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dc.contributor.advisorAdegoke, Jimmy O.eng
dc.contributor.authorAligeti, Naresh, 1984-eng
dc.coverage.spatialChad, Lakeeng
dc.coverage.spatialAfrica, Westeng
dc.date.issued2012-01-31eng
dc.date.submitted2011 Falleng
dc.descriptionTitle from PDF of title page, viewed on January 31, 2012eng
dc.descriptionThesis advisor: Jimmy O. Adegokeeng
dc.descriptionVitaeng
dc.descriptionIncludes bibliographic references (p. 53-56)eng
dc.descriptionThesis (M.S.)--Dept. of Geosciences. University of Missouri--Kansas City, 2011eng
dc.description.abstractInvasive plants are a huge threat not only to the biological integrity of the world's natural ecosystems but also the economies that are supported by those ecosystems. Today, governments worldwide are spending millions of dollars to address this issue. Invasive species pose great danger to the natural habitat, sometimes causing irreversible change. Typha australis - an aquatic weed locally known as ―Kachalla‖ in the Lake Chad Basin (LCB) is an example of an invasive species of major concern. This study presents a method to identify and characterize this weed on a large scale using medium resolution LANDSAT, MODIS satellite imagery and high resolution QUICKBIRD satellite imagery. The satellite imagery was augmented with ground truth data obtained during field work in the LCB by a UMKC team of scientists and students in 2009. Land Use Land Change (LULC) classification was carried out using Landsat and MODIS Imagery. Normalized Difference Vegetation Index (NDVI) was generated for every year from 2000 to 2010 on MOD13GQ and for every month in 2009. MOD13GQ is a product of MODIS. Simultaneously, a Quickbird satellite image was used to more accurately track the weed using 500 meter buffered GPS points collected during field work in the LCB. The resultant classification was then overlaid on Landsat and MODIS Imagery to randomly pick signature points of the weed and to train the software for classification. Supervised classification was done on both of the images, accuracy assessment was conducted and statistics were generated respectively. The end result is a classified medium resolution LULC map of the LCB and a high resolution map of a subset area of the LCB with a well defined LULC category that we could identify, with reasonable certainty, as an invasive species category.eng
dc.description.tableofcontentsOverview -- Approaches for identifying invasive species -- Data preparation -- Methodology -- Results and discussion -- Conclusioneng
dc.format.extentxiii, 57 pageseng
dc.identifier.urihttp://hdl.handle.net/10355/12593eng
dc.publisherUniversity of Missouri--Kansas Cityeng
dc.subject.lcshInvasive plantseng
dc.subject.lcshRemote-sensing imageseng
dc.subject.lcshTyphaeng
dc.subject.otherThesis -- University of Missouri--Kansas City -- Geoscienceseng
dc.titleSatellite-based assessment of invasive vegetation in Lake Chad Basin, West Africaeng
dc.typeThesiseng
thesis.degree.disciplineGeosciences (UMKC)eng
thesis.degree.grantorUniversity of Missouri--Kansas Cityeng
thesis.degree.levelDoctoraleng
thesis.degree.namePh.D.eng


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