Community Ecology
Volume/Issue:
Volume 4: Issue 2
Synoptic environmental indicators as image analogs for landscape analysis
Authors:
W.L. Myers School of Forest Resources and Penn State Institutes of Environment, The Pennsylvania State Unversity University Park, PA 16802, USA

Search for other papers by W.L. Myers in
Current site
Google Scholar
PubMed Close
,
G.P. Patil Center for Statistical Ecology and Environmental Statistics, Department of Statistics, The Pennsylvania State Unversity University Park, PA 16802, USA

Search for other papers by G.P. Patil in
Current site
Google Scholar
PubMed Close
,
C. Taillie Center for Statistical Ecology and Environmental Statistics, Department of Statistics, The Pennsylvania State Unversity University Park, PA 16802, USA

Search for other papers by C. Taillie in
Current site
Google Scholar
PubMed Close
, and
D.C. Walrath Penn State Institute of Environment, The Pennsylvania State Unversity University Park, PA 16802, USA

Search for other papers by D.C. Walrath in
Current site
Google Scholar
PubMed Close
Pages:
205–217
Online Publication Date:
22 Jul 2005
Publication Date:
01 Dec 2003
Article Category:
Research Article
DOI:
https://doi.org/10.1556/comec.4.2003.2.7
Keywords:
Species richness.; Species richness.; Change detection; Clustering algorithms; Geographic information systems; Image analysis; Environmental indicators; Landscape ecology; Remote sensing; Species habitat
Restricted access

Spatially synoptic multivariate image data implicitly embody information on landscape pattern, for which analytical techniques of explicit pattern extraction are evolving. In parallel, a multiplicity of 'environmental indicators' is being generated in the arena of geographic information systems. Landscape ecological analysis offers substantial opportunity for configuring these indicators synoptically as cells over spatial extents and for stacking them into complementary sets of image-structured multiple environmental indicators whereby the values of the indicators become intensity analogs of brightness for spectral bands. As environmental signal analogs of multiband images, these data become available to image portrayal in both graytone and quasi-color renditions to reveal joint properties of pattern for visual interpretation. Likewise, many of the conventional image analysis operations can be conceived more broadly to allow their application in the indicator context. This includes combinatorial approaches such as calculation of an NDVI equivalent from indicator intensities. Similarly, supervised and unsupervised analyses can have meaningful application in the context of multiple environmental indicators. Furthermore, newer techniques of pattern-based image segmentation can also be applied. Application to habitat modeling for vertebrates from Gap Analysis shows the effectiveness of the approach.

  • Chen, J., P. Gong, C. He, R. Pu and P. Shi. 2003. Land-use/land-cover change detection using improved change vector analysis. Photogrammetric Engineering and Remote Sensing 69: 369-379.

    'Land-use/land-cover change detection using improved change vector analysis ' () 69 Photogrammetric Engineering and Remote Sensing : 369 -379 .

    • Search Google Scholar

  • Coppin, P. and M. Bauer. 1996. Digital change detection in forest ecosystems with remote sensing imagery. Remote Sensing Reviews 13:207-234.

    'Digital change detection in forest ecosystems with remote sensing imagery ' () 13 Remote Sensing Reviews : 207 -234 .

    • Search Google Scholar

  • Davis, F. W., D. M. Stoms, J. E. Estes, J. Scepan and J. M. Scott. 1990. An information systems approach to biological diversity. International Journal of Geographic Information Systems 4: 55-78.

    'An information systems approach to biological diversity ' () 4 International Journal of Geographic Information Systems : 55 -78 .

    • Search Google Scholar

  • Forman, R. T. T. 1995. Land Mosaics: The Ecology of Landscapes and Regions. Cambridge University Press, Cambridge, U.K. 632 p.

    Land Mosaics: The Ecology of Landscapes and Regions , () 632 .

  • Forman, R. T. T. and M. Godron. 1986. Landscape Ecology. John Wiley & Sons, New York.

    Landscape Ecology. , ().

  • Frohn, R. 1998. Remote Sensing for Landscape Ecology: New Metric Indicators for Monitoring, Modeling, and Assessment of Ecosystems. Lewis Publishers, Boca Raton, FL.

    Remote Sensing for Landscape Ecology: New Metric Indicators for Monitoring, Modeling, and Assessment of Ecosystems. , ().

    • Search Google Scholar

  • Gibson, P. and C. Power. 2000. Introductory Remote Sensing: Principles and Practices. Taylor and Francis, New York.

    Introductory Remote Sensing: Principles and Practices , ().

  • Gong, P. 1993. Change detection using principal component analysis and fuzzy set theory. Canadian Journal of Remote Sensing 19: 22-29.

    'Change detection using principal component analysis and fuzzy set theory ' () 19 Canadian Journal of Remote Sensing : 22 -29 .

    • Search Google Scholar

  • Isaaks, E. and R. M. Shrivastava 1989. An Introduction to Applied Geostatistics. Oxford Univ. Press, New York.

    An Introduction to Applied Geostatistics. , ().

  • James, M. 1985. Classification Algorithms. John Wiley & Sons, London, UK.

    Classification Algorithms. , ().

  • Jensen, J. 2000. Remote Sensing of the Environment: An Earth Resource Perspective. Prentice-Hall, Upper Saddle River, NJ.

    Remote Sensing of the Environment: An Earth Resource Perspective , ().

  • Lunetta, R. and C. Elvidge, eds. 1998. Remote Sensing Change Detection: Environmental Monitoring Methods and Applications. Ann Arbor Press, Ann Arbor, MI.

    Remote Sensing Change Detection: Environmental Monitoring Methods and Applications. , ().

    • Search Google Scholar

  • Mas, J. 1999. Monitoring land-cover changes: a comparison of change detection techniques. International Journal of Remote Sensing 20: 139-152.

    'Monitoring land-cover changes: a comparison of change detection techniques ' () 20 International Journal of Remote Sensing : 139 -152 .

    • Search Google Scholar

  • McGarigal, K. and B. Marks. 1995. FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. General Technical Report PNW 351, U.S. Forest Service, Pacific Northwest Research Station.

    FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. General Technical Report PNW 351 , ().

    • Search Google Scholar

  • Miller, E. W, Ed. 1995. A Geography of Pennsylvania. The Pennsylvania State University Press, University Park, PA.

    A Geography of Pennsylvania. , ().

  • Myers, W. 2000. Landscape scale ecological mapping of Pennsylvania forests. Research Rept. ER2002, Environmental Resources Research Institute, The Pennsylvania State University, Univ. Park, PA 16802 USA.

    Landscape scale ecological mapping of Pennsylvania forests. Research Rept. ER2002 , ().

    • Search Google Scholar

  • Myers, W. 2003. Doubly segmented images for pattern-based approach to change detection. Final report on NASA Research Project NAG5-1054. Research Report PSIE 2003-6, Penn State Institutes of Environment, The Pennsylvania State University, Univ. Park, PA 16802 USA. 90 pp. + CD-ROM.

    Doubly segmented images for pattern-based approach to change detection. Final report on NASA Research Project NAG5-1054. Research Report PSIE 2003-6 , () 90 .

    • Search Google Scholar

  • Myers, W., J. Bishop, R. Brooks, T. O'Connell, D. Argent, G. Storm, J. Stauffer, Jr. and R. Carline. 2000. The Pennsylvania GAP Analysis Final Report. The Pennsylvania State University, Univ. Park, PA 16802.

    The Pennsylvania GAP Analysis Final Report , ().

  • Myers, W., J. Bishop, R. Brooks and G. P. Patil. 2001. Composite spatial indexing of regional habitat importance. Community Ecology 2: 213-220.

    'Composite spatial indexing of regional habitat importance ' () 2 Community Ecology : 213 -220 .

    • Search Google Scholar

  • Myers, W., G. P. Patil and C. Taillie. 1999. Conceptualizing pattern analysis of spectral change relative to ecosystem status. Ecosystem Health 5: 285-293.

    'Conceptualizing pattern analysis of spectral change relative to ecosystem status ' () 5 Ecosystem Health : 285 -293 .

    • Search Google Scholar

  • Myers, W., G. P. Patil and C. Taillie. 2003. Doubly segmented proxy images for multi-scale landscape ecology and ecosystem health. Community Ecology 4:163-183.

    'Doubly segmented proxy images for multi-scale landscape ecology and ecosystem health ' () 4 Community Ecology : 163 -183 .

    • Search Google Scholar

  • Olivieri, S. T. and E. H. Backus. 1992. Geographic information systems (GIS) Applications in biological conservation. Biology International 25: 10-16.

    'Geographic information systems (GIS) Applications in biological conservation ' () 25 Biology International : 10 -16 .

    • Search Google Scholar

  • Rogan, J., J. Miller, D. Stow, J. Franklin, L. Levien and C. Fisher. 2003. Land-cover change monitoring with classification trees using Landsat TM and ancillary data Photogrammetric Engineering and Remote Sensing 69: 793-804.

    'Land-cover change monitoring with classification trees using Landsat TM and ancillary data ' () 69 Photogrammetric Engineering and Remote Sensing : 793 -804 .

    • Search Google Scholar

  • Scott, J. M., F. Davis, B. Custi, R. Noss, B. Butterfield, C. Groves, H. Anderson, S. Caicco, F. D'Erchia, T. C. Edwards, Jr., J. Ulliman and R. G. Wright. 1993. Gap analysis: A geographic approach to protection of biological diversity. Wildlife Monographs No. 123.

    'Gap analysis: A geographic approach to protection of biological diversity ' () Wildlife Monographs .

    • Search Google Scholar

  • Singh, A. 1989. Digital change detection techniques using remotely sensed data. International Journal of Remote Sensing 10: 989-1003.

    'Digital change detection techniques using remotely sensed data ' () 10 International Journal of Remote Sensing : 989 -1003 .

    • Search Google Scholar

  • Tso, B. and P. Mather. 2001. Classification Methods for Remotely Sensed Data. Taylor and Francis, New York.

    Classification Methods for Remotely Sensed Data , ().

  • Walrath, D. 2000. Multiscale analysis of avian distributions in Pennsylvania Master of Science Thesis in Ecology, The Pennsylvania State University, Univ. Park, PA 16802 USA.

    Multiscale analysis of avian distributions in Pennsylvania Master of Science Thesis in Ecology , ().

    • Search Google Scholar

  • Wilkie, D. and J. Finn. 1996. Remote Sensing Imagery for Natural Resources Monitoring: A Guide for First-Time Users. Columbia University Press, New York.

    Remote Sensing Imagery for Natural Resources Monitoring: A Guide for First-Time Users , ().

    • Search Google Scholar

  • Argent, D., J. Bishop, J. Stauffer, R. Carline and W. Myers. 2003. Predicting freshwater fish distributions using landscape-level variables. Fisheries Research 60: 17-32.

    'Predicting freshwater fish distributions using landscape-level variables ' () 60 Fisheries Research : 17 -32 .

    • Search Google Scholar

  • Brauning, D. 1992. Atlas of Breeding Birds in Pennsylvania. University of Pittsburgh Press, Pittsburgh, PA.

    Atlas of Breeding Birds in Pennsylvania. , ().

  • Bruzzone, L. and D. Prieto. 2000. Automatic analysis of the difference image for unsupervised change detection. IEEE Transactions on Geoscience and Remote Sensing 38: 1171-1182.

    'Automatic analysis of the difference image for unsupervised change detection ' () 38 IEEE Transactions on Geoscience and Remote Sensing : 1171 -1182 .

    • Search Google Scholar
  • Collapse
  • Expand
Cover Community Ecology
Community Ecology An Interdisciplinary Journal Reporting Progress in Community and Population Studies
Print ISSN:
1585-8553
Online ISSN:
1588-2756

To see the editorial board, please visit the website of Springer Nature.

Manuscript Submission: HERE

For subscription options, please visit the website of Springer Nature.

Community Ecology
Language English
Size A4
Year of
Foundation		 2000
Volumes
per Year		 1
Issues
per Year		 3
Founder Akadémiai Kiadó
Founder's
Address		 H-1117 Budapest, Hungary 1516 Budapest, PO Box 245
Publisher Akadémiai Kiadó
Springer Nature Switzerland AG
Publisher's
Address		 H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
CH-6330 Cham, Switzerland Gewerbestrasse 11.
Responsible
Publisher		 Chief Executive Officer, Akadémiai Kiadó
ISSN 1585-8553 (Print)
ISSN 1588-2756 (Online)

Monthly Content Usage

Abstract Views Full Text Views PDF Downloads
Nov 2024 43 0 0
Dec 2024 39 0 0
Jan 2025 46 0 0
Feb 2025 52 0 0
Mar 2025 56 0 0
Apr 2025 25 0 0
May 2025 0 0 0