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PPRS > LiDAR > Flashcards

LiDAR Flashcards

1
Q

What is ECV?

A

Essential Climate Variables, such as above ground biomass

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2
Q

What do ECV datasets support?

A

the UNFCC and the IPCC

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3
Q

What is a pro of LiDAR data?

A

3D

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4
Q

What is LiDAR data most used for in the UK?

A

flood modelling

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5
Q

What is 2.5D?

A

A 2D raster with each pixel containing 1 elevation value

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6
Q

What is a benefit of 2.5D?

A

It can be represented on paper without losing information

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7
Q

What does 3D account for the 2.5D doesn’t?

A

things that overlap each other

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8
Q

what are the three 3D data types?

A

point clouds, voxel space and geometric primitives

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9
Q

Give an example of an attribute a data point can have

A

properties of the object such as its colour or properties of the measurement such as laser return intensity

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10
Q

what is voxel space?

A

a volumetric pixel (3d grid wit attributes per grid cell

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11
Q

what do you need to consider when using voxel space?

A

you need to be careful about blank space

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12
Q

What are geometric primitives

A

a triangular mesh 3D dot to dot

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13
Q

what do geometric primitives let you do?

A

allows a shape to be built up, eg. spheres and cyclinders

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14
Q

What is a limitation of using geometric primitives?

A

Complex shapes can use a lot of memory

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15
Q

what is a useful 3D application in weather

A

predicting storm surges

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16
Q

What are the different DEMs?

A

Digital Terrain Model (DTM), Digital Surface Model (DSM) and Canopy Height Model (CHM)

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17
Q

What is the difference between a DTM and a DSM

A

DTM is bare ground elevation and DSM is the highest point elevation (tree tops and building roofs

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18
Q

Here is a list of applications

A

monitoring infrastructure, creating 3D models of fragile historic artefacts, ancient city footprints (Mexico jungle discovery)

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19
Q

What global forestry maps can be produced?

A

height, biomass, leaf area, structure

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20
Q

What is forestry data used for?

A

driving weather and vegetation models,

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21
Q

What is knowing forest structure useful for?

A

studying biodiversity

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22
Q

what can you achieve when surveying

A

you can collect data using GPS and total station. It’s accurate and allows context to be recorded. it can be used in forest when GPS doesn’t work

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23
Q

What is a limitation of surveying?

A

slow

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24
Q

photogrammetry

A

using views from multiple photographs

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25
Q

advantages of photogrammetry

A

Can be made using low cost cameras and rapidly collects large areas

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26
Q

Disadvantages of photogrammetry

A

requires recognisable features and you only see the top layer

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27
Q

which needs less signal processing. LiDAR or RADAR?

A

LiDAR, no need for unwrapping

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28
Q

Disadvantages of LiDAR

A

high energy requirements, limited coverage and cannot see through clouds

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29
Q

How does lidar work?

A

laser is used to emit a short pulse of light. we know the speed of light. travel time is used to measure range. GPS and interval navigation get instrument position. Attitude sensors and laser pointing are used to get direction of the laser beam

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30
Q

give the equation to get the distance from lidar instrument to the target

A

Distance = ( speed of light * time ) / 2

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31
Q

What are the 4 lidar platforms

A

Terrestrial Laser Scanning (TLS), Unmanned Aerial Vehicle (UAV), Airborne Laser Scanning (ALS), Spaceborne LIDAR

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32
Q

What is the accuracy resolution and coverage of TLS

A

~5 mm accuracy, ~1 cm resolution, ~100 m coverage

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33
Q

What is the accuracy resolution and coverage of UAV lidar

A

~5 cm accuracy, ~1-10 cm resolution, 1-10 km coverage

34
Q

What is the accuracy resolution and coverage of ALS

A

~5-20 cm accuracy, ~10cm-1m resolution, 10-100’s km coverage

35
Q

What is the accuracy resolution and coverage of Spaceborne lidar

A

~1 m accuracy, ~500 m resolution, global coverage

36
Q

What is the most widely available lidar platform?

37
Q

What is TLS good for?

A

small studies

38
Q

What are the different ways of measuring the returning signal?

A
  • Full-waveform – record returned light as a function of time (energy reflects back as the laser hits things)
  • discrete return - Record timing of significant returns
  • photon counting - use very sensitive detectors to time single photons
  • phase based - use modulated output and record phase difference
39
Q

which is conceptually the simplest measuring technique?

A

Full waveform ALS

40
Q

more info on full waveform ALS and why is less common

A

all visible objects are recorded, large data volume and fast disk write speeds, more expensive instruments, produces volumetric data, displayed as voxels of processed to a derived product, software to handle is not quite mainstream

41
Q

how does does discrete return do?

A

Uses signal processing to estimate the range of scattering objects.
* 1-20 ranges recorded per shot
* Point cloud produced
* Greatly reduced data needs
* All lidar software can handle
* May not record all visible surfaces, do
not know what is not recorded.
* Different instruments and survey configurations can give different results.
* Algorithms are proprietary
* Analysis can be difficult in complex
environments

42
Q

full waveform vs discrete return pro and con

A

full waveform offers far more information than DRL, it reveals more structure>
However, at greater cost
This is why discrete is more common

43
Q

Photon counting, details

A
  • “Geiger mode” detector
  • One photon per detector element
  • Allows lower powered lasers (increased
    coverage)
  • Will detect sunlight (noisy)
  • Instruments currently very expensive
  • sensor clicks when the conductance of the air changes
  • Used by ICESat
44
Q

Data formats for LiDAR data

A

.pts – text file

.las –binary format, a bit compressed and can be opened in arc 4 bytes per coordinate

.laz – compressed .las

Full-waveform – no dominant format yet.

45
Q

.laz more info

A

cannot be opened in arc. Factor of ~2 saving. can be opened in cloudcompare

46
Q

.las more info

A

, a bit compressed and can be opened in arc 4 bytes per coordinate

47
Q

.pts more info

A
  • 1 byte per significant figure (~10 bytes per coord)
48
Q

how to deal with large data

A

process tile by tile, few Gbytes at a time, then can spread tile processing across multiple cores for “embarassingly parallel” processing

49
Q

what software is used to visualise lidar data?

A

CloudCompare, ArcScene and Python 3D plots

50
Q

What do you use to analyse lidar data?

A

Lastools, pylidar, ArcGIS, independent conding libraries (rLidar, lidaR, libClidar, libLas), proprietary software from manufacturer (Leica Cyclone, Riegl RiAnalyse & RiScan, QTM etc…)

51
Q

1st step in processing LiDAR is…

A

finding where the ground is and classifying those points

52
Q

what are the three classifications when identifying the ground points

A

ground, not ground and noise

53
Q

What can you do to help identify which points are ground?

A

using mathematical algorithms to split up the data into a raster and connects potential ground points within threshold you choose - the algorithm does this until it cannot add any mire points

54
Q

Criteria for ground points

A
  • Ground will be at the bottom
  • Within a given small area, ground points are likely to be at the same elevation
  • The ground is unlikely to have sudden spikes or deep holes
  • Changes in elevation are likely to be smooth
55
Q

LASTools lasground_new.exe function used in the practical

56
Q

Three most important variables

A

step, spike and offset

57
Q

step

A

How large an area are statistics calculated over. setting the size of the raster, AKA ‘patch’

  • If short, it will find sharply varying surfaces, but will pick up building roofs as ground.
58
Q

-spike/-spike_down:

A

How large an instantaneous change can still be classed as ground

Smaller than a wall but larger than the depth of the plough in the case of the field

59
Q

Offset

A

How much variation do we expect from the line of best fit?

  • If data has any ground roughness (eg ruts in ploughed fields) or is noisy, this number should be increased to contain the variation in ground elevation.

Offset must always be bigger than the noise

60
Q

how big is the uncertainty in object location given the range uncertainty?

61
Q

what issues to building cause

A
  • Large areas with no ground returns
  • If patch size (step) is less than building size, lowest point will be on the roof.
  • Need to adjust patch size accordingly.
  • Can use sudden change from ground to
    wall identify building.
62
Q

What is the rule of thumb when covering an area with large buildings?

A

Rule of thumb is the step needs to be at least half the size of the largest building in your area

63
Q

Issues with vegetation

A

Trees can block view of ground – requires
longer patch size than bare-Earth.
* Forests can have complex topography (too steep to farm) – requires shorter patch size.
* Where does the ground end and the plants begin?
Point density is important to determine where the ground is

64
Q

issues with complex topography

A

Rapidly changing steep terrain
* Real ground can have sharp changes
* Requires a shorter patch size

example - quarries

increase spike to pick up these real changes

65
Q

Issues with ALS density

A

Point density is key
* The more points, the greater the chance of all objects being correctly measured.
* Do we see the real ground?
4 point/ m^2 needed to see the ground well

66
Q

What can be used to estimate population in countries without census

A

Building volume

67
Q

Datums

A

Our elevation is measured relative to a “vertical datum”.
This is most commonly one of:
* An ellipsoid (assumes a regular shape for the Earth)
* Mean sea level through the local gravity field (“geoid”)

MAKE SURE YOU KNOW WHICH ONE YOU ARE USING, OTHERWISE ALLIGN THEM IF COMPARING

68
Q

Advances in ground finding algorithms

A

In the last 20 years they have become more sophisticated

69
Q

Classifying surfaces

A

Use texture metrics – standard deviation of points about the mean elevation.

Buildings will be smooth, have lower stdev.
Vegetation will be rough, have higher standard deviation.

70
Q

give an example of a spaceborne LiDAR looking at veg

A

Global Ecosystem Dynamics Investigation Lidar (GEDI)
First lidar mission designed for forest measurement.
* $94,000,000 mission

71
Q

give an example of a spaceborne LiDAR looking at ice

A

ICESat - 2
Optimised for ice measurement
* Photon-counting, greater coverage but noisier data than GEDI
* $1 billion mission

72
Q

give an example of a spaceborne LiDAR looking at clouds

A

CALIPSO
Optimised for cloud measurement
* Full-waveform
* Dual wavelength and dual polarisation
* 2006 - 2023
used for forecasting

73
Q

give an example of a spaceborne LiDAR looking at wind speed

A

Aeolus
* Uses high-energy UV laser pulses
* Data is used to improve weather forecasting

74
Q

summary, what 4 main things can lidar measure wind speed

A
  • 3D structure
  • Surface elevation
  • Height
  • Wind speed (with Doppler)
    measures doppler shift off the gas
    also used in forecasting
75
Q

What are level 2 products?

A

things that lidar directly measure

76
Q

What are level 4 products

A

Things you are modelling, inferred through statistical modelling - eg. biomass

77
Q

Much lidar is now freely available, where?

A
  • England & Wales environment agency
  • Lidar Scotland - https://remotesensingdata.gov.scot
  • Open Topography
78
Q

what country gets renewed coverage every 6 years?

79
Q

what is a limitation of the lidar industry evolving?

A

power intensity

80
Q

what is evolving

A

detector efficiency

81
Q

Which gas blocks more? CO2 or methane?

PPRS (8 decks)

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