140
interpreting satellite images. Aerial photographs,
with their high spatial resolution, provide a link between the resource data on the ground and the high
spectral resolution of satellite imagery.
An interagency program called the National High
Altitude Photography (NHAP) program was established in 1980 to build a uniform archive of aerial
photos of the 48 conterminous states. Black-andwhite and color-infrared photos were acquired at an
approximate scale of 1 : 80,000 and 1 : 58,000, respectively. In 1987, the flight specifications were
modified, as was the name: NHAP became the National Aerial Photography Program (NAPP). Blackand-white and color-infrared NAPP photos are
1 : 40,000 scale centered on quarters of 7.5-minute
quadrangles. Many image processing software packages have modules that allow the user to analyze and
manipulate digital copies of aerial photographs.
Airborne videography and digital camera systems provide powerful tools for ecosystem management. A camera can be mounted in a small airplane and imagery can be viewed as soon as the
flight is complete (King, 1995). A wide range of
spatial resolution can be obtained by varying the
flying altitude and camera lenses. Digital camera
imagery linked with GPS provides location information for each frame, allowing users to quickly
locate specific areas on maps or images. Images
can be georeferenced and used with other GIS layers. These systems are used for a variety of resource
applications, including aerial surveys for forest
pests (Knapp et al., 1998) and monitoring and mapping riparian areas (Bobbe et aI., 1993; Bobbe and
McKean, 1995) and as a high-resolution data source
for satellite image classification (Slaymaker et aI.,
1996).
Digital orthophoto quadrangles (DOQs) combine the image characteristics of a photograph with
the geometric qualities of a map. Wirth et ai. (1994)
describe the creation of DOQs as a process of scanning aerial photographs with each pixel of the image being corrected for relief displacement and
camera orientation. DOQs are valuable data
sources for updating road and existing land cover
databases and for georeferencing other data for use
in a GIS. However, the large file size associated
with DOQs can make them cumbersome to use. A
7.5 minute quadrangle-based DOQ is approximately 160 Mbytes. Often multiple DOQs, requiring hundreds of megabytes or even gigabytes of
hard disk space, need to be mosaicked together to
cover a project area. The large file size should become less of an issue as larger hard drives, faster
processors, and improved image compression techniques become available.
Remote Sensing Applied to Ecosystem Management
Radar Data
Radar systems form a unique addition to our capabilities for collecting remotely sensed data. The systems can operate during day or night and can penetrate clouds, thereby providing high-quality imagery
of Earth's surface in situations where photographic
or multispectral systems cannot be used (Hoffer et
al., 1995). Radar imagery can be obtained from aircraft or satellite platforms. Kasischke et ai. (1997)
discuss the capabilities of radar systems for investigating terrestrial ecosystems. They organize applications into four broad areas: (1) classification and
detection of change in land cover, (2) estimation of
woody plant biomass, (3) monitoring the extent and
timing of inundation, and (4) monitoring other temporally dynamic processes. Specific examples are
provided for each application area. Imhoff et al.
(1997) used radar imagery to discern structural differences relevant to bird habitat quality in the Northwest Territory, Australia.
Lidar Data
Compared to radar, lidar (light detection and ranging) is relatively new. This technology involves
pulsing Earth's surface with lasers and collecting
the reflected electromagnetic energy. By precisely
timing the interval between the emission of the
pulse and the detection of the reflected energy, distances and relative heights of objects can be determined, even for objects as small as 5 cm. Lidar is
currently being used to produce precise digital terrain models; it also shows great promise as a
method for estimating forest stand structure. Today, lidar sensors operate from airborne platforms
(fixed-wing aircraft and helicopter), but in the year
2000 a satellite with three to five Lidar sensors was
scheduled to become operational (Flood and
Gutelius, 1997). Lidar was used by Means et ai.
(1999) to estimate forest stand characteristics such
as height, basal area, and biomass in western Oregon. Similar forest stand characteristics were measured by Lefsky et al. (1999) in eastern Maryland.
10.3.2 Vegetation Characteristics
Derived from Remote Sensing
Most remote sensing systems provide image data,
as opposed to point data. Images are made of thousands or even millions of data, either single picture
elements (pixels) or single grains of photographic
emulsion. As such, these data are interpreted, not
measured directly, by visual and computer-aided
analysis. Interpretations are made using the data's
interpreting satellite images. Aerial photographs,
with their high spatial resolution, provide a link between the resource data on the ground and the high
spectral resolution of satellite imagery.
An interagency program called the National High
Altitude Photography (NHAP) program was established in 1980 to build a uniform archive of aerial
photos of the 48 conterminous states. Black-andwhite and color-infrared photos were acquired at an
approximate scale of 1 : 80,000 and 1 : 58,000, respectively. In 1987, the flight specifications were
modified, as was the name: NHAP became the National Aerial Photography Program (NAPP). Blackand-white and color-infrared NAPP photos are
1 : 40,000 scale centered on quarters of 7.5-minute
quadrangles. Many image processing software packages have modules that allow the user to analyze and
manipulate digital copies of aerial photographs.
Airborne videography and digital camera systems provide powerful tools for ecosystem management. A camera can be mounted in a small airplane and imagery can be viewed as soon as the
flight is complete (King, 1995). A wide range of
spatial resolution can be obtained by varying the
flying altitude and camera lenses. Digital camera
imagery linked with GPS provides location information for each frame, allowing users to quickly
locate specific areas on maps or images. Images
can be georeferenced and used with other GIS layers. These systems are used for a variety of resource
applications, including aerial surveys for forest
pests (Knapp et al., 1998) and monitoring and mapping riparian areas (Bobbe et aI., 1993; Bobbe and
McKean, 1995) and as a high-resolution data source
for satellite image classification (Slaymaker et aI.,
1996).
Digital orthophoto quadrangles (DOQs) combine the image characteristics of a photograph with
the geometric qualities of a map. Wirth et ai. (1994)
describe the creation of DOQs as a process of scanning aerial photographs with each pixel of the image being corrected for relief displacement and
camera orientation. DOQs are valuable data
sources for updating road and existing land cover
databases and for georeferencing other data for use
in a GIS. However, the large file size associated
with DOQs can make them cumbersome to use. A
7.5 minute quadrangle-based DOQ is approximately 160 Mbytes. Often multiple DOQs, requiring hundreds of megabytes or even gigabytes of
hard disk space, need to be mosaicked together to
cover a project area. The large file size should become less of an issue as larger hard drives, faster
processors, and improved image compression techniques become available.
Remote Sensing Applied to Ecosystem Management
Radar Data
Radar systems form a unique addition to our capabilities for collecting remotely sensed data. The systems can operate during day or night and can penetrate clouds, thereby providing high-quality imagery
of Earth's surface in situations where photographic
or multispectral systems cannot be used (Hoffer et
al., 1995). Radar imagery can be obtained from aircraft or satellite platforms. Kasischke et ai. (1997)
discuss the capabilities of radar systems for investigating terrestrial ecosystems. They organize applications into four broad areas: (1) classification and
detection of change in land cover, (2) estimation of
woody plant biomass, (3) monitoring the extent and
timing of inundation, and (4) monitoring other temporally dynamic processes. Specific examples are
provided for each application area. Imhoff et al.
(1997) used radar imagery to discern structural differences relevant to bird habitat quality in the Northwest Territory, Australia.
Lidar Data
Compared to radar, lidar (light detection and ranging) is relatively new. This technology involves
pulsing Earth's surface with lasers and collecting
the reflected electromagnetic energy. By precisely
timing the interval between the emission of the
pulse and the detection of the reflected energy, distances and relative heights of objects can be determined, even for objects as small as 5 cm. Lidar is
currently being used to produce precise digital terrain models; it also shows great promise as a
method for estimating forest stand structure. Today, lidar sensors operate from airborne platforms
(fixed-wing aircraft and helicopter), but in the year
2000 a satellite with three to five Lidar sensors was
scheduled to become operational (Flood and
Gutelius, 1997). Lidar was used by Means et ai.
(1999) to estimate forest stand characteristics such
as height, basal area, and biomass in western Oregon. Similar forest stand characteristics were measured by Lefsky et al. (1999) in eastern Maryland.
10.3.2 Vegetation Characteristics
Derived from Remote Sensing
Most remote sensing systems provide image data,
as opposed to point data. Images are made of thousands or even millions of data, either single picture
elements (pixels) or single grains of photographic
emulsion. As such, these data are interpreted, not
measured directly, by visual and computer-aided
analysis. Interpretations are made using the data's