Delhez, E. J. M., and Wolk, F., 2013. Diagnosis of the transport of
adsorbed material in the Scheldt estuary: a proof of concept.
Journal of Marine Systems, 128, 17–26.
Delhez, E. J. M., Campin, J.-M., Hirst, A. C., and Deleersnijder, E.,
1999. Toward a general theory of the age in ocean modelling.
Ocean Modelling, 1, 17–27.
Delhez, E. J. M., Deleersnijder, E., Mouchet, A., and Beckers, J.-M.,
2003. A note on the age of radioactive tracers. Journal of Marine
Systems, 38, 277–286.
DeVries, T., and Primeau, F., 2010. An improved method for
estimating water-mass ventilation age from radiocarbon data.
Earth and Planetary Science Letters, 295, 367–378.
Haine, T. W. N., and Hall, T. M., 2002. A generalized transport
theory: water-mass composition and age. Journal of Physical
Oceanography, 32, 1932–1946.
Kratzer, C. R., and Biagtan, R. N., 1997. Determination of Travel
Times in the Lower San Joaquin River Basin, California, from
Dye-Tracer Studies During 1994–1995. U.S. Geological Survey
Water-Resources Investigations Report 97–4081.
Lucas, L. V., Thompson, J. K., and Brown, L. R., 2009. Why are
diverse relationships observed between phytoplankton biomass
and transport time? Limnology and Oceanography, 54(1), 381–390.
Monsen, N. E., Cloern, J. E., Lucas, L. V., and Monismith, S. G.,
2002. A comment on the use of flushing time, residence time,
and age as transport time scales. Limnology and Oceanography,
47(5), 1545–1553.
Mouchet, A., and Deleersnijder, E., 2008. The leaky funnel model,
a metaphor of the ventilation of the World Ocean as simulated in
an OGCM. Tellus, 60A, 761–774.
Sheldon, J. E., and Alber, M., 2002. A comparison of residence time
calculations using simple compartment models of the Altamaha
River Estuary, Georgia. Estuaries, 25(6B), 1304–1317.
Shen, J., and Haas, L., 2004. Calculating age and residence time in
the tidal York River using three-dimensional model experiments.
Estuarine, Coastal and Shelf Science, 61, 449–461.
Takeoka, H., 1984. Fundamental concepts of exchange and
transport time scales in a coastal sea. Continental Shelf Research,
3(3), 311–326.
Xu, B.-C., Dimova, N. T., Zhao, L., Jiang, X.-Y., and Yu, Z.-G., 2013.
Determination of water ages and flushing rates using short-lived
radium isotopes in large estuarine system, the Yangtze River Estuary, China. Estuarine, Coastal and Shelf Science, 121–122, 61–68.
Zimmerman, J. T. F., 1976. Mixing and flushing of tidal
embayments in the western Dutch Wadden Sea part I:
distribution of salinity and calculation of mixing time scales.
Netherlands Journal of Sea Research, 10(2), 149–191.
Cross-references
Residence Time
Timescale
AIRBORNE LASER TERRAIN MAPPING (ALTM)
Michael J. Starek
Harte Research Institute for Gulf of Mexico Studies,
Texas A&M University, Corpus Christi, TX, USA
Synonyms
Airborne laser scanning; Airborne laser swath mapping;
Airborne light detection and ranging; Laser altimetry;
Laser radar
Definition
Airborne laser terrain mapping (ALTM) is an active
remote sensing technology that employs light detection
and ranging (see Light Detection and Ranging (LIDAR))
to measure topography at high spatial resolution over large
areas. ALTM pulses a laser to measure the range between
an airborne platform and the Earth’s surface at many thousands of times per second. Using a rotating mirror or other
scanning mechanism inside the laser transmitter, the laser
pulses can be made to sweep through an angle, tracing out
a line or other patterns on the reflecting surface. With the
scan line oriented perpendicular to the direction of flight,
it produces a sawtooth pattern of ranges within a strip
centered directly along the flight path (Figure 1). An integrated global positioning system (GPS) and inertial
navigation unit are used to accurately determine the aircraft position and attitude as each laser pulse leaves
the aircraft. This information is then combined with
the scan angle and range for each pulse to derive the
georeferenced location of the sample points on the
reflecting surface (Baltsavias, 1999; Wehr and Lohr,
1999). The result is a densely sampled three-dimensional
(3D) point cloud of x,y,z values representing the ground
and land cover. In addition to spatial information,
ALTM systems typically provide a relative measure of
the reflection intensity for each surface point based on
the return pulse amplitude.
History
ALTM is commonly referred to as airborne lidar mapping.
The first airborne lidar systems were developed in the late
1960s as a way to measure height profiles of ice packs
and underwater surfaces (bathymetry) where traditional
sonar techniques failed due to shallow water depths. The
development of profiling bathymetric lidar systems continued through the 1970s. The first system to incorporate
a scanning mechanism was the NASA Airborne Oceanographic Lidar (AOL) that became operational in 1977
(Fernandez-Diaz et al., 2013). Terrestrial experiments
were conducted starting in 1980 to evaluate the capability
of the AOL system to derive topographic maps in areas not
suited for photogrammetric methods, such as forested
regions. Early results encouraged researchers to develop
lidar systems with specific design characteristics targeted
for terrestrial applications. However, it was not until the
mid-1990s that commercially manufactured units became
fully operational (Shan and Toth, 2009). Starting in the
1990s, rapid advancements in enabling technologies such
as GPS, IMUs, solid-state lasers, photodetectors, and optical scanners paved the way for the modern-day ALTM
system.
System components
ALTM systems consist of three main components. First,
the laser ranging unit consists of the laser transmitter,
scanner (e.g., oscillating mirror), and a receiver to record
the reflected energy. Second, the position and orientation
4
AIRBORNE LASER TERRAIN MAPPING (ALTM)
adsorbed material in the Scheldt estuary: a proof of concept.
Journal of Marine Systems, 128, 17–26.
Delhez, E. J. M., Campin, J.-M., Hirst, A. C., and Deleersnijder, E.,
1999. Toward a general theory of the age in ocean modelling.
Ocean Modelling, 1, 17–27.
Delhez, E. J. M., Deleersnijder, E., Mouchet, A., and Beckers, J.-M.,
2003. A note on the age of radioactive tracers. Journal of Marine
Systems, 38, 277–286.
DeVries, T., and Primeau, F., 2010. An improved method for
estimating water-mass ventilation age from radiocarbon data.
Earth and Planetary Science Letters, 295, 367–378.
Haine, T. W. N., and Hall, T. M., 2002. A generalized transport
theory: water-mass composition and age. Journal of Physical
Oceanography, 32, 1932–1946.
Kratzer, C. R., and Biagtan, R. N., 1997. Determination of Travel
Times in the Lower San Joaquin River Basin, California, from
Dye-Tracer Studies During 1994–1995. U.S. Geological Survey
Water-Resources Investigations Report 97–4081.
Lucas, L. V., Thompson, J. K., and Brown, L. R., 2009. Why are
diverse relationships observed between phytoplankton biomass
and transport time? Limnology and Oceanography, 54(1), 381–390.
Monsen, N. E., Cloern, J. E., Lucas, L. V., and Monismith, S. G.,
2002. A comment on the use of flushing time, residence time,
and age as transport time scales. Limnology and Oceanography,
47(5), 1545–1553.
Mouchet, A., and Deleersnijder, E., 2008. The leaky funnel model,
a metaphor of the ventilation of the World Ocean as simulated in
an OGCM. Tellus, 60A, 761–774.
Sheldon, J. E., and Alber, M., 2002. A comparison of residence time
calculations using simple compartment models of the Altamaha
River Estuary, Georgia. Estuaries, 25(6B), 1304–1317.
Shen, J., and Haas, L., 2004. Calculating age and residence time in
the tidal York River using three-dimensional model experiments.
Estuarine, Coastal and Shelf Science, 61, 449–461.
Takeoka, H., 1984. Fundamental concepts of exchange and
transport time scales in a coastal sea. Continental Shelf Research,
3(3), 311–326.
Xu, B.-C., Dimova, N. T., Zhao, L., Jiang, X.-Y., and Yu, Z.-G., 2013.
Determination of water ages and flushing rates using short-lived
radium isotopes in large estuarine system, the Yangtze River Estuary, China. Estuarine, Coastal and Shelf Science, 121–122, 61–68.
Zimmerman, J. T. F., 1976. Mixing and flushing of tidal
embayments in the western Dutch Wadden Sea part I:
distribution of salinity and calculation of mixing time scales.
Netherlands Journal of Sea Research, 10(2), 149–191.
Cross-references
Residence Time
Timescale
AIRBORNE LASER TERRAIN MAPPING (ALTM)
Michael J. Starek
Harte Research Institute for Gulf of Mexico Studies,
Texas A&M University, Corpus Christi, TX, USA
Synonyms
Airborne laser scanning; Airborne laser swath mapping;
Airborne light detection and ranging; Laser altimetry;
Laser radar
Definition
Airborne laser terrain mapping (ALTM) is an active
remote sensing technology that employs light detection
and ranging (see Light Detection and Ranging (LIDAR))
to measure topography at high spatial resolution over large
areas. ALTM pulses a laser to measure the range between
an airborne platform and the Earth’s surface at many thousands of times per second. Using a rotating mirror or other
scanning mechanism inside the laser transmitter, the laser
pulses can be made to sweep through an angle, tracing out
a line or other patterns on the reflecting surface. With the
scan line oriented perpendicular to the direction of flight,
it produces a sawtooth pattern of ranges within a strip
centered directly along the flight path (Figure 1). An integrated global positioning system (GPS) and inertial
navigation unit are used to accurately determine the aircraft position and attitude as each laser pulse leaves
the aircraft. This information is then combined with
the scan angle and range for each pulse to derive the
georeferenced location of the sample points on the
reflecting surface (Baltsavias, 1999; Wehr and Lohr,
1999). The result is a densely sampled three-dimensional
(3D) point cloud of x,y,z values representing the ground
and land cover. In addition to spatial information,
ALTM systems typically provide a relative measure of
the reflection intensity for each surface point based on
the return pulse amplitude.
History
ALTM is commonly referred to as airborne lidar mapping.
The first airborne lidar systems were developed in the late
1960s as a way to measure height profiles of ice packs
and underwater surfaces (bathymetry) where traditional
sonar techniques failed due to shallow water depths. The
development of profiling bathymetric lidar systems continued through the 1970s. The first system to incorporate
a scanning mechanism was the NASA Airborne Oceanographic Lidar (AOL) that became operational in 1977
(Fernandez-Diaz et al., 2013). Terrestrial experiments
were conducted starting in 1980 to evaluate the capability
of the AOL system to derive topographic maps in areas not
suited for photogrammetric methods, such as forested
regions. Early results encouraged researchers to develop
lidar systems with specific design characteristics targeted
for terrestrial applications. However, it was not until the
mid-1990s that commercially manufactured units became
fully operational (Shan and Toth, 2009). Starting in the
1990s, rapid advancements in enabling technologies such
as GPS, IMUs, solid-state lasers, photodetectors, and optical scanners paved the way for the modern-day ALTM
system.
System components
ALTM systems consist of three main components. First,
the laser ranging unit consists of the laser transmitter,
scanner (e.g., oscillating mirror), and a receiver to record
the reflected energy. Second, the position and orientation
4
AIRBORNE LASER TERRAIN MAPPING (ALTM)