EX1-4 - LIDAR Flashcards
LIDAR basics and overview
Light Detection and Ranging
A form of active remote sensing
These “profiling” lasers were placed beneath aircraft andpointed downward to acquire topographic information.
• Light returns (reflected energy from laser pulses) were
collected from locations directly beneath the aircraft.
• topography, vegetation structure, hydrography, and atmospheric properties
• Uses pulses of laser light (upto 300,000 pulses per second)
How does LIDAR calculate elevations based on return times of pulses (remember relationship between speed, distance and time)
s = d/t
A beam of light is generated by one or more laser, bounced off a surface and the return reflection is detected and recorded
Measures the round-trip for a pulse to travel between the sensor and the target
Since all EMR travel at the speed of light, the only variable affecting the rate of return is the distance between the sensor and the target
Farther the object, longer the return time for the pulse
Consequently, LIDAR can very precisely measure elevations
on land and under water
LIDAR Types
(Discrete single return, discrete multiple return and waveform return)
LIDAR and surface complexity
the more complex the surface the larger the data set
In urban areas, the first pulse return (or1st return) of LIDAR data measures the elevations of the canopy, building roof elevations, and other unobstructed surfaces. Depending on the surface complexity (variable vegetation heights, terrain changes, etc.), the data sets can beremarkably large:
200,000 points per square mile suburban, 350,000 points per square mile forestland.
LIDAR DSM and BEDEM
DSM (Digital Surface Model) or SEM (Surface Elevation Model):
BEDEM (Bare Earth Digital Elevation Model):
LIDAR applications
To obtain building heights
Advanced visualization of urban surfaces
Calculate urban ground heights for flood risk evaluation
Urban planning
Obstruction evaluation (aircraft, telecommunications)
Applications - LIDAR for urban mapping
Lidar is a more efficient tool for large-scale mapping than
conventional photogrammetry thanks to rapid data collection
and high point density.
Conventional manual stereo techniques collect approximately 1,500 data points per hour; lidar can collect 360,000,000 per
hour.
Lidar contour generation should be in 0.3-meter accuracy for
most municipal geospatial applications
Recent advancements producing more powerful laser pulses
have allowed for sub-decimeter accurate lidar data collection
from altitudes of several thousand meters
Applications - LIDAR and Vegetation
Studies
Provide data on the vertical distribution of intercepted surfaces →
Aboveground biomass estimates → Carbon studies
Spatial pattern of canopy height and cover
Derived metrics: stem diameter, basal area
Metrics from lidar sensitive to different land-use histories
Discrete return LIDARs:
• Single Return System: It records a single height in a sweep across alandscape. It looks for and records peaks in the landscape. The height would correspond with building tops, trees, hedges, cars and
ground across the landscape
• Multiple Return System: It records a discrete series of heights, called first return, second return, third return etc. It typically records up to 5 returns from a single pulse. The advantage is that both ground height and top height (i.e. tree canopy, bare ground and in-between
understory) can be discerned.
Waveform LIDARs:
.
• These capture a continuous return, potentially modeling every objectat every elevation at the same time, which has to be separated into various elevation layers through additional processing. This allows
characterization of tree canopy structure, separate from the ground signal
DSM or SEM
This data represents the highest point measured. It is the first “z” of “xyz”.
It represents the first surface intercepted by the lidar pulse.
BEDEM
This represents the lowest data point measured.
It is the last “z” of “xyz”.
It represents the terrain surface after removal of vegetation and structures.
This model is generated through a complex filtering process where manmade structures and trees are identified and removed from the dataset.
DSM and DEM difference
A DSM is different from a DEM in that it represents the top of the landscape, be it bare earth, rooftop or treetop. A DEM is height of land surface above msl and does not include building or tree heights