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Remote Sensing for Detecting and Mapping Flowering Rush: A Case Study in the Ottawa National Wildlife Refuge (ONWR), Ohio

Droog, Arisca
http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1349900740

Abstract Details

2012, Master of Science (MS), Bowling Green State University, Geology.
Predicting and mapping invasive wetland plant species is an important process for future management decisions and strategies. Controlling and mapping such plant species requires robust methods that are applicable at different ecological scales to map and monitor their spread. In particular, this study tested the feasibility of classification tree analysis (CTA) by using a high resolution Applanix 439 Digital Sensor System (DSS) aerial imagery (< 20 cm) and linear spectral unmixing (LSU) analysis by using Landsat Thematic Mapper (TM) data to produce different distribution maps of invasive flowering rush (Butomus umbellatus L.) potential in the Ottawa National Wildlife Refuge (ONWR) wetlands, in Northwest Ohio. The classification accuracy from CTA maps derived from different splitting rules was evaluated by kappa statistics. The overall accuracy within the different runs varied between 35 to 56 % while the “Gini” splitting rule had the best performance. The endmembers from the best CTA performing map were utilized by the LSU method for estimating sub-pixel endmember fractions at a broader geographical scale. The results derived from the aerial imagery were slightly better than those from the Landsat imagery, as the goodness of fit between the flowering rush fraction map and the data measured in the field was lower. This study was intended to demonstrate the potential for flowering rush mapping over larger area using knowledge developed from smaller geographical scale using high resolution imagery. Results indicate that both methods show promising results for the prediction of flowering rush, but additional research that encompass different field data collection techniques, datasets of imagery and modeling methods need to be explored.
Peter Gorsevski (Advisor)
Helen Michaels (Committee Member)
Enrique Gomezdelcampo (Committee Member)
Remote Sensing
Flowering Rush; Invasive Plants Species; Linear Spectral Umixing; Classification Tree Analysis; Aerial Imagery; Landsat TM Imagery; Remote Sensing;

Recommended Citations

Citations

  • Droog, A. (2012). Remote Sensing for Detecting and Mapping Flowering Rush: A Case Study in the Ottawa National Wildlife Refuge (ONWR), Ohio [Master's thesis, Bowling Green State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1349900740

    APA Style (7th edition)

  • Droog, Arisca. Remote Sensing for Detecting and Mapping Flowering Rush: A Case Study in the Ottawa National Wildlife Refuge (ONWR), Ohio. 2012. Bowling Green State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1349900740.

    MLA Style (8th edition)

  • Droog, Arisca. "Remote Sensing for Detecting and Mapping Flowering Rush: A Case Study in the Ottawa National Wildlife Refuge (ONWR), Ohio." Master's thesis, Bowling Green State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1349900740

    Chicago Manual of Style (17th edition)

bgsu1349900740
1,434
© 2012, all rights reserved.
This open access ETD is published by Bowling Green State University and OhioLINK.
Release 3.2.12