Combining Hyperspectral and Lidar Data for Vegetation Mapping in the Florida Everglades

This study explored a combination of hyperspectral and lidar systems for vegetation mapping in the Florida Everglades. A framework was designed to integrate two remotely sensed datasets and four data processing techniques. Lidar elevation and intensity features were extracted from the original point cloud data to avoid the errors and uncertainties in the raster-based lidar methods. Lidar significantly increased the classification accuracy compared with the application of hyperspectral data alone. Three lidar-derived features (elevation, intensity, and topography) had the same contributions in the classification. A synergy of hyperspectral imagery with all lidar-derived features achieved the best result with an overall accuracy of 86 percent and a Kappa value of 0.82 based on an ensemble analysis of three machine learning classifiers. Ensemble analysis did not signifi cantly increase the classification accuracy, but it provided a complementary uncertainty map for the final classified map. The study shows the promise of the synergy of hyperspectral and lidar systems for mapping complex wetlands.

• Publication year

  2014

• Venue

  Photogrammetric Engineering and Remote Sensing

• Publication date

  2014-08-01

• Fields of study

  Geography, Environmental Science

• Identifiers
  DOI 10.14358/PERS.80.8.733
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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  2014influential reference
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  2013influential reference
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  2012influential reference
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• The Nature of Statistical Learning Theory

  2000cited by this paper
• The Everglades : A perspective on the requirements and applications for vegetation map and database products

  1999cited by this paper
• Mapping the Everglades.

  1999cited by this paper
• Assessing the accuracy of remotely sensed data : principles and practices

  1998cited by this paper
• Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, Second Edition

  1998cited by this paper
• The South Florida Environment: A Region Under Stress

  1996cited by this paper
• Everglades: The Ecosystem and its Restoration.

  1995cited by this paper
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