Chapter 14
134
discrimination and therefore of improvements in our ability to detect subtle
changes in the quality of vegetation.
Nevertheless, we should recognize that land cover information has
frequently been employed as a surrogate for physical variables that are not
directly accessible by other means, rather than as a product in its own right.
For example, meteorological models require estimates of aerodynamic
roughness and land cover has been used as a proxy; hydrological models
need maps of surface permeability in order to estimate through-flow;
estimates of ecosystem productivity and bio-geochemical fluxes have
similarly exploited land cover as a surrogate for more directly useful
physical variables, such as rates of photosynthesis or evapotranspiration.
Each of the above applications would be better served by representing the
variable of interest as a continuous surface, rather than as an arbitrary map of
an indeterminate classification of land cover. Given the very real prospect
that it may soon be possible and preferable to extract the biophysical data of
interest directly from Earth Observation, it may well be that the dominance
of land cover mapping in terrestrial applications of remote sensing will soon
be a phenomenon of the past, although it is likely that there will always be a
requirement for information on land cover and land cover change to inform
and direct the management and protection of landscapes.
13.
REFERENCES
Adams, J. B., Sabol, D. E., et al. (1995) Classification of multi-spectral images based on
fractions of end members: Application to land cover change in the Brazilian Amazon,
Remote Sensing of Environment, 52, 137–154.
Alonso, F. G. and Soria, S. L. (1991) Using contextual information to improve land use
classification of satellite images in central Spain, International Journal of Remote Sensing,
12, 2227–2235.
Babey, S.K. and Anger, C.D. (1989) A Compact Airborne Spectrographic Imager (CASI),
IGARSS 89/12th Canadian Symposium on Remote Sensing, Vancouver. B. C.
Barr, C. J., Bunce, R. G. H., and Heal, O.W. (1995) Countryside Survey 1990: A measure of
change, Journal of the RASE, 48–58.
Belward, A. S., Taylor, J. C., et al. (1990) An unsupervised approach to the classification of
semi-natural vegetation from Landsat Thematic Mapper data. A pilot study on Islay,
International Journal of Remote Sensing, 11, 429–445.
Belward, A. S., Kennedy, P. J., et al. (1994) The limitations and potential of AVHRR GAC
data for continental scale fire studies, International Journal of Remote Sensing, 15, 2215–
2234.
Binaghi, E., Madella, P., Montesano, G. and Rampini, A. (1997) Fuzzy contextual
classification of multi-source remote sensing images, IEEE Transactions on Geoscience
and Remote Sensing, 35, 326–340.
Bourgeau-Chavez, L. L., Harrell, P. A., et al. (1997) The detection and mapping of Alaskan
wildfires using a space-borne imaging radar system, International Journal of Remote
Sensing, 18, 355–373.
134
discrimination and therefore of improvements in our ability to detect subtle
changes in the quality of vegetation.
Nevertheless, we should recognize that land cover information has
frequently been employed as a surrogate for physical variables that are not
directly accessible by other means, rather than as a product in its own right.
For example, meteorological models require estimates of aerodynamic
roughness and land cover has been used as a proxy; hydrological models
need maps of surface permeability in order to estimate through-flow;
estimates of ecosystem productivity and bio-geochemical fluxes have
similarly exploited land cover as a surrogate for more directly useful
physical variables, such as rates of photosynthesis or evapotranspiration.
Each of the above applications would be better served by representing the
variable of interest as a continuous surface, rather than as an arbitrary map of
an indeterminate classification of land cover. Given the very real prospect
that it may soon be possible and preferable to extract the biophysical data of
interest directly from Earth Observation, it may well be that the dominance
of land cover mapping in terrestrial applications of remote sensing will soon
be a phenomenon of the past, although it is likely that there will always be a
requirement for information on land cover and land cover change to inform
and direct the management and protection of landscapes.
13.
REFERENCES
Adams, J. B., Sabol, D. E., et al. (1995) Classification of multi-spectral images based on
fractions of end members: Application to land cover change in the Brazilian Amazon,
Remote Sensing of Environment, 52, 137–154.
Alonso, F. G. and Soria, S. L. (1991) Using contextual information to improve land use
classification of satellite images in central Spain, International Journal of Remote Sensing,
12, 2227–2235.
Babey, S.K. and Anger, C.D. (1989) A Compact Airborne Spectrographic Imager (CASI),
IGARSS 89/12th Canadian Symposium on Remote Sensing, Vancouver. B. C.
Barr, C. J., Bunce, R. G. H., and Heal, O.W. (1995) Countryside Survey 1990: A measure of
change, Journal of the RASE, 48–58.
Belward, A. S., Taylor, J. C., et al. (1990) An unsupervised approach to the classification of
semi-natural vegetation from Landsat Thematic Mapper data. A pilot study on Islay,
International Journal of Remote Sensing, 11, 429–445.
Belward, A. S., Kennedy, P. J., et al. (1994) The limitations and potential of AVHRR GAC
data for continental scale fire studies, International Journal of Remote Sensing, 15, 2215–
2234.
Binaghi, E., Madella, P., Montesano, G. and Rampini, A. (1997) Fuzzy contextual
classification of multi-source remote sensing images, IEEE Transactions on Geoscience
and Remote Sensing, 35, 326–340.
Bourgeau-Chavez, L. L., Harrell, P. A., et al. (1997) The detection and mapping of Alaskan
wildfires using a space-borne imaging radar system, International Journal of Remote
Sensing, 18, 355–373.