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Mapping Elaeagnus Umbellata on Coal Surface Mines using Multitemporal Landsat Imagery

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dc.contributor.authorOliphant, Adam J.en
dc.contributor.committeechairWynne, Randolph H.en
dc.contributor.committeechairZipper, Carl E.en
dc.contributor.committeememberFord, W. Marken
dc.contributor.departmentForest Resources and Environmental Conservationen
dc.date.accessioned2017-02-22T07:00:45Zen
dc.date.available2017-02-22T07:00:45Zen
dc.date.issued2015-08-31en
dc.description.abstractInvasive plant species threaten native plant communities and inhibit efforts to restore disturbed landscapes. Surface coal mines in the Appalachian Mountains are some of the most disturbed landscapes in North America. Moreover, there is not a comprehensive understanding of the land cover characteristics of post- mined lands in Appalachia. Better information on mined lands' vegetative cover and ecosystem recovery status is necessary for implementation of effective environmental management practices. The invasive autumn olive (Elaeagnus umbellata) is abundant on former coal surface mines, often outcompeting native trees due to its faster growth rate. The frequent revisit time and spatial and spectral resolution of Landsat satellites make Landsat imagery well suited for mapping and characterizing land cover and forest recovery on former coal surface mines. I performed a multitemporal classification using a random forest analysis to map autumn olive on former and current surface coal mines in southwest Virginia. Imagery from the Operational Land Imager on Landsat 8 were used as input data for the study. Calibration and validation data for use in model development were obtained using high-resolution aerial imagery. Results indicate that autumn olive cover is sufficiently dense to enable detection using Landsat imagery on approximately 12.6% of the current and former surface coal mines located in the study area that have been mined since the early 1980s. The classified map produced here had a user's and producer's accuracy of 85.3% and 78.6% respectively for the autumn olive coverage class. Overall accuracy in reference to an independent validation dataset was 96.8%. These results indicate that autumn olive growing on reclaimed coal mines in Virginia and elsewhere in the Appalachian coalfields can be mapped using Landsat imagery. Additionally, autumn olive occurrence is a significant landscape feature on former surface coal mines in the Virginia coalfields.en
dc.description.degreeMaster of Scienceen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:5473en
dc.identifier.urihttp://hdl.handle.net/10919/75119en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectAfforestationen
dc.subjectEcosystem Recoveryen
dc.subjectLandsaten
dc.subjectLand Cover Changeen
dc.subjectAlien Plantsen
dc.subjectExotic Plantsen
dc.subjectInvasive Plantsen
dc.titleMapping Elaeagnus Umbellata on Coal Surface Mines using Multitemporal Landsat Imageryen
dc.typeThesisen
thesis.degree.disciplineForestryen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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