Riparian zone showing shading by streamside trees. Note the
dense canopy and understory on the left side may make it
very difficult for small-footprint lidar to obtain reflections
from the ground.LVIS in detecting the ground over 99% of
the time in Sequoia National Forest in California and at least
90% of the time in the dense rainforests of La Selva
Biological Research Station, Costa Rica (Blair et al., 1999).
5 USES
The different capabilities of these lidar classes give rise to
different current and potential uses (Table 4). Small-footprint
lidars are used primarily for creation of DTMs. These can be
for road, rail or pipeline right-of-ways, open pit mines, and
other uses including more recently, surveys of cities that
include accurate building positions. Change detection is an
emerging capability of small-footprint lidars and development
of this capability in urban areas is occurring (Murakami et al.,
1999). Creation of DTMs under forests and other vegetation
is still a challenge. Most companies that offers lidar services
International Archives of Photogrammetry and Remote Sensing, Vol. 32, Part 3W14, La Jolla, CA, 9-11 Nov. 1999
have developed this capability, though details are closely
guarded. Additionally, approaches to creating DTMs have
been developed in Europe at universities (Axelsson, 1999;
Kraus & Pfeifer, 1998). Vegetation height and volume have
been measured with good success using small-footprint
(Jensen et al., 1987; Naesset, 1997a; Naesset, 1997b) and
large foot-print lidars (Lefsky et al., 1999; Means et al.,
1999). Forestry applications of small-footprint lidar have a
bright future that is currently being explored.
Future uses
Data fusion Integration of lidar data with image data offers
great potential for applications in feature recognition and
forestry because the two types of information are so
complementary. Lidar provides structural information, such
as height, cover density and vertical distribution, while
imagery provides information on composition such as roof
type, landcover type, species groups and proportions of
broadleaves conifers and shrubs, herbs or grass. Progress
made in integrating lidar with raster imagery to make 3-D
Table 4. Uses of Two Different Types of Lidar Systems.
Small-footprint, discrete return
Large-footprint, waveform return”
Current uses
— DTMs: right-of-ways for new & existing roads, high-
voltage electric power lines (pre-construction, line sag,
vegetation encroachment), pipelines, mines, landfills, etc.
— Urban/suburban surveys, quantitative 3-D descriptions
including vegetation, buildings
— Change detection of surveyed features
— Forest tree height, stand volume
— Integration with raster imagery and airphotos
— DTMs and topography: glaciers, volcanoes (hazards
assessment, erosion, accretion), extensive areas
— Change detection of surveyed features
— Forest stand height, canopy cover, biomass, basal area, leaf
area, including dense vegetation
Potential future uses and developments
— Forest biomass, canopy cover, wildland fuels
floor and channel morphology (above water)
— Wildlife habitat
— Agricultural field drainage, crop height development
— Standards for accuracy and performance
—Co-collection with co-registered imagery using digital
cameras, multi- & hyperspectral sensors
— More automated DTM creation and integration with
imagery
— Global coverage of topography, ice sheets, vegetation
height & roughness
— River/stream: riparian vegetation (height, shade), valley — Integration and coregistration with raster imagery
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