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

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 satellite-based 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:
  2. 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.
  3. 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.
  1. Satellite-based sensors:
  2. 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.
  3. 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.
  4. 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.

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.
Lidar - for high-resolution terrain mapping. Rock and vertical structure characteristics of forest canopy.
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. / Variables are based on Wilson (2009) and could be expanded to generate a more detailed model.
All variables are currently available from existing data sources; however, higher-resolution terrain mapping and forest characteristics could refine the model.
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.
Radar - some forest structural characteristics can be identified / No remote sensing method can directly detect arboreal lichens.
Lidar holds the most promise but also requires extensive processing and interpretation.
Evidence of movement among winter ranges / Mountain goat location data / None
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.

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.

Recommendations on using remote sensing to monitor goat winter ranges1