Extending satellite remote sensing to local scales: Land and water resource monitoring using high-resolution imagery

Kali E. Sawaya, Leif Olmanson, Nathan J. Heinert, Patrick L. Brezonik, Marvin E. Bauer

Research output: Contribution to journalArticlepeer-review

333 Scopus citations


The potential of high-resolution IKONOS and QuickBird satellite imagery for mapping and analysis of land and water resources at local scales in Minnesota is assessed in a series of three applications. The applications and accuracies evaluated include: (1) classification of lake water clarity (r 2=0.89), (2) mapping of urban impervious surface area (r 2=0.98), and (3) aquatic vegetation surveys of emergent and submergent plant groups (80% accuracy). There were several notable findings from these applications. For example, modeling and estimation approaches developed for Landsat TM data for continuous variables such as lake water clarity and impervious surface area can be applied to high-resolution satellite data. The rapid delivery of spatial data can be coupled with current GPS and field computer technologies to bring the imagery into the field for cover type validation. We also found several limitations in working with this data type. For example, shadows can influence feature classification and their effects need to be evaluated. Nevertheless, high-resolution satellite data has excellent potential to extend satellite remote sensing beyond what has been possible with aerial photography and Landsat data, and should be of interest to resource managers as a way to create timely and reliable assessments of land and water resources at a local scale.

Original languageEnglish (US)
Pages (from-to)144-156
Number of pages13
JournalRemote Sensing of Environment
Issue number1-2
StatePublished - Nov 30 2003

Bibliographical note

Funding Information:
We gratefully acknowledge the support of the NASA Science Data Purchase for providing IKONOS images, the Upper Great Lakes Regional Earth Science Applications Center (NASA grant NAG-13-99002), and the University of Minnesota Agricultural Experiment Station. We also appreciate the interest and cooperation of the City of Eagan, Metropolitan Council, Minnesota Pollution Control Agency and Minnesota Department of Natural Resources. Melanie Tyler and John D. Madsen, Biological Sciences Department, Minnesota State University, Mankato, provided the aquatic vegetation survey field data. We also thank the reviewers whose comments helped us improve this paper. Finally, we thank Sarah Finley for her help in compiling and editing this manuscript.


  • Aquatic vegetation
  • High resolution imagery
  • Impervious surface
  • Lake clarity
  • Remote sensing


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