Abstract
A significant portion of the Canadian Maritime coastline has been surveyed with airborne Light Detection and Ranging (LiDAR). The purpose of these surveys has been to map the risk of flooding from storm surges and projected long-term sea‑level rise from climate change and to include projects in all three Maritime Provinces: Prince Edward Island, New Brunswick, and Nova Scotia. LiDAR provides the required details in order to map the flood inundation from 1 to 2 m storm surge events, which cause coastal flooding in many locations in this region when they occur at high tide levels. The community of Annapolis Royal, Nova Scotia, adjacent to the Bay of Fundy, has been surveyed with LiDAR and a 1 m DEM (Digital Elevation Model) was constructed for the flood inundation mapping. Validation of the LiDAR using survey grade GPS indicates a vertical accuracy better than 30 cm. A benchmark storm, known as the Groundhog Day storm (February 1–3, 1976), was used to assess the flood maps and to illustrate the effects of different sea-level rise projections based on climate change scenarios if it were to re-occur in 100 years time. Near shore bathymetry has been merged with the LiDAR and local wind observations used to model the impact of significant waves during this benchmark storm. Long-term (ca. greater than 30 years) time series of water level observations from across the Bay of Fundy in Saint John, New Brunswick, have been used to estimate return periods of water levels under present and future sea-level rise conditions. Results indicate that under current sea-level rise conditions this storm has a 66 year return period. With a modest relative sea-level (RSL) rise of 80 cm/century this decreases to 44 years and, with a possible upper limit rise of 220 cm/century, this decreases further to 22 years. Due to the uncertainty of climate change scenarios and sea-level rise, flood inundation maps have been constructed at 10 cm increments up to the 9 m contour which represents an upper flood limit estimate in 100 years, based on the highest predicted tide, plus a 2 m storm surge and a RSL of 220 cm/century.
Highlights
Digital Elevation Models (DEMs) derived from aerial photography or other remote sensing systems such as the Shuttle Radar Topography Mission (SRTM) have degraded accuracies in forested areas
The Light Detection and Ranging (LiDAR) ‘ground’ and ‘non-ground’ points were used to construct triangulated irregular networks (TINs) based on the orthometric height that was linearly interpolated to a 1-m resolution digital surface model (DSM) (Figure 3)
The real-time kinematic (RTK) GPS points were compared to the LiDAR points within a 2 m horizontal distance resulting in a mean difference of 10 cm and a standard deviation of 12 cm, indicating the LiDAR data was within the vertical accuracy expected
Summary
Digital Elevation Models (DEMs) derived from aerial photography or other remote sensing systems such as the Shuttle Radar Topography Mission (SRTM) have degraded accuracies in forested areas. Light Detection and Ranging (LiDAR) is a remote sensing technology to derive very accurate elevation measurements of the earth’s surface. The benefit of LiDAR is that a narrow laser beam is directed from the aircraft towards the earth’s surface and reflected back in order to measure the range or distance from the aircraft to the ground. A portion of that beam has to make it through the gaps in the forest canopy and hit the ground in order to be reflected back to the aircraft. The LiDAR sensor records a series of points that represent what the laser pulse was reflected off and contains “hits” from the vegetation, buildings, and bare ground targets, for example. Sensors today are capable of recording intermediate pulse returns in addition to the first and last return
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