Multi-dimensional geospatial data integration for coastal change analysis

R. Li, S. Deshpande, X. Niu, I. C. Lee, B. Wu

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

Coastal change analysis, particularly of the variation in shorelines and blufflines, is critical for coastal disaster mitigation, environmental protection, resource management, and coastal development decision making. As data from a variety of sources has become more easily available, it is highly desirable to investigate a strategy for the integration of multi-dimensional geospatial data for coastal mapping and change analysis. This paper summarizes an investigation of techniques for integrating satellite images, aerial images, and LiDAR data for high precision coastal mapping. The integration of IKONOS and QuickBird satellite stereo image pairs with aerial images for shoreline mapping and the integration of LiDAR data and aerial orthoimages for coastal bluffline extraction are both examined. Experiments using data collected at Tampa Bay, Florida, and Lake Erie, Ohio, have shown that sub-meter measurement accuracy can be achieved through these integration strategies. Using improved mapping products based on these new techniques, bluffline erosion analysis was conducted at Lake Erie near Painesville, Ohio, and correlations between bluffline recessions and various geological and meteorological factors were examined.

Original languageEnglish (US)
Pages (from-to)1311-1316
Number of pages6
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume37
StatePublished - 2008
Event21st International Congress for Photogrammetry and Remote Sensing, ISPRS 2008 - Beijing, China
Duration: Jul 3 2008Jul 11 2008

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Geography, Planning and Development

Fingerprint

Dive into the research topics of 'Multi-dimensional geospatial data integration for coastal change analysis'. Together they form a unique fingerprint.

Cite this