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Classification of mature Australian pines (Casuarina equisetifolia) using LIDAR data in Broward County, Florida

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Date Issued:
2003
Summary:
The development of high resolution LIDAR DSM combined with digital infrared ortho-photography data enhances the ability to map canopy structures with a higher degree of accuracy and precision than with either data set alone. The purpose of this thesis is to map Australian Pine (Casuarina equisetifolia with a 85% or greater accuracy by creating a methodology that uses LIDAR and color infrared ortho-photography and to test it within three different landscape types within Broward County. LIDAR features below a determined height threshold (i.e. Deerpoint 25 ft) were eliminated and recoded to 0 to create Mask 1. NDVI technique separated non-vegetative features from vegetative features to create Mask 2. Mask 1 and Mask 2 were merged and overlaid on the raw LIDAR data set to perform isodata clustering, as well as density slicing to identify mature Australian Pines. Careful delineation of study areas is critical to obtain the highest possible accuracy. Density slicing proved to be a faster and less time consuming technique for achieving 85% level of accuracy than compared to isodata clustering.
Title: Classification of mature Australian pines (Casuarina equisetifolia) using LIDAR data in Broward County, Florida.
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Name(s): Zumbado, Jennifer M.
Florida Atlantic University, Degree Grantor
Roberts, Charles, Thesis Advisor
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 2003
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 101 p.
Language(s): English
Summary: The development of high resolution LIDAR DSM combined with digital infrared ortho-photography data enhances the ability to map canopy structures with a higher degree of accuracy and precision than with either data set alone. The purpose of this thesis is to map Australian Pine (Casuarina equisetifolia with a 85% or greater accuracy by creating a methodology that uses LIDAR and color infrared ortho-photography and to test it within three different landscape types within Broward County. LIDAR features below a determined height threshold (i.e. Deerpoint 25 ft) were eliminated and recoded to 0 to create Mask 1. NDVI technique separated non-vegetative features from vegetative features to create Mask 2. Mask 1 and Mask 2 were merged and overlaid on the raw LIDAR data set to perform isodata clustering, as well as density slicing to identify mature Australian Pines. Careful delineation of study areas is critical to obtain the highest possible accuracy. Density slicing proved to be a faster and less time consuming technique for achieving 85% level of accuracy than compared to isodata clustering.
Identifier: 9780496219308 (isbn), 13092 (digitool), FADT13092 (IID), fau:9956 (fedora)
Note(s): Thesis (M.S.)--Florida Atlantic University, 2003.
Subject(s): Casuarina--Florida--Broward County
Aerial photography in forestry
Ecology--Remote sensing
Aerial photogrammetry
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/13092
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.