148
Mendocino National Forest in California (Lachowski et al., 1997; Hardwick et al., 1998). The
display of digital data allowed faster identification
of critical areas within the burn to focus the team's
limited and expensive time. Mapping using digital
camera imagery proved, in this instance, to be 20%
more accurate than traditional mapping methods and
saved an estimated $250,000 in rehabilitation costs.
Noxious weeds are transported by wildlife, livestock, wind, water, vehicles, and people to new
sites and then become established in soil disturbed
by construction, travel, or recreation. Once established, they are able to invade adjacent undisturbed
plant communities, where they tend to crowd out
native species. Many noxious weeds have sitespecific requirements that can be modeled to identify areas susceptible to invasion and possibly the
degree of susceptibility. The cost of data acquisition can be better allocated or even reduced by
knowing if an area is susceptible to invasion and
how susceptible it is. Many of the GIS data layers
needed for susceptibility modeling come from remote sensing sources. A project in central Idaho
demonstrated how a vegetation-cover-type map developed from Landsat TM and digital elevation
models as well as other data layers could be used
to generate a map of susceptible area (Varner et aI.,
1998).
10.5 Conclusions
Geospatial information describing our land and natural resources is the backbone of effective ecosystem management. The examples provided here illustrate just a few of the areas where geospatial
information and specifically information originating from various remote sensors have been used to
increase our knowledge of ecosystems. Information
from remote sensing provides us with a unique vantage point that permits both broad-scale perspectives and project area analysis. Remote sensing not
only offers a means for providing cost-effective information, but in many areas provides the only information available to study ecosystems. As new sensors with finer spatial and spectral resolution become
available, the ability to interpret and process data
from these sensors will follow. Image-processing
software for remote sensing image analysis is becorning widespread and, with appropriate training,
will be an important tool for managing ecosystems.
Information derived from remote sensing serves
many diverse applications in managing ecosystems. These applications range from monitoring
forest sustainability through criteria and indicators
at the national level to mapping and monitoring
Remote Sensing Applied to Ecosystem Management
land cover at various ecosystem and land management levels.
10.6 References
Achard, F.; Estreguil, C. 1995. Forest classification of
Southeast Asia using NOAA A VHRR data. Remote
Sens. Environ. 54(3):198-208.
Agee, J. K.; Johnson, D. R. 1988. Introduction to ecosystem management. In: Agee, J. K; Johnson, D. R., eds.
Ecosystem management for parks and wilderness.
Seattle: University of Washington Press: 3-14.
Atkinson, P. M.; Curran, P. J. 1997. Choosing an appropriate spatial resolution for remote sensing investigation. Photogramm. Eng. Remote Sensing 63(12):
1345-1351.
Avers, P. E.; Cleland, D. T.; McNab, W. H.; Jensen, M.
E.; Bailey, R. G.; King, T.; Goudey, C. B. 1993. National hierarchical framework of ecological units.
Washington DC: U.S. Dept. Agric., For. Servo
Avery, T. E.; Berlin, G. L. 1992. Fundamentals of remote sensing and air photo interpretation, 5th ed. Minneapolis, MN: Burgess Publishing Co.
Bailey, R. G. 1996. Ecosystem geography. New York:
Springer-Verlag.
Bobbe, T.; McKean, 1. 1995. Evaluation of a digital camera system for natural resource management. Earth
Observation Magazine: 45--48.
Bobbe, T.; Reed, D.; Schramek, J. 1993. Georeferenced
airborne video imagery. J. For. 91(8):34-37.
Boudreau, S. L.; Maus, P. A. 1996. An ecological approach to assess vegetation change after large scale
fires on the Payette National Forest. In: Greer, J. D.,
ed. Proceedings of the sixth biennial Forest Service
conference on remote sensing. Denver, CO: Amer.
Soc. Photogramm. Remote Sensing: 330-339.
Brand, D. G. 2001. Criteria and indicators for the conservation and sustainable management of forests:
progress to date and future directions. New Zealand J.
For. An online version of the paper is located at:
http://www.forest.nsw.gov.aulsfmlJCIPAPE.html.
Campbell, J. B. 1996. Introduction to remote sensing,
2nd ed. New York: Guilford Press.
Cohen, W. B.; Spies, T. A. 1992. Estimating structural
attributes of Douglas-fir/western hemlock forest
stands from Landsat and SPOT imagery. Remote Sens.
Environ. 41(1):1-17.
Collins, J. B.; Woodcock, C. E. 1997. An assessment of
several linear change detection techniques for mapping forest mortality using multitemporal Landsat TM
data. Remote Sens. Environ. 56(1):66-77.
Congalton, R.; Green, K 1998. Assessing the accuracy
of remotely sensed data, principles and practices.
Boca Raton, FL: Lewis Publishers.
Congalton, R.; Green, K; Teply, J. 1993. Mapping old
growth forests on national forest and park lands in the
Pacific Northwest from remotely sensed data. Photogramm. Eng. Remote Sensing 59(4):529-535.
Cristofani, A. 1996. The earth in balance-maintaining
Brazil's biodiversity. GPS World 7(6):20-30.
Mendocino National Forest in California (Lachowski et al., 1997; Hardwick et al., 1998). The
display of digital data allowed faster identification
of critical areas within the burn to focus the team's
limited and expensive time. Mapping using digital
camera imagery proved, in this instance, to be 20%
more accurate than traditional mapping methods and
saved an estimated $250,000 in rehabilitation costs.
Noxious weeds are transported by wildlife, livestock, wind, water, vehicles, and people to new
sites and then become established in soil disturbed
by construction, travel, or recreation. Once established, they are able to invade adjacent undisturbed
plant communities, where they tend to crowd out
native species. Many noxious weeds have sitespecific requirements that can be modeled to identify areas susceptible to invasion and possibly the
degree of susceptibility. The cost of data acquisition can be better allocated or even reduced by
knowing if an area is susceptible to invasion and
how susceptible it is. Many of the GIS data layers
needed for susceptibility modeling come from remote sensing sources. A project in central Idaho
demonstrated how a vegetation-cover-type map developed from Landsat TM and digital elevation
models as well as other data layers could be used
to generate a map of susceptible area (Varner et aI.,
1998).
10.5 Conclusions
Geospatial information describing our land and natural resources is the backbone of effective ecosystem management. The examples provided here illustrate just a few of the areas where geospatial
information and specifically information originating from various remote sensors have been used to
increase our knowledge of ecosystems. Information
from remote sensing provides us with a unique vantage point that permits both broad-scale perspectives and project area analysis. Remote sensing not
only offers a means for providing cost-effective information, but in many areas provides the only information available to study ecosystems. As new sensors with finer spatial and spectral resolution become
available, the ability to interpret and process data
from these sensors will follow. Image-processing
software for remote sensing image analysis is becorning widespread and, with appropriate training,
will be an important tool for managing ecosystems.
Information derived from remote sensing serves
many diverse applications in managing ecosystems. These applications range from monitoring
forest sustainability through criteria and indicators
at the national level to mapping and monitoring
Remote Sensing Applied to Ecosystem Management
land cover at various ecosystem and land management levels.
10.6 References
Achard, F.; Estreguil, C. 1995. Forest classification of
Southeast Asia using NOAA A VHRR data. Remote
Sens. Environ. 54(3):198-208.
Agee, J. K.; Johnson, D. R. 1988. Introduction to ecosystem management. In: Agee, J. K; Johnson, D. R., eds.
Ecosystem management for parks and wilderness.
Seattle: University of Washington Press: 3-14.
Atkinson, P. M.; Curran, P. J. 1997. Choosing an appropriate spatial resolution for remote sensing investigation. Photogramm. Eng. Remote Sensing 63(12):
1345-1351.
Avers, P. E.; Cleland, D. T.; McNab, W. H.; Jensen, M.
E.; Bailey, R. G.; King, T.; Goudey, C. B. 1993. National hierarchical framework of ecological units.
Washington DC: U.S. Dept. Agric., For. Servo
Avery, T. E.; Berlin, G. L. 1992. Fundamentals of remote sensing and air photo interpretation, 5th ed. Minneapolis, MN: Burgess Publishing Co.
Bailey, R. G. 1996. Ecosystem geography. New York:
Springer-Verlag.
Bobbe, T.; McKean, 1. 1995. Evaluation of a digital camera system for natural resource management. Earth
Observation Magazine: 45--48.
Bobbe, T.; Reed, D.; Schramek, J. 1993. Georeferenced
airborne video imagery. J. For. 91(8):34-37.
Boudreau, S. L.; Maus, P. A. 1996. An ecological approach to assess vegetation change after large scale
fires on the Payette National Forest. In: Greer, J. D.,
ed. Proceedings of the sixth biennial Forest Service
conference on remote sensing. Denver, CO: Amer.
Soc. Photogramm. Remote Sensing: 330-339.
Brand, D. G. 2001. Criteria and indicators for the conservation and sustainable management of forests:
progress to date and future directions. New Zealand J.
For. An online version of the paper is located at:
http://www.forest.nsw.gov.aulsfmlJCIPAPE.html.
Campbell, J. B. 1996. Introduction to remote sensing,
2nd ed. New York: Guilford Press.
Cohen, W. B.; Spies, T. A. 1992. Estimating structural
attributes of Douglas-fir/western hemlock forest
stands from Landsat and SPOT imagery. Remote Sens.
Environ. 41(1):1-17.
Collins, J. B.; Woodcock, C. E. 1997. An assessment of
several linear change detection techniques for mapping forest mortality using multitemporal Landsat TM
data. Remote Sens. Environ. 56(1):66-77.
Congalton, R.; Green, K 1998. Assessing the accuracy
of remotely sensed data, principles and practices.
Boca Raton, FL: Lewis Publishers.
Congalton, R.; Green, K; Teply, J. 1993. Mapping old
growth forests on national forest and park lands in the
Pacific Northwest from remotely sensed data. Photogramm. Eng. Remote Sensing 59(4):529-535.
Cristofani, A. 1996. The earth in balance-maintaining
Brazil's biodiversity. GPS World 7(6):20-30.