Comparison of IKONOS Derived Vegetation Index and LiDAR Derived Canopy Height Model for Grassland Management. Metadata

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Title

  • Main Title Comparison of IKONOS Derived Vegetation Index and LiDAR Derived Canopy Height Model for Grassland Management.

Creator

  • Author: Parker, Gary
    Creator Type: Personal

Contributor

  • Chair: Dong, Pinliang
    Contributor Type: Personal
    Contributor Info: Major Professor
  • Committee Member: Hunter, Bruce
    Contributor Type: Personal
  • Committee Member: Tiwari, Chetan
    Contributor Type: Personal

Publisher

  • Name: University of North Texas
    Place of Publication: Denton, Texas

Date

  • Creation: 2009-12

Language

  • English

Description

  • Content Description: Forest encroachment is understood to be the main reason for prairie grassland decline across the United States. In Texas and Oklahoma, juniper has been highlighted as particularly opportunistic. This study assesses the usefulness of three remote sensing techniques to aid in locating the areas of juniper encroachment for the LBJ Grasslands in Decatur, Texas. An object based classification was performed in eCognition and final accuracy assessments placed the overall accuracy at 94%, a significant improvement over traditional pixel based methods. Image biomass was estimated using normalized difference vegetation index (NDVI) for 1 meter resolution IKONOS winter images. A high correlation between the sum of NDVI for tree objects and field tree biomass was determined where R = 0.72, suggesting NDVI sum of a tree area is plausible. However, issues with NDVI saturation and regression produced unrealistically high biomass estimates for large NDVI. Canopy height model (CHM) derived from 3-5m LiDAR data did not perform as well. LiDAR typically used for digital elevation model (DEM) production was acquired for the CHM and produced correlations of R = 0.26. This suggests an inability for this particular dataset to identify juniper trees. When points that registered a tree height where correlated with field values, an R = 0.5 was found, suggesting denser point spacing would be necessary for this type of LiDAR data. Further refining of the methods used in this study could yield such information as the amount of juniper tree for a given location, fuel loads for prescribed burns and better information for the best approach to remove the juniper and ultimately management juniper encroachment into grasslands.

Subject

  • Keyword: LiDAR
  • Keyword: encroachment
  • Keyword: grasslands
  • Keyword: juniper
  • Keyword: remote sensing
  • Keyword: CHM
  • Keyword: NDVI
  • Library of Congress Subject Headings: Eastern redcedar -- Texas -- Lyndon B. Johnson National Grassland.
  • Library of Congress Subject Headings: Junipers -- Texas -- Lyndon B. Johnson National Grassland.
  • Library of Congress Subject Headings: Grassland ecology -- Texas -- Lyndon B. Johnson National Grassland.
  • Library of Congress Subject Headings: Grassland conservation -- Texas -- Lyndon B. Johnson National Grassland.
  • Library of Congress Subject Headings: Lyndon B. Johnson National Grassland (Tex.)
  • Library of Congress Subject Headings: Optical radar -- Texas -- Lyndon B. Johnson National Grassland.

Collection

  • Name: UNT Theses and Dissertations
    Code: UNTETD

Institution

  • Name: UNT Libraries
    Code: UNT

Rights

  • Rights Access: public
  • Rights License: copyright
  • Rights Holder: Parker, Gary
  • Rights Statement: Copyright is held by the author, unless otherwise noted. All rights reserved.

Resource Type

  • Thesis or Dissertation

Format

  • Text

Identifier

  • OCLC: 606556043
  • UNT Catalog No.: b3826307
  • Archival Resource Key: ark:/67531/metadc12179

Degree

  • Degree Name: Master of Science
  • Degree Level: Master's
  • Degree Discipline: Applied Geography
  • Academic Department: Department of Geography
  • Degree Grantor: University of North Texas

Note