Recommendations on Using Remote
Sensing to Monitor Mountain Goat
Habitat
DRAFT
Prepared by:
Steven F. Wilson, Ph.D., R.P.Bio.
EcoLogic Research
406 Hemlock Avenue
Gabriola Island, BC V0R 1X1
V0R 1X1
steven.wilson@ecologicresearch.ca
247-7435
Prepared for:
Ecosystems Branch
BC Ministry of Environment
4th Floor, 2975 Jutland Ave
Victoria, BC
28 February 2009
Introduction
The Forest and Range Evaluation Program is developing monitoring and evaluation strategies in relation
to specific values affected by forest and range activities. One of the key priority monitoring questions is
related to the evaluation of ungulate winter ranges. Winter ranges established for mountain goats, are
often located in remote and inaccessible locations; therefore, there may be opportunities to use remotely
sensed data to assist with the evaluation of the ranges’ effectiveness.
The report briefly outlines opportunities for using remote sensing technology to monitor mountain goat
winter ranges.
What is Remote Sensing?
Remote sensing refers to using instrument-based techniques to measure spatially organized properties of
features that are located at some distance from the instrument. Techniques can vary from manual
interpretation of aerial photos to computer-based analysis of non-visible radiation collected by satellitebased sensors.
What are the Advantages of Using Remote Sensing for
Monitoring?
There are a number of potential advantages of using remote-sensing technology for monitoring mountain
goat habitat (Coops and Bater 2008):
• analysis can cover large spatial areas;
• data can be collected at a high spatial resolution;
• change can be detected through repeated observation; and,
• data collection can be cost-effective compared to alternatives.
Monitoring Requirements of Mountain Goat Habitat
Wilson (2009) describes monitoring questions, indicators and monitoring methods for assessing the
effectiveness of mountain goat winter ranges. Assessment methods fall into two spatial scales.
UWR-scale and Smaller
Assessment at the scale of individual winter ranges includes collecting data related to forest canopy
characteristics (e.g., percent cover by canopy layer, forest health and blowdown), snow depth and
consolidation, and evidence of use by mountain goats (e.g., tracks, browse, pellets). Some data generally
require ground assessments or low-speed reconnaissance flights.
Watershed-scale and Larger
Assessments at the watershed scale or larger addresses whether a sufficient proportion of suitable (or
capable) mountain goat habitat is under management, or whether there is evidence that goats are moving
among winter ranges.
Remote Sensing Techniques
Remote sensing techniques that might be relevant to monitoring mountain goat habitat can be classified
into the following general categories:
1. Aircraft-based sensors:
Draft recommendations on using remote sensing to monitor goat winter ranges
2
a. Aerial photography - interpretation of aerial photographs is currently the principle operational
technique for conducting forest and ecosystem inventories. Cover types are interpreted manually,
which makes the system time-consuming and expensive, but accurate. The resolution of aerial
photography exceeds that of any available satellite-based platform. Aerial photos need to be
scanned and orthorectified before they can be in GIS applications.
b. Lidar - “light detection and ranging system” is capable of mapping both terrain and vegetation
structure at <1 m resolution (Bater et al. 2008). Lidar instruments are mounted on aircraft, emit
pulses of laser light and measure the characteristics of returning signals. The footprint of the
beam is <1 m, so Lidar generally samples an area-of-interest and results are interpolated using
aerial photography or satellite imagery.
2. Satellite-based sensors:
a. Landsat - the Landsat program has been collecting freely available images of the earth’s surface
since 1972. Data are imaged in the visible, shortwave and infrared spectra at a 30 m resolution.
Although the resolution is relatively low, an archive of 35 years of images, covering the entire
earth every 16 days, has provided a important database for measuring landscape change.
b. High-resolution satellite imagery - there are a number satellite image products now available that
exceed the resolution of Landsat. These are known by trade names such as SPOT, IKONOS and
Quickbird. The Province has acquired SPOT-5 images at a resolution of 5 m.
c.
Radar - unlike visible- and near-visible light systems, satellite-based radar imaging is not limited
by daylight or clouds. Radar has been used for terrain, land cover and forest structure mapping,
although at a lower resolution than that available by Lidar.
Cost advantages derived from remote sensing are due to:
1. Lower costs to acquire data - aerial photography and Lidar offer cost benefits over ground-based
reconnaissance because data can be acquired over a larger area more quickly and at a lower unit
cost. Similarly, satellite-derived data offer cost savings over aerial-based data because images are
usually just purchased from an existing database and there are no costs associated with logistics,
flight time, specialized equipment and analysis. But moving from ground to aerial to satellite data
comes at the cost of reduced resolution in the data.
2. Automated classification - cost saving can be significant if image classification (i.e., spatial identifying
relevant features from an image) can be done by automatically through software applications rather
than by technicians. This is an area of active research but few applications are sufficiently advanced
to provide operational alternatives to manual classification.
Application of Remote Sensing to Monitoring
There are several remote sensing techniques that might be suitable for collecting monitoring data (Table
1).
Table 1. Data requirements related to monitoring the effectiveness of mountain goat winter ranges, and
the potential of different remote-sensing technologies to provide the data.
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Indicator
Data Required
Suitable Remote
Sensing Technology
Notes
1. Proportion of suitable
or capable habitat
managed as mountain
goat winter range.
Aspect, slope,
consolidated rock,
forest cover >120 years
Aerial photography - for
consolidated rock and
forest cover, use
existing terrain
mapping.
Variables are based on
Wilson (2009) and
could be expanded to
generate a more
detailed model.
Lidar - for highresolution terrain
mapping. Rock and
vertical structure
characteristics of forest
canopy.
All variables are
currently available from
existing data sources;
however, higherresolution terrain
mapping and forest
characteristics could
refine the model.
Landsat - low resolution
terrain and forest cover
mapping.
SPOT-5 - provides all
variables but coarser
resolution of forest
characteristics than
aerial photography
Radar - high resolution
terrain mapping, rock
and some forest
characteristics can be
interpreted.
Forest cover
characteristics
Percent canopy cover
of different strata,
abundance of arboreal
lichens, blowdown and
forest health
Aerial photography provides rudimentary
canopy information but
much poorer than
ground reconnaissance.
Lidar - can provide
detailed vertical
structure information.
No remote sensing
method can directly
detect arboreal lichens.
Lidar holds the most
promise but also
requires extensive
processing and
interpretation.
Radar - some forest
structural
characteristics can be
identified
Evidence of movement
among winter ranges
Mountain goat location
data
None
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Indicator
Data Required
Suitable Remote
Sensing Technology
Notes
Snow conditions
Snow depth and
consolidation
None
Coops and Bater (2008)
do not identify any
technology capable of
remotely sensing snow
depth and consolidation
data, particularly under
canopy.
Evidence of sustained
use
Tracks, browse, pellets,
location data
None
Utility of remote-sensing technologies can be summarized as follows:
• Landsat - suitable for monitoring changes in cover characteristics over time across large areas (i.e.,
watershed to province-wide). Automated processing is possible. Data are widely available and
retrospective analyses spanning 30 years can be conducted.
• SPOT 5 - a suitable alternative to aerial photography for identifying rock and monitoring forest cover
changes (excluding vertical canopy characteristics). The advantage of satellite imagery is that it is
available where recent aerial photos may not be, and satellite imagery is updated more frequently.
Coverages are GIS-ready and are produced at an adequate resolution to identify most of the required
features. Automated processing for some features may be feasible.
• Lidar could provide extensive vertical structure mapping of forests, but logistics and analysis
requirements are significant. If combined with assessments for other values, Lidar might be a feasible
option, depending on the desired scale of the monitoring.
• Radar could provide benefit similar to Landsat but at higher spatial resolutions. The availability of
Landsat and SPOT 5 imagery reduces the utility of radar mapping, except for creating higher-resolution
terrain maps than are currently available.
Discussion
Existing and emerging remote sensing technologies provide the opportunity to address at least some of
the monitoring requirements of goat winter ranges. There will always be data that cannot be collected via
remote sensing. These include direct censusing of animals, monitoring goat movements via telemetry or
GPS, and directly observing tracks, pellets or browse. Snow conditions cannot currently be remotely
sensed, although this might become possible with advances in technology.
The utility of remote sensing increases at smaller scales and larger spatial extents; therefore, the
applicability of some technologies depends on the emphasis places on extensive versus intensive
monitoring. For example, long-term monitoring of broad forest conditions on winter ranges or in the forest
matrix between winter ranges at watershed or subregional scales can be based on manual or partly
automated analysis of landsat imagery. In contrast, remotely sensed data are of limited utility if the
emphasis is on confirming use of ranges by goats, or on measuring snow characteristics.
Opportunities to use remote sensing techniques appear limited because indicators and monitoring
protocols were designed in the context of currently available tools (Wilson 2009). With different tools, the
indicators and protocols could change to take advantage of them. For example, higher resolution terrain
and remotely sensed forest structure data could significantly improve the identification of potential
mountain goat habitat and make the province-wide monitoring of habitat conditions more feasible.
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There are significant opportunities to integrate the monitoring of goat winter ranges with other values if
remote sensing applications are further developed. For example, many of the forest characteristics that
are important to monitor on goat winter ranges are important characteristics to monitor for other values,
including winter ranges of other ungulate species, habitat for other wildlife species (e.g., White-headed
Woodpecker, Marbled Murrelet), biodiversity, riparian, timber and visual quality values.
Recommendations
• Common monitoring requirements among FREP values should be identified, in order to gauge
efficiencies that could be realized by remote sensing techniques;
• any projects currently being conducted by the Ministry of Forests and Range related to Lidar or
automated image processing should be examined for opportunities to leverage the projects to pilot
monitoring techniques on winter ranges or other areas; and,
• if the FREP program standardizes on one or more remote-sensing technologies, then the indicators and
protocols associated with winter range monitoring should be re-examined to capitalize on the availability
of the data.
Literature Cited
Bater, C. W., D. Collins, and N. C. Coops. 2008. Lidar remote sensing: mapping British Columbia’s
forests with lasers. Research Section, Coast Forest Region, BC Ministry of Forests and Range, Nanaimo,
Extension Note EN-025.
Coops, N. C., and C. W. Bater. 2008. Remote sensing opportunities for monitoring indicators of forest
sustainability. Draft. Integrated Remote Sensing Studio, Department of Forest Resources Management,
Faculty of Forestry, University of British Columbia, Vancouver.
Wilson, S. F. 2009. Effectiveness monitoring for mountain goat winter ranges: methods and field trials.
Prepared for: Ecosystems Branch, BC Ministry of Environment, Victoria.
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