Methodology and Statistics
International Conference, 24 - 27 September 2000
Hotel Bor and Castle Hrib, Preddvor, Slovenia
Watershed Frontier of Landscape Health Assessment in
Environmental and Ecological Statistics
G. P. Patil
Center for Statistical Ecology and Environmental Statistics
Department of Statistics
The Pennsylvania State University, University Park, PA 16802 USA
It is exciting to see that it looks now feasible to do landscape health
assessment using remote imagery and multiscale landscape fragmentation.
Using various technologies, it is now
possible to provide snapshots of landscapes indicative of various features of
interest pertaining to human societies, plant and animal communities, aquatic
networks, etc. This information can be
represented in various kinds of multicolor maps that depict political, natural,
methodological, or other features.
These multicolor maps provide a basis for comparative assessments of
regions within a policy making and implementation context.
It is also possible to extract meaningful
profiles of management units, such as watersheds, that can be calibrated and
compared in order to assess and manage watersheds of a region.
These current developments are part of the
environmental and ecological information superhighway and are at the cutting
edge of regional policy research with
remote imagery and geospatial information.
When a natural landscape is cast as a categorical raster map, a
multiresolution characterization of spatial pattern can be obtained whereby the
entropy is computed for a finer resolution map, conditioned on the values of a
coarser resolution map. After application
to a sequence of rescaled maps which have increasingly degraded resolution, the
conditional entropy is plotted as a function of measurement scale (resolution),
thus resulting in a multiresolution profile of fragmentation patterns.
For neutral landscapes that are simulated by multiresolution stochastic
generating models, we present a method to directly compute conditional entropy
profiles. Such profiles can provide
benchmarks for comparing results obtained from raster maps of actual landscapes
that are classified from satellite images.
Results show that characteristic landscape types give rise to
characteristic features of these fragmentation (conditional entropy)
profiles.
Keywords:
Multiscale landscape fragmentation profile,
Multiscale assessment of landscapes
and watersheds, Multiresolution stochastic generating matrices.
References
Johnson, G. D., Myers, W. L., and Patil,
G. P. (1999). Stochastic generating
models for simulating hierarchically structured multi-cover landscapes.
Landscape Ecology, 14, 413-421.
Johnson, G. D., Myers, W. L., Patil, G.
P., and Taillie, C. (1999).
Multiresolution fragmentation profiles for assessing hierarchically
structured landscape patterns. Ecological Modeling, 116, 293--301,
1999.
Johnson, G. D., Myers, W. L., Patil, G.
P., and Taillie, C. (2000).
Characterizing watershed-delineated landscapes in Pennsylvania using
conditional entropy profiles. Landscape Ecology. (Under revision).
Johnson, G. D., Myers, W. L., Patil, G. P. and Taillie, C. (2000).
Fragmentation profiles for real and
simulated landscapes. Environmental and Ecological Statistics,
7(4). (To appear).
Johnson, G. D., and Patil, G. P. (1998).
Quantitative multiresolution characterizations of landscape patterns for
assessing the status of ecosystem health in watershed management areas.
Ecosystem
Health, 4(3), 177—187.
Myers, W. L., Patil, G. P.,
and Taillie, C. (1999).
Conceptualizing pattern analysis of spectral
change relative to ecosystem health. Ecosystem Health,
5(4), 285—293.
Patil, G. P. (1998).
Environmental and ecological regional policy research with remote
imagery and geospatial information.
Issues, approaches, and examples.
Technical Report 98-1201, Center for Statistical Ecology and
Environmental Statistics, Department of Statistics, Penn State University,
University Park, PA.
Patil, G. P., and Myers, W. L.
(1999). Guest Editorial:
Environmental and ecological health
assessment of landscapes and watersheds with remote sensing data.
Ecosystem
Health, 5(4), 221—224.
Patil, G. P., and Taillie, C. (1999).
Fitting a multiscale hierarchical generating
model for thematic raster maps.
Technical Report 99-0203, Center for Statistical Ecology and
Environmental Statistics, Department of Statistics, Penn State University, University
Park, PA.
Patil, G. P., and Taillie, C.
(1999).
A Markov model for hierarchically scaled landscape patterns. In
Bull. of the International Statistical
Institute, Volume 58, Book 1. pp.
89-–92.
Rapport, D. J., Christensen, N., Karr, J.
R., and Patil, G. P. (1999). The
centrality of ecosystem health in achieving sustainability in the 21st
century: Concepts and New Approaches to
Environmental Management. Human
Survivability in the 21st Century:
Transactions of the Royal Society of Canada, University of Toronto
Press, pp. 3--40, 1999.
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