Hydro-enforced and flattened bare earth DEM from 4ppsm lidar data

• Digital elevation models (DEMs) generated from LiDAR data offer a fast and cost-effective solution for terrain analysis. These include reflective-surface DEMs derived from first returns, which capture elevations of above-ground features, and bare-earth DEMs, providing precise measurements of the earth’s surface.

• Point cloud data is generated after computing elevation points from individual LiDAR returns, resulting in a ‘cloud’ of points that represent ground and above-ground features. These point clouds can be directly imported into various computer-aided design (CAD) programs for applications such as volume computations, visualization, fly-throughs, 3D modeling, line-of-sight analysis, feature extraction, orthorectification, and more.

• Classifications provided by Fugro adhere to all base Quality Level (QL) LiDAR classifications set by the United States Geological Survey (USGS): processed, unclassified, bare earth, low noise, water, ignored ground, bridge decks, and high noise. Additional customized classifications are available to meet specific client requirements, including buildings, culverts, roads, and low, medium, and high vegetation.

• Intensity images derived from LiDAR data resemble low-resolution photographs and are georeferenced for spatial accuracy. These images are valuable for extracting planimetric features and serve as ancillary inputs in LiDAR data processing workflows. Additionally, intensity images can be utilized to verify the horizontal accuracy of LiDAR data and assess other quality criteria.

• Contours derived from LiDAR data can be generated at intervals ranging from 1 to 5 feet, adhering to the National Map Accuracy Standards outlined by FEMA LiDAR mapping specifications and ASPRS standards.

• Hydro-flattening is a cartographic and aesthetic enhancement applied to digital elevation models (DEMs). This process involves extracting breaklines along water features within the LiDAR dataset to assign a consistent elevation to water bodies. Streams and rivers are hydro-flattened bank-to-bank and adjusted to ensure a downhill flow, accurately representing water movement in the terrain.

• Hydro-enforcement is a process used in hydraulic and hydrologic modeling to ensure accurate representation of water flow in terrain models. In a hydro-enforced model, the terrain is modified to remove false obstructions, such as bridges and culverts, maintaining drainage connectivity. This adjustment simulates how water flows naturally through these structures. Without hydro-enforcement, water would appear obstructed by topography, creating false pooling in areas where bridges or culverts are present.

• Land Use / Land Cover (LULC) data can be utilized to generate preliminary land-cover classifications, including open, scrub or shrub, urban, and forested areas. These classifications are valuable for hydrologic and hydraulic modeling, particularly in supporting floodplain mapping and analysis.

• Base mapping – lidar DEMs are accurate for image orthorectification as well as for contour generation

• Floodplain mapping – lidar data supports erosion forecasting, flood hazard analyses and hydrologic and hydraulic modelling

• Natural resources management – lidar data is used to calculate tree-stand heights, biomass, and timber density. It is also useful in establishing volume calculations for mineral extraction

• Transportation and utility corridor mapping – lidar data can supplement traditional ground and aerial surveys in the planning and design of new transportation and utility corridors, as well as ongoing maintenance of utility corridors

• Urban modeling – 3D models from bare-earth and reflective-surface lidar data can be used to analyse and visualise things like urban planning, line-of-sight studies and view-shed analysis

• Change detection – point clouds from multiple years of elevation data can be compared, to reveal areas of change and to track urban change, as well as for disaster mapping, forest restoration and shoreline mapping

Lidar dataset with value-added topographic mapping data created from the lidar point cloud.

Fugro provides lidar derived highest adjacent grade (HAG) and lowest adjacent grade (LAG) values for use on elevation certificates and other floodplain management needs.