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Using Advanced Land Imager (ALI) and Landsat Thematic Mapper (TM) for the detection of the invasive shrub Lonicera maackii in southwestern Ohio forests

Lawlor, Sarah E.
http://rave.ohiolink.edu/etdc/view?acc_num=miami1303831778

Abstract Details

2011, Master of Arts, Miami University, Geography.
Lonicera maackii, an understory invasive shrub, has an extended leaf phenology that can be detected with remote sensing in the fall when the canopy is leafless and the shrub’s leaves are still green. The purpose of this research was to compare how accurately image data from the Advanced Land Imager (ALI) sensor vs. Landsat Thematic Mapper (TM) identify L. maackii. Point intercept sampling was used to quantify L. maackii in 20 woodlots in two counties in southwestern Ohio. Spectral Vegetation Indices (SVIs) were applied to both images for each plot. Field estimated percent cover was regressed on values for each SVI per image to determine the best predictor of L. maackii cover. Cover of L. maackii was better explained by Landsat TM regressions than ALI. TM image results suggest that the ALI image was acquired too late seasonally to accurately detect the invasive shrub. The analysis did not clearly assess ALI for this research.
Mary Henry, PhD (Advisor)
David Gorchov, PhD (Committee Member)
Jerry Green, PhD (Committee Member)
35 p.
Geographic Information Science; Geography; Physical Geography; Remote Sensing
Advanced Land Imager; Landsat Thematic Mapper; Lonicera maackii, invasive species

Recommended Citations

Citations

  • Lawlor, S. E. (2011). Using Advanced Land Imager (ALI) and Landsat Thematic Mapper (TM) for the detection of the invasive shrub Lonicera maackii in southwestern Ohio forests [Master's thesis, Miami University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=miami1303831778

    APA Style (7th edition)

  • Lawlor, Sarah. Using Advanced Land Imager (ALI) and Landsat Thematic Mapper (TM) for the detection of the invasive shrub Lonicera maackii in southwestern Ohio forests. 2011. Miami University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=miami1303831778.

    MLA Style (8th edition)

  • Lawlor, Sarah. "Using Advanced Land Imager (ALI) and Landsat Thematic Mapper (TM) for the detection of the invasive shrub Lonicera maackii in southwestern Ohio forests." Master's thesis, Miami University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=miami1303831778

    Chicago Manual of Style (17th edition)

miami1303831778
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© 2011, all rights reserved.
This open access ETD is published by Miami University and OhioLINK.