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Technical information: LiDAR data and derived products

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Using Light Detection and Ranging (LiDAR) point cloud data, we can create a wide range of spatial information products (often referred to as ‘derived products’) to help you understand and address geospatial challenges.

Classified LiDAR

What is Classified LiDAR?

Classified LiDAR identifies features within the raw LiDAR data and assigns them a value based on their characteristics. This includes ground features (bare earth), and above ground features such as vegetation, buildings and infrastructure.

Classified LiDAR represents the initial data processing step. It makes complex information easier to work with and powers the development of more complex derived products.

Why use Classified LiDAR?

  • Classified LiDAR allows for layered analysis and filtering by feature type.
  • It is completed in line with standard classifications (International Society for Photogrammetry and Remote Sensing LAS format) but can include specific classifications to suit your project/data end-use.
  • Classified LiDAR allows data sets to be compared easily through a standardised spatial ‘language’.
Digital Elevation Model (DEM)

What is a Digital Elevation Model (DEM)?

Digital Elevation Models (DEMs) use an evenly spaced grid of values that represent the surface of the ground (also known as a bare earth model). DEMs are generally provided in a raster format with 1 metre grid spacing to support import directly into CAD/GIS software systems.

Why use a Digital Elevation Model (DEM)?

  • DEMs provide a cost-effective alternative to traditional detail surveys completed by ground survey crews.
  • They support landowners/managers to better understand spatial issues such as site drainage and hydrology, subsidence, or erosion and they can inform route/site selection for buildings infrastructure and preliminary design work.
Digital Terrain Model (DTM)

What is a Digital Terrain Model (DTM)?

Digital Terrain Models (DTM) are a more complex form of bare earth model, with every point in a Digital Terrain Model (DTM) representing an actual LiDAR laser strike on the ground. DTMs are the most detailed LiDAR dataset available and are typically delivered in ASCII XYZ format (which can be imported into the widest possible range of software).

Why use a Digital Terrain Model (DTM)?

  • DTMs are best used when very accurate surface data measurements are required.
  • DTMs are often used for mining and quarry volume calculations, erosion and deposition studies, and engineering design.
Digital Terrain Slope Model (DTS)

What is a Digital Terrain Slope Model (DTS)?

Digital Terrain Slope (DTS) Models calculate ground slope as a percentage over a grid-divided surface. DTS models are generally provided in a raster format with 1 metre grid spacing to support import directly into a client’s nominated CAD/GIS software system.

Why use a Digital Terrain Slope Model (DTS)?

  • DTS models help engineers, planners and environmental custodians to identify areas of steep terrain quickly.
  • They are commonly used for engineering design, land use planning, development schemes, flood and drainage modelling, or route selection for infrastructure.
Canopy Height Model (CHM)

What is a Canopy Height Model (CHM)?

A Canopy Height Model (CHM) is a 3D model showing the height of vegetation above ground level (non-vegetation features are excluded).

Why use a Canopy Height Model (CHM)?

  • CHMs are the best method for capturing vegetation height metrics for small or large areas, and are used for detailed vegetation monitoring and assessment.
  • CHMs can assist land managers to identify vegetation species (where height is a determining factor) and identify vegetation encroachment into infrastructure corridors etc.
Foliage Cover Model (FCM)

What is a Foliage Cover Model (FCM)?

Foliage Cover Models (FCM) measure the number of LiDAR returns that strike vegetation features before striking the ground. They are used to measure vegetation density below the canopy level.

Why use a Foliage Cover Model (FCM)?

  • FCMs are useful for analysing vegetation makeup and monitoring vegetation health.
  • They are regularly used by forestry agencies for yield estimation, species identification (where understory growth can be used as an identifier), and determining potential sunlight penetration to the understory.
  • FCMs can help land managers to qualify whether ground survey/truthing is required, and can assist with identification across difficult-to-access areas of land/vegetation.
Waveform Data Packets

What are Waveform Data Packets?

Waveform Data Packets represent additional data that is only available when a full-waveform LiDAR sensor like RPS’ is used for capture. They contain information including wavelength and signal strength over the entire beam's path to the ground, and return back to the sensor.

Why use Waveform Data Packets?

  • Waveform Data Packets are primarily used for vegetation analysis, though there is potential for a wider range of applications.
  • Waveform Data Packets can be used to provide specific information about nominated features based on specific waveform behaviours.
GeoNet Drainage

What is GeoNet Drainage?

GeoNet Drainage is a computational tool that supports the automatic extraction of channel networks and geomorphic features from LiDAR data. The tool combines non-linear filtering for data pre-processing and is a cost-effective solution for identifying and extracting drainage features.

Elevation bands are typically:

  • 0-0.5m
  • 5-2m
  • 2-5m
  • 5m-10m
  • >10m.

Why use GeoNet Drainage?

  • GeoNet Drainage supports the assessment of hydrological functions and features.
  • This product is useful for the review of forested wetlands and their drainage functions, and can be used to guide the development of artificial drainage trenches.
Triangular irregular model (TIN)

What is a Triangular Irregular Model (TIN)?

Triangular Irregular (TIN) Models are composed of a series of adjoining 3D triangular faces that are generated from actual LiDAR strikes. It is essentially a Digital Terrain Model (DTM) modelled as a surface. Imagery can be also draped over TIN Models to offer 3D viewing.

Why use a Triangular Irregular Model (TIN)?

  • Triangular Irregular (TIN) Models are commonly used for engineering design, hydrological modelling, volume, and other surface calculations.
  • They also allow for the generation of additional derived products such as Contours.
Contours

What are Contours?

Contours are generated from ground points (digital elevation model/bare-earth model) at fit-for-purpose intervals. Contours are generally presented in CAD/GIS format.

Why use Contours?

  • Contours are often used for CAD/paper plans (labelled if required) but can be converted to Triangular Irregular Network (TIN) format for 3D-modelling purposes.
  • The smaller file size of Contours allows for the display of features over large areas.
Digital Terrain Aspect Model

What is a Digital Terrain Aspect Model?

Digital Terrain Aspect Models allow for aspect (the direction that a slope faces) to be derived from the slope percentages of a gridded surface. These models are typically provided as a 1 metre grid spacing in raster format, which allows for import into CAD/GIS software.

Why use a Digital Terrain Aspect Model?

  • Digital Terrain Aspect Models are used regularly for urban planning and infrastructure planning.
  • They can assist with the preparation of plans for planning schemes, the calculation of metrics for subdivisions, the identification of optimal corridor routing for infrastructure, and the generation of less tangible products such as visual amenity.
3D Feature Capture

What is 3D Feature Capture?

3D Feature Capture is generated from both LiDAR and imagery data. It incorporates three-dimensional representations of discrete features through strings, points, and polygons delivered as detailed 3D CAD models/GIS data.

Why use 3D Feature Capture?

  • 3D Feature Capture is used for the identification/modelling of features such as high voltage powerlines, kerbs, road centrelines, and building rooftops details.
  • 3D Feature Capture allows for rapid capture of features over large areas.
2D Feature Capture

What is 2D Feature Capture?

2D Feature Capture is generated from both LiDAR and imagery data. It incorporates two-dimensional representations of discrete features through strings, points, and polygons.

Why use 2D Feature Capture?

  • 2D Feature Capture is used for the mapping of features where height is not a requirement (kerb, road/rail centrelines, the edges of vegetation, water, buildings etc)
  • 2D feature capture can be processed and delivered more rapidly than more detailed 3D Feature Capture.
RGB Ortho-Photography

What is RGB Ortho-Photography?

Ortho-photography is geo-referenced aerial photography captured simultaneously with LiDAR. The images are processed to eliminate distortions caused by the terrain and combined (mosaicked) to create an accurate, seamless image. They can be delivered as either a series of 1km2 tiles, or as a full mosaic image.

Why use RGB Ortho-Photography?

  • RGB ortho-photography is a great solution for applications requiring more detailed feature identification such as vegetation analysis, and is typically used for GIS/CAD modelling, and the generation of paper plans.
Intensity Imagery

What is Intensity Imagery?

Ground features with higher reflectivity will return more of the LiDAR beam, and Intensity Imagery is used to measure and visualise the strength of LiDAR returns as either an 8-bit value, or a percentage. This intensity value is gridded like a DEM (bare earth) model.

Why use Intensity Imagery?

  • Intensity Imagery assists with the identification of features where no ortho-photo is available and can be used to automatically identify features with specific reflectivity profiles.
  • Intensity Imagery is commonly used for asset mapping features like road markings, the edges of pavement and concrete etc.
Digital Surface Model

What is a Digital Surface Model?

Digital Surface Models are an evenly spaced grid of values that represent combined ground and non-ground models, showing the ground only when there are no other overhead features. These models are typically provided as a 1m grid spacing in raster format suitable for import into CAD/GIS software.

Why use a Digital Surface Model?

  • Digital Surface Models are useful in determining line of sight/visual amenity mapping, completing powerline clearances/encroachment assessments, or determining exclusion zones around structures or vegetation.
First Return Classification

What is First Return Classification?

First Return Classification is a process of classifying LiDAR points based on the first return of a laser pulse to the scanner. First returns indicate what type of feature the laser is striking first. They are typically provided in LAS or ASCII XYZ format.

Why use First Return Classification?

  • First Return Classification allows for the pragmatic analysis of feature types, and the generation of ‘true’ ortho-photo.
  • First returns are often used for ground cover analysis and determining vegetation encroachment.
Last Return Classification

What is Last Return Classification?

Last Return Classification is a process of classifying LiDAR points based on the last return from each laser pulse to the scanner. Last returns indicate what type of feature the laser is striking last. They are typically provided in LAS or ASCII XYZ format.

Why use Last Return Classification?

  • Last Return Classification is a good solution for understanding features at ground level while ignoring vegetation coverage.
  • It can also be used for select areas of very dense vegetation, where few strikes make it to the ground surface.
Percentage LiDAR Returns

What are Percentage LiDAR Returns?

Percentage LiDAR Returns divide elevations above ground into bands and calculate the percentage of LiDAR returns that appear in each band.

Elevation bands are typically:

  • 0-0.5m
  • 5-2m
  • 2-5m
  • 5m-10m
  • >10m.

Why use Percentage LiDAR Returns?

  • Percentage LiDAR Returns provide detailed information not easily acquired by any other means.
  • They are often used in the forestry sector for vegetation health analysis, species identification, vegetation profiling, understory growth, and forestry yield calculations.

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