Skip to Content

Construction of the Annapolis Valley Digital Elevation Model from LiDAR

Applied Geomatics Research Group
Centre of Geographic Sciences
NSCC, Middleton, NS
Tel. 902 825 5475
Fax 902 825 5479
email: timothy [dot] webster [at] nscc [dot] ca

ABSTRACT

High-resolution Digital Elevation Models (DEMs) have been derived from a new remote sensing technique known as airborne laser altimetry or LiDAR. The LiDAR surveys were conducted in the summer of 2000 and the spring of 2003 and 2004 for the Annapolis valley region Nova Scotia. The surveys were flown by two private sector companies utilizing three different LiDAR systems over the course of the project. Funding for the project was provided by a grant to AGRG by the Canada Foundation for Innovation to conduct applied geomatics research in the coastal zone. Although one of the areas had to be reflown in order to meet the accuracy specifications of the survey, all data have met the required accuracy specifications. The LiDAR data were delivered separated into ‘ground’ and ‘non-ground’ points which have been used to construct DEMs and Digital Surface Models (DSMs) within the ArcGIS environment. The resulting surfaces have been used to demonstrate the benefits of LiDAR technology in the fields of earth sciences, both bedrock and surficial mapping, and for flood risk mapping from coastal storm surge events and future sea-level rise from climate change.

The different surveys of the valley have been merged into one continuous elevation model at a 2 m cell size. This surface has been used to construct a colour shaded relief map that is now available to view as a google map product.

Introduction

Landscapes are influenced by several factors including geology, soils, climate, glaciations, topography, and vegetation cover, among others. In order to study landscapes and their evolution, we attempt to map these different factors. The digital compilation of maps and data layers is accomplished within a Geographic Information System (GIS) environment. One of the most critical layers to describe a landscape is the topography or elevation model of the terrain. In this research, a remote sensing technique known as Light Detection and Ranging (LiDAR) was used to acquire high-resolution topographic data from an aircraft. These topographic measurements were then used to construct a Digital Elevation Model (DEM) for the region of the Annapolis Valley and Bay of Fundy coast in Nova Scotia (Figure 1). The detail and resolution of these new maps is ten times better than previous available DEM data for the area. Generally, DEMs derived from aerial photography or other remote sensing systems such as the Shuttle Radar Topography Mission (SRTM) have degraded accuracies in forested areas and have horizontal resolutions of ca. 20 – 30 m. In this region, previous topographic maps derived from aerial photo surveys were hampered in forested areas where the ground was obscured by the trees and accurate measurements of the terrain were difficult. 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. The beam divergence is typically very small (0.3 rmad), resulting in a laser footprint diameter of 20-30 cm on the ground, depending on flying height. Only 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. Thus in the forest, if one can see patches of sky above them, there is a good chance the laser beam will partially make it through a gap and make it to the ground or near ground features such as dense shrubs. A rotating mirror (galvanometer) is used to direct the laser pulses in a profile that is perpendicular to the aircraft flight direction. As the aircraft advances, the oscillating mirror effectively causes the laser pulses to sample a swath below the aircraft in a saw tooth pattern. The aircraft’s trajectory (position) is precisely calculated by using survey grade GPS and an inertial measurement unit (IMU) to measure the attitude (pitch, roll, and heading) and the position of the aircraft. The three-dimensional location of the reflected LiDAR pulse can then be positioned in the GPS World Geodetic System of 1984 (WGS84) mapping system. Since the laser pulse can partially hit several targets (top of canopy, branches, tree trunk, buildings, shrubs, and ground) the LiDAR sensor can record several returns. Earlier LiDAR sensors, ca 2003, could record a single return, first or last. Regardless of which return was selected, the recorded points typically captured both the ground and non-ground object (trees, buildings), however selecting the last return will give a higher percentage of ground returns. Today’s sensors are capable of capturing multiple returns, however many surveys record the first and last returns only to reduce the data volume.

Although the effect of DEM resolution on measuring different hydrologic and geomorphic properties has been examined (e.g. Wolock and Price, 1994; Zhang and Montgomery, 1994; Goa, 1997; Zang et al., 1994; Walker and Willgoose, 1999), most of these studies focussed on the effects of different grid cell size interpolated from similar source data. This study is different in that its focused on the enhanced DEM resolution and precision as a result of advances in laser altimetry data acquisition technology. In glaciated terrains such as this region of the Fundy Basin, unconsolidated sediments commonly mask bedrock features. Since LIDAR systems measure surface topography, their applicability in mapping surficial deposits and glacial landforms is important both from a landscape evolution perspective and also from an economic perspective for the identification of aggregate deposits.

LiDAR has been used in a number of geoscience applications, including the analysis of river networks (Stock et al., 2005), the generation of cross-sections across rivers (Charlton et al., 2003), in general glaciology (Krabill et al., 1995, 2000), groundwater monitoring (Harding and Berghoff, 2000), investigation of landslides (McKean and Roering, 2003), and in the mapping of tectonic fault scarps and geomorphic features (Haugerud et al., 2003). LiDAR has been used to demonstrate improvements in mapping bedrock and surfical geology as well as landscape metrics such as stream incision, and to resolve and map the individual flow units of the North Mountain Basalt and the identification of crater structures within the lower flow unit (Webster, 2005a).

The LiDAR points and surfaces are generally expected to have an absolute vertical error less than 30 cm, and typically less than 15 cm. Independent survey grade GPS measurements have been taken to validate the LiDAR points and derived surface models.   Details of each survey will be presented later in this paper. Three research papers have been published on the validation of these different LiDAR datasets; GeoCarto (Webster, 2005b –  PDF), Computers & GeoScience (Webster & Dias, 2006 – PDF), and the book GIS for Coastal Zone Management, chapter 15 (Webster, Christian, Sangster, and Kingston, 2004 – PDF TF1714_CH15).

In addition to the improved elevation accuracy and detail of these new maps, these data have been extremely useful for scientific research in earth science. Six research papers have been published utilizing these data in the fields of  geology (bedrock and surficial) and coastal flood risk mapping; Canadian Journal of Earth Sciences (Webster, Murphy and Gosse, 2006 – PDF), Canadian Journal of Remote Sensing (Webster, Murphy, Gosse, and Spooner, 2006 – link PDF; Brennan and Webster, 2006 – PDF; Webster, Templin, Ferguson, and Dickie, 2009 – link draft PDF), Geomatica (Webster, Mosher, and Pearson, 2008), and the book Risk Analysis VI Simulations and Hazard Mitigation (Webster and Stiff – link PDF).

The region was covered by a total of 4 LiDAR surveys from 2000 to 2004. The LiDAR sensor records a series of points that represent what the laser pulse was reflected off of and contains “hits’ from the vegetation, buildings, and bare ground targets for example. The points were processed in the computer and classified into ‘ground’ and ‘non-ground’ targets by the data provider. This process evaluated a cluster of points, assuming that the lowest points represent the ground. The algorithm begins building a surface from these low points and other higher points are then evaluated against the surface based on a set of thresholds. Points with abrupt vertical changes in height compared to other points are not considered to be ground, since they would typically represent the roof of a building or top of a tree. The classification of raw LiDAR points is an active area of research and this method does not produce 100% accurate results thus some ground points maybe classified and ‘non-ground’ and vise versa. A continuous surface was interpolated from the ‘ground’ points to construct a “bare earth” DEM. Since the LiDAR sensor can acquire more ‘ground’ measurements in the forest and in open areas than traditional methods such as photogrammetry, the resultant high-resolution DEM provides new images never seen before of the earth’s surface. The LiDAR point spacing on the ground for these surveys was approximately every 1-4 m depending on the land cover (dense coniferous forest results in sparser ground point spacing). As a result, the DEM surfaces were constructed at a grid cell size of 1-2 m.

Study Area

The study area is located within the Annapolis Valley region of Nova Scotia, Canada and is part of the Mesozoic Fundy Basin (Figure 1).

Figure 1 Fundy Mesozoic Basin (shaded area). The background image is a Radarsat-1 mosaic of Nova Scotia, colour coded by topographic information (green=low and red=high elevations) and bathymetry (blue shades).

Figure 1 Fundy Mesozoic Basin (shaded area). The background image is a Radarsat-1 mosaic of Nova Scotia, colour coded by topographic information (green=low and red=high elevations) and bathymetry (blue shades).

The LIDAR data cover over 2800 km2 of the basin and include the basin’s three physiographic features; the North Mountain, South Mountain and the intervening Annapolis Valley. The Annapolis Valley is predominantly underlain by Triassic sedimentary rocks (Blomidon and Wolfville formations), flanked by the Jurassic North Mountain Basalt (NMB) to the north and Devonian South Mountain Batholith to the south (Keppie, 2000) (Figure 2). The North Mountain dips gently to the northwest, forms the southeast limb of a regional syncline (Withjack et al., 1995), and is crosscut by north to northeast-trending faults and fractures that exhibit dextral displacement (Olsen and Schlische, 1990; Schlische and Ackermann, 1995).  The South Mountain forms the southern margin of the Annapolis Valley and is underlain by ca. 370 Ma granitoid rocks of the South Mountain Batholith (SMB) and by the Cambrian-Ordovician Meguma Supergroup (Keppie, 2000) (Figure2).

 

Figure 2 Bedrock geology of the Annapolis Valley (source NS Department of Natural Resources). The North Mountain Basalt forms the nothern extent and is adjacent to the bay of Fundy and the South Mountain Batholith (granite) bounds the southern extent.

Figure 2 Bedrock geology of the Annapolis Valley (source NS Department of Natural Resources). The North Mountain Basalt forms the nothern extent and is adjacent to the bay of Fundy and the South Mountain Batholith (granite) bounds the southern extent.

The study area lies at the margin of the Wisconsinan Laurentide ice sheet and has been affected by repeated episodes of glaciation until ca. 12 ka (Stea and Mott, 1998). The surficial geology deposits range from high clay content glacial till to sand and gravel glacial outwash plains within the valley floor (Figure 3).

Figure 3 Surficial geology of the Annapolis Valley and area (source NS Department of Natural Resources). The surficial geology map is merged with a regional 20 m shaded relief DEM (source NS Geomatics Centre).

Figure 3 Surficial geology of the Annapolis Valley and area (source NS Department of Natural Resources). The surficial geology map is merged with a regional 20 m shaded relief DEM (source NS Geomatics Centre).

The earliest ice flows were eastward and southeastward from an Appalachian or Laurentide ice source (Stea et al., 1998). North Mountain Basalt (NMB) erratics (boulders) were transported by ice southeastward up to 120 km to the Atlantic Coast (Stea et al., 1998; Lewis et al., 1998). The second major ice-flow was southward and southwestward from the Escuminac Ice Centre in the Prince Edward Island (PEI) region and is recorded by southward-trending striae crossing earlier southeastward-trending striae (Stea et al., 1998). The Carboniferous red beds of PEI were eroded and transported southward and deposited in the Lawrencetown Till (Figure 3, 12. Silty Till Plain). Ice then flowed northwestward and southward from the Scotian Ice Divide across the axis of Nova Scotia (Stea et al., 1998). Locally ice flowed from the Scotian Divide northwestward over the NMB into the Bay of Fundy transporting South Mountain erratics onto the North Mountain (Hickox, 1962). With the late-glacial rise of relative sea-level, ice margins were probably destabilized, with ice flow increasingly directed into the Bay of Fundy to merge with southwestward ice streams from New Brunswick (Stea et al., 1998). Locally, ice flowed westward from the eastern end of the Annapolis Valley (Rivard et al., 2007; Stea and Mott, 1998; Purdy, 1951). The relative sea-level (RSL) history of the region is complicated and varies spatially along the Bay of Fundy. Raised beaches and deltas dated at 14 to 12 ka 14C occur along the shoreline of the bay (Stea and Mott, 1998).

The land cover on the North Mountain is influenced by the occurrence of the till cover; farmland (pastures and hayfields) and mixed forest dominate where the till is thickest, and dominantly mixed forest cover where the till in thinnest. The valley floor is dominated by farmland (crops) and the major population centres are located in the valley. The South Mountain land cover consists of mixed farmland (apple orchards and hayfields) on the north-slope and mixed forest on the upland. The coastline varies between gently sloping bedrock platforms and ca. 25 m cliffs that occur in embayments.

Methods
LiDAR survey configurations

The complete study area was covered during four LiDAR surveys utilizing different sensor configurations over a four year period (Figure 4).

 

Figure 4 LiDAR composite colour shaded relief map. Polygons denote the different LiDAR surveys involved in completing the coverage of the Annapolis Valley.

Figure 4 LiDAR composite colour shaded relief map. Polygons denote the different LiDAR surveys involved in completing the coverage of the Annapolis Valley.

For the LIDAR acquisition in 2000, the survey was conducted between July 6 and July 13 and consisted of an area of 350 km2 (Figure 4). An Optech ALTM1020 sensor mounted in a Navajo P31 twin-engine fixed-wing aircraft was used in the survey (Figure 5 A). The LIDAR operated at a 5000 Hz laser repetition rate along with the scanning mirror operating at 15 Hz to direct the laser pulses across the swath. The system used a near-infrared laser operating at 1047 nm and has a beam divergence of 0.25 mrad. The flying altitude of 800 m resulted in the laser ground footprint diameter of 25 cm with an average point spacing of 2-3 m. Since a “bare earth” DEM was one of the desired outcomes of the survey, the LIDAR unit was set to record the last return pulse.
For the LIDAR acquisitions in 2003, the surveys were conducted between April 30th and May 21st, 2003 and consisted of an area of 1869 km2 (Figure 4). The Mark I is a first-return LiDAR system that was originally designed for corridor mapping and was mounted on a pod fixed to the underside of a Bell 206L helicopter (Figure 5 B, C). The sensor operated at 10,000 Hz repetition rate along with the scanning mirror operating at 15 Hz to direct the laser pulses across the swath. Two configurations were used with point spacing varying between 3 m and 0.6 m. The flying altitudes of 600 m and 300 m for these configurations resulted in a laser footprint diameter of 18 cm and 9 cm respectively (Figure 5 B, C).

For the LIDAR acquisition in 2004, the survey was conducted between April 20 and April 25 and consisted of 595 km2 (Figure 4). The Mark II system is capable of recording the first and last returns and the intensity of one of the returns and was mounted on a pod that was fixed to the underside of a Bell 206L helicopter (Figure 5 D). It was decided to acquire the intensity on alternating returns; thus, every other first and last return would record the intensity. The system utilizes a laser with a wavelength of 1064 nm and beam divergence of 0.45 mrad and operated at a 30,000 Hz laser repetition rate along with the scanning mirror operating at 17 Hz to direct the laser pulses across the swath. The survey configuration had a point spacing of 1 m at an altitude of 800 m with a laser footprint diameter of 36 cm (Figure 5 D). Because the Mark II sensor is capable of recording the first and last returns, the wider laser beam could still partially penetrate the vegetation canopy and reflect off the ground or near-ground surface and be measured as the last returning pulse. The Mark II has improved precision to better than ±15 cm in the vertical as a result of the higher-precision laser ranging system and IMU.

Figure 5 Different LiDAR survey configurations for the four acquisitions used to construct the entire DEM. (A) July 2000 survey with Optech 1250 sensor, (B) May 2003 survey with Mark 1 sensor, (C) May 2003 high-resolution survey with Mark 1 sensor, (D) April 2004 survey with Mark 2 sensor.

Figure 5 Different LiDAR survey configurations for the four acquisitions used to construct the entire DEM. (A) July 2000 survey with Optech 1250 sensor, (B) May 2003 survey with Mark 1 sensor, (C) May 2003 high-resolution survey with Mark 1 sensor, (D) April 2004 survey with Mark 2 sensor.

LiDAR surface construction and validation

The LiDAR data were delivered as ‘ground’ and ‘non-ground’ ASCII files separated into 4 km × 4 km tiles for the 2000 survey and in 2 km x 2 km tiles for the 2003 and 2004 surveys. Each LiDAR point contained the following attributes: UTM easting, UTM northing, ellipsoidal height, orthometric height (referenced to the Canadian Geodetic Vertical Datum 1928 (CGVD28) ~mean sea level), GPS time, echo code, and flight line number, and intensity (2004 data only). The data were processed into ArcInfo™ GIS point coverages, and different surfaces were constructed. The 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). The ground points were used to construct a second grid using the same method that represented a “bare earth” digital elevation model (DEM).

Real-time kinematic (RTK) GPS surveys were conducted to collect on the ground checkpoints for each of the LiDAR study areas using a Leica GPS System 500 that consisted of a rover and a base station. The baselines were kept below 15 km in length, allowing the RTK GPS rover to achieve a vertical precision of 3 cm or better. The GPS data were post-processed and orthometric heights were computed and used to compare with the LiDAR points and surfaces. The heights of the LiDAR point data were validated using a technique described in Webster and Dias (2006). The technique uses the GPS points to compare LiDAR points within a search radius around each GPS point specified by the user. For this study a comparison of the resultant LiDAR DEMs and the GPS points will be reported following methods outlined by Webster (2005b).

Results

The LiDAR DEMs from the different surveys were constructed and used to compose one very large DEM. This surface model was then used to construct a grey scale shaded relief map, with the sun illumination from the northwest (335o) at a zenith angle of 45o with a 5-times vertical exaggeration applied to the terrain heights. Colour was then applied to the DEM based on elevation, from below sea-level (shades of blue), to low lying land (green through yellow) to the highest point along the North Mountain (ca 265 m) (red). The colours for figure 1 and 4 are coded such that the terrain appears in 3-D if viewed with ChromadepthTM glasses. The colourized DEM is then merged with the grey scale shaded relief map in order to provide the texture of the terrain as a result of the sun shading effect. The resultant model was then manipulated into a google map format for display on the web.

The different DEMs were also used to assess their accuracy based on the GPS check points collected. In general, all datasets met the vertical accuracy specifications of 30 cm and generally displayed an average difference in height between the DEM and GPS checkpoints of less than 15 cm.
The GPS check points were acquired utilizing RTK techniques with the GPS antenna mounted on a vehicle. In many cases GPS points collected over bridges had to be removed since these features were not classified as ground in the LiDAR points cloud and thus were not represented in the LiDAR bare earth DEM.

 

Figure 6 Location of GPS check points for validating the three derived LiDAR DEMs; 2000, 2003, and 2004. Statistics of the difference between GPS and DEM heights of the surveys are shown on the right of the figure.

Figure 6 Location of GPS check points for validating the three derived LiDAR DEMs; 2000, 2003, and 2004. Statistics of the difference between GPS and DEM heights of the surveys are shown on the right of the figure.

Conclusion

The use of high resolution LiDAR DEMs provide a significantly clearer and more accurate representation of the ‘bare earth’ terrain. These new DEMs have been used to enhance mapping of bedrock volcanic basalt flows and flow units, and to identify glacial landforms. Although the areas have been mapped (bedrock & surficial geology) using traditional aerial photography methods this research highlights the additional details that were extracted from the LiDAR data. In this region we experience storm surges of a magnitude of 1-2 m above normal tidal levels. This research has also demonstrated how these new DEM maps can be used to accurately predict areas at risk of coastal flooding. In addition they can be used to predict future areas at risk as a result of increased sea-level rise from climate change.

Bibliography
  • Brennen, R. and Webster, T.L. 2006. Object Oriented Land Cover Classification of LiDAR Derived Surfaces. Canadian Journal of Remote Sensing, Vol. 32, No. 2, pp. 167-172.Charlton, M.E., Large, A.R., and Fuller, I.C. 2003. Application of airborne LIDAR in River Environments: The River Coquet, Northumberland, UK. Earth Surface Processes and Landforms, Vol. 28, pp. 299-306.

    Ferguson, M., Webster, T., Gosse, J.C. 2007.  The Application of High-Resolution Laser Altimetry to Deglaciation Dynamics: Annapolis Royal, Nova Scotia.  Unpublished Honours Thesis, Dalhousie University.
     
    Goa, J. 1997. Resolution and accuracy of terrain representation by grid DEMs at micro scale. International Journal of Geographical Information Science. Vol. 11, No. 2, pp. 199-212.

    Harding, D.L., and Berghoff, G.S., 2000. Fault scarp detection beneath dense vegetation cover: Airborne LiDAR mapping of the Seatle fault zone, Bainbridge Island, Washington State. In Proceedings of the American Society of Photogrammetry and Remote Sensing Annual Conference, Washington, D.C., pp. 9.

    Harris , J. R. 2008. Remote Predictive Mapping: An aid to northern mapping; Geological Survey of Canada, Open File 5643.

    Haugerud, R.A., Harding, D.J., Johnson, S.Y., Harless, J.L., Weaver, C.S., and Sherrod, B.L., 2003. High-resolution LiDAR topography of the Puget Lowland-A bonanza for earth science. Geological Society of America Today, Vol. 13, No. 6, pp. 4-10.

    Hickox, C.F. Jr. 1962. Pleistocene geology of the Central Annapolis Valley, Nova Scotia. Nova Scotia Department of Mines Memoir 5, 36 p.

    Keppie, J.D. 2000. Geological Map of the Province of Nova Scotia. Nova Scotia Department of Natural Resources Minerals and Energy Branch, Map ME 2000-1.

    Krabill, W.B., Thomas, R.H., Martin, C.F., Swift, R.N. and Frederick, E.B. 1995. Accuracy of airborne laser altimetry over the Greenland ice sheet. International Journal of Remote Sensing, Vol. 16, pp. 1211-1222.

    Krabill, W., Abdalati, W., Frederick, E., Manizade, S., Martin, C., Sonntag, J., Swift, R., Thomas, R.,  Wright, W. and Yungel, J. 2000. Greenland Ice Sheet: high-elevation balance and peripheral thinning. Science, Vol. 289, pp. 428-430.

    Lewis, C.F.M., Taylor, B.B., Stea, R.R., Fader, G.B.J., Horne, R.J., MacNeill, S.G. and Moore, J.G. 1998. Earth Science and Engineering: Urban Development in the Metropolitan Halifax Region. In Urban Geology of Canadian Cities, Geological Association of Canada Special Paper 42. Edited by Karrow, P.F. and White, O.L. pp. 409-444.

    MacNeill, R. H. 1956. Surficial geology maps of Nova Scotia [21H08 west, 21H01 east, 21A13 east]. Nova Scotia Research Foundation, Dartmouth, Nova Scotia, Scale 1:50,000.
     
    McKean, J. and Roering, J. 2003. Objective landslide detection and surface morphology mapping using high-resolution airborne laser altimetry. Geomorphology, Vol. 1412, pp. 1-21.

    Olsen, P. E and Schlische, R.W. 1990. Transtensional arm of the early Mesozoic Fundy rift basin: Penecontemporaneous faulting and sedimentation. Geology, Vol. 18, pp. 695-698.

    Paradis, S.J., Bolduc, A.M., and Stea, R.R. 2005. Surficial Geology, Annapolis Valley, Nova Scotia. Geological Survey of Canada, Open File 5276, Scale 1:100,000.

    Parrot, R.D., Todd, B.J., Shaw, J., Hughs Clarke, J., Griffin, J. MacGowan, B., Lamplugh, M., and Webster, T. 2008. Integration of Multibeam Bathymetry and LiDAR Surveys of the Bay of Fundy, Canada. Proceedings of the Canadian Hydrographic Conference and National Surveyors Conference, 2008.

    Purdy, C.A. 1951, Pleistocene geology of the Kentville area, Nova Scotia. Unpublish MSc thesis, Acadia University, Wolfville, Nova Scotia 51 p.

    Rivard, C., Deblonde, C., Boivin, R., Bolduc, A., Paradis, S.J., Paradis, D., Liao, S., Gauthier, M.J., Blackmore, A., Trépanier, S., Castonguay, S., Drage, J., and Michad, Y. 2007: Canadian groundwater inventory: Hydrogeological atlas of the Annapolis Valley, Nova Scotia, Geological Survey of Canada,  Open File 5541, 128 p.

    Schlische, R.W., Ackermann, R.V. 1995. Kinematic significance of sediment-filled fissures in the North Mountain Basalt, Fundy rift basin, Nova Scotia, Canada. Journal of Structural Geology, Vol. 17, No. 7, pp. 987-996.

    Stea, R.R, Connely, H. and Brown, Y. 1992. Surfiicial Geology of the Province of Nova Scotia. Map 92-3, scale 1:500,000. Nova Scotia Department of Natural resources, Mines and Energy Branch.

    Stea, R.R. and Mott, R.J. 1998. Deglaciation of Nova Scotia: Stratigraphy and Chronology of Lake Sediment Cores and Buried Organic Sections. Geographie physique et Quaternaire, Vol 50, No. 1, pp. 3-21.

    Stea, R.R., Piper, D.J.W, Fader, G.B.J., and Boyd, R. 1998. Wisconsinan glacial and sea level history of Maritime Canada and the adjacent continental shelf: A correlation of land and sea events. Geological Society of America Bulletin, Vol. 110, No. 7, pp. 821-845.

    Stock, J.D., Montgomery, D. R, Collins, B.D., Dietrich, W.E., and Sklar, L. 2005. Field measurements on incision rates following bedrock exposure: Implications for process controls on the long profiles of valleys cut by rivers and debris flows. Geological Society of America Bulletin. 117: 174-194.

    Templin, A. 2006. Characterization of Surficial Landforms within the Eastern Annapolis Valley Utilizing High-resolution elevation data from laser Altimetry. Unpublished research report, Applied Geomatics Research Group, Nova Scotia Community College.

    Walker, J.P. and Willgoose, G.R. 1999. On the effect of digital elevation model accuracy on hydrology and geomorphology. Water Resources Research, Vol. 35, No. 7, pp. 2259-2268.

    Webster, T., Templin, A., Ferguson, M., and Dickie, G. 2009 (accepted). Remote Predictive Mapping of Aggregate Deposits using LiDAR. Canadian Journal of Remote Sensing, Vol. xx, No. xx, pp. xx-xx.

    Webster, T., Murphy, J.B., Quinn, D.P. 2009 (accepted). Remote Predictive Mapping of a Potential Vent Complex in the Southern Antigonish Highlands using LiDAR, Magnetics & Field Mapping. Canadian Journal of Remote Sensing, Vol. xx, No. xx, pp. xx-xx.

    Webster, T.L., Mosher, R., Pearson, M. (2008). A Coastal Zone Decision Support System to generate Flood Risk Maps from Storm Surge Events and Sea Level Rise. Geomatica.Vol. 62, No. 4, pp. 393-406.

    Webster, T. and Stiff, D. (2008). The prediction and mapping of coastal flood risk associated with storm surge events and long-term sea level changes. In Risk Analysis VI Simulations and Hazard Mitigation. WIT Press. Edited by Brebbia, C.A. and Beriatos, E. pp. 129-139.

    Webster, T.L., and Dias, G. 2006. An automated GIS procedure for comparing GPS and proximal LIDAR ground elevations. Computers & Geosciences, Vol. 32/6, pp. 713-726.

    Webster, T.L., Murphy, J.B., Gosse, J.C., and Spooner, I. 2006 A. The application of LIDAR-derived DEM analysis for geological mapping: An example from the Fundy Basin, Nova Scotia, Canada. Canadian Journal of Remote Sensing, Vol. 32, No. 2, pp. 173-193.

    Webster, T.L., Murphy, J.B., and Gosse, J.C. 2006 B. Mapping subtle structures with LIDAR: Phreomagmatic rootless cones in the North Mountain Basalt, Nova Scotia. Canadian Journal of Earth Sciences, Vol. 43, pp. 157-176.

    Webster, T.L. 2005a. The application of high-resolution LIDAR DEM data to landscape evolution: an example from the Fundy Basin, Nova Scotia, Canada. Ph.D. thesis, Dalhousie University, Halifax, N.S.

    Webster, T.L. 2005b. LIDAR validation using GIS: A case study comparison between two LIDAR collection methods. GeoCarto International. Vol. 20, No. 4, pp. 11-19.

    Webster, T.L., and Forbes, D.L. 2005. Using Airborne LIDAR to map exposure of Coastal Areas in Maritime Canada to Flooding from Storm-Surge events: A Review of recent experience. Canadian Coastal Conference, Dartmouth, Nova Scotia.

    Webster, T.L., Christian, M., Sangster, C., and Kingston, D. 2005. High-Resolution Elevation and Image Data within the Bay of Fundy Coastal Zone, Nova Scotia, Canada. In GIS for Coastal Zone Management, Edited by Bartllet, D. and Smith, J. pp.195-218.

    Withjack, M. O., Olsen, P.E., and Schlische, R.W., 1995. Tectonic evolution of the Fundy rift basin, Canada: Evidence of extension and shortening during passive margin development. Tectonics, Vol. 14, No. 2, pp. 390-405.

    Wolock, D.M. and Price, C.V. 1994. Effects of Digital Elevation Map Scale and Data Resolution on a Topographically Based Watershed Model. Water Resources Research. Vol. 30, No. 11, pp. 3041-52.

    Zhang, W. and Montgomery, D.R. 1994. Digital elevation model grid size, landscape representation, and hydrological simulations. Water Resources Research, Vol. 30, No. 4, pp. 1019-1028.
Tagged in: