Lec 14 - LiDAR Flashcards by KEANNA MARIE DUEÑAS

It is a remote sensing method used to examine the surface of the Earth. It uses light in the form of a pulsed laser to measure ranges (variable distances) to the Earth.

Light Detection and Ranging (LiDAR)

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LiDAR Components

(1) a laser
(2) a scanner
(3) a specialized GPS receiver

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These are the most commonly used platforms for acquiring LiDAR data over broad areas.

Airplanes and helicopters

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Types of LiDAR (2)

(1) Topographic LiDAR
(2) Bathymetric LiDAR

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This type of LiDAR typically uses a near- infrared laser to map the land

Topographic LiDAR

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This type of LiDAR uses water-penetrating green light to also measure seafloor and riverbed elevations.

Bathymetric LiDAR

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It measures distances (through laser pulses) that strike and reflect from the earth’s surface features.

LiDAR system

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LiDAR system distance formula

Distance = (speed of light * round-trip time) * 1⁄2

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LiDAR technologies

(1) Positioning
(2) Inertial technology
(3) Laser scanning
(4) Digital imagery

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It converts scanning angle and distance-from-sensor information into geo-referenced data points:

LiDAR system

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Airborne LiDAR System Components

(1) a laser scanner unit
(2) a GPS
(3) an IMU

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It is composed of a laser range finder unit, which is based on time-of- flight distance measurement techniques, and a beam deflection device that creates the desired scanning pattern.

Laser scanner

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It provides the absolute position of the sensor platform (plat),

GPS

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It records the angular attitude of the platform (including roll, pitch, and yaw/heading).

IMU

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These enable the system to generate the aircraft’s absolute position (X, Y, Z) at any given time.

Airborne LiDAR System Components

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Advantages of LiDAR

(1) High Accuracy of elevation model collection for 0.3m - 0.6m contours
(2) Can be used any time of the day
(3) Shadows in mountains that are usually problematic is not an issue on LiDAR
(4) Cloud shadows is not an issue
(5) Cost effective in large projects

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Advantages of LiDAR over conventional survey and photogrammetry

(1) LiDAR performs better than photogrammetry in vegetative areas
(2) Fast data collection
(3) Fast data processing
(4) Less weather dependent
(5) Robust data sets which have variety of data sets
(6) Cost-saving

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Disadvantages of LiDAR

(1) Indiscriminate - shows elevation points of everything
(2) Only places mass points - doesn’t pick up breaklines, or lines of change of ground elevation
(3) Not imagery - can be shaded to offer a relief image
(4) Incapable of penetrating thick vegetation
(5) Not applicable in all weather

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Features LiDAR cannot identify

(1) Boundary information
(2) Underground utilities
(3) Water or depth of water

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It is a laser beam emitted from the LiDAR sensor.

Pulse

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These are used in order to map out vegetation.

Near Infrared (NIR) and green light

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These are the portions of the pulse that is reflected by the objects on the ground back to the sensors.

Returns

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It is a set of points gathered through a 3D laser scanner that is plotted in order to form a 3D object.

Point Cloud

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LiDAR Data Characteristics

(1) Data resolution (full point cloud)
(2) LiDAR intensity
(3) Precision and accuracy
(4) Consistency

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It is Pulses per unit area (pulses/m^2).

Pulse Density

It is the relative measure of the reflectivity of the target.

Intensity

It consists of precisely referenced points in time and space.

Discrete-return LiDAR data

These can be extracted from a point cloud.

(1) ground roads and other surface features (2) vegetation (3) structures

This may vary between scanners or missions and between returns in the same pulse.

Consistency

It may vary its sensitivity (gain) during the flight to compensate for variability in return signal strength.

Sensor

Information provided by LiDAR

(1) High resolution (1 meter) "Bare Earth Surface" or DEM (2) Roads, structures, and other surface features (3) Vegetation (canopy closure, tree and stand heights, canopy structure, etc.

It contains only of the set of the returns from the ground (vegetation, structures, etc. filtered out).

Bare Earth Point Clouds

When assessing a bare earth filtered point cloud, this indicates how well we sampled the “ground”.

Point Spacing

When assessing a raw LIDAR point cloud, this indicates how well we sampled “all targets”.

Pulse Density

It looks impressive, but is of little use to most clients.

LiDAR “point cloud”

These will dictate which type of LiDAR system should be used for data collection.

Accuracy, detail and deliverable requirements

Through these processes, raw LiDAR data can be reduced to be manageable, while maintaining accuracy and detail.

Filtering, digitizing, and vectorizing,

By using this, we can normalize the topography or remove it from the data. This allows us to measure and make comparisons of vegetation structure.

ground surface

LiDAR Pulse Density Products

(1) Low pulse density (2) Moderate pulse density (3) High pulse density

Low Pulse Density Products

(1) Moderate Resolution Topographic Products (≥ 2 meter Grid) (2) Moderate Resolution (3m) LiDAR DEM can provide improved stream location accuracy, improved flood mapping, and landslide detection and hazard assessment.

Moderate Pulse Density Products

(1) Stand Level Vegetation Metrics (e.g. canopy height, canopy cover) (2) High Resolution Topographic Products

High Pulse Density Products

(1) Forest Structure (Modeling and Field Data Collection required) (2) Includes all capabilities of Low and Moderate Pulse density data (3) Possible to model Forest Inventory parameters: Dominant height, basal area, stem volume, biomass, canopy (4) Expensive LiDAR data, Accurate field data, complex analysis

Though it is preferable to have high pulse density, there are times that this LiDAR data may have the capacity to estimate the typical structure of a forest with an adequate accuracy.

Low Density LiDAR data

LIDAR Errors

(1) laser induced - changes in height for points on terrain (ridges and ditches) and grain noise (smooth surfaces appear rough) (2) GPS/INS - induced variances in measurements taken by the instruments. (3) Filtering induced - incomplete/unnecessary removal of features (vegetation, buildings, rock outcroppings)

LiDAR Error Sources

(1) Error due to sensor position due to error in GPS, INS and GPS- INS integration. (2) Error due to angles of laser travel as the laser instrument is not perfectly aligned with the aircrafts roll, pitch and yaw axis. (3) The vector from GPS antenna to instrument in INS reference system is required in the geolocation process. (4) There may be error in the laser range measured due to time measurement error, wrong atmospheric correction and ambiguities in target surface which results in range walk. (5) Error is also introduced in LiDAR data due to complexity in object space, e.g., sloping surfaces leads to more uncertainty in X, Y and Z coordinates.

It refers to the closeness of a measured or computed value to a standard or accepted (true) value of a particular quantity.

Accuracy

It is commonly estimated by calculating the Root Mean Square Error (RMSE).

LiDAR Accuracy

Types of Accuracy Specifications

(1) Absolute LiDAR Accuracy (2) Relative LiDAR Accuracy

It refers to both the horizontal and vertical accuracy of LiDAR data.

Absolute LiDAR accuracy

It is assessed by comparing the LiDAR data with ground surveyed checkpoints.

Absolute LiDAR accuracy

It refers to the internal quality of LiDAR elevation data without using surveyed ground control points.

Relative LiDAR accuracy

It is a measure of local differences between points in the point cloud.

Relative LiDAR accuracy

Relative LiDAR accuracy is affected by this.

LiDAR system calibration

Assessment of Relative Accuracy

(1) Within-swath accuracy assessment (2) Swath-to-swath accuracy assessment

Assessment of data collected within the same swath or flight line. It indicates how stable the LiDAR system is.

Within-swath accuracy assessment

Assessment of data collected between swaths/ adjacent flight lines. It involves comparing overlapping sections in adjacent swaths.

Swath-to-swath accuracy assessment

LiDAR systems are often fitted with these sensors that can provide useful information to accompany the LiDAR data.

Additional Complementary Sensors

This creates an image that is uniform from edge to edge.

Orthophotography

These produce real-time images and temperature data

Infra-red cameras

These collect and process information from across the electromagnetic spectrum.

Hyperspectral sensors

LiDAR Applications

(1) LIDAR has significant fixed cost but can be very cost effective for large projects (2) Appropriate for a wide range of projects including forestry, corridor studies, obstruction mapping, flood studies, city/county mapping, and transportation projects (3) Required accuracy must be carefully evaluated

LiDAR Applications

(1) Autonomous Vehicles (2) Aerial Inspection (3) Precision Agriculture (4) Forestry and Land Management (5) Survey and mapping (6) Renewable Energy (7) Robotics (8) Urban Modelling (9) Transmission Line (10) Railways, Highways, Levees and Pipelines