cloud was then derived following the bundle adjustment. (2) The point cloud was checked for residual tilt using a network of Ground Control Points with coordinates that were determined by RTK differential GPS survey. The corrected point cloud density was reduced to a resolution of 0.5 m and the resulting dataset was filtered in MATLAB using a Chauvenet-type criterion. This procedure was implemented to derive the DSM in dry (non-submerged) areas of the river. (3) In wet (submerged) areas, bed elevations were derived using a depth-brightness model as follows. First, water surface elevations at the interface between wet and dry areas of the river bed were extracted from the corrected point cloud and interpolated to generate a water surface elevation field for the submerged bed areas. Second, water depth measurements made at the time of image acquisition were located on the orthomosaic of the river, and pixel brightness values were extracted at these locations. A log-linear regression between water depth and pixel brightness was then derived, and this relationship was used to model water depth for all sub-merged bed areas. Bed elevations in these areas were determined by subtracting the predicted depth from the water surface elevation. The final DSM was derived by combining elevation values for the dry and wet bed areas.