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dc.contributor.advisorAdegoke, Jimmy O.en
dc.contributor.authorAligeti, Naresh, 1984-
dc.coverage.spatialChad, Lakeen
dc.coverage.spatialAfrica, Westen
dc.date.issued2012-01-31
dc.date.submitted2011 Fallen
dc.descriptionTitle from PDF of title page, viewed on January 31, 2012en
dc.descriptionThesis advisor: Jimmy O. Adegokeen
dc.descriptionVitaen
dc.descriptionIncludes bibliographic references (p. 53-56)en
dc.descriptionThesis (M.S.)--Dept. of Geosciences. University of Missouri--Kansas City, 2011en
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.en_US
dc.description.tableofcontentsOverview -- Approaches for identifying invasive species -- Data preparation -- Methodology -- Results and discussion -- Conclusionen
dc.format.extentxiii, 57 pagesen
dc.identifier.urihttp://hdl.handle.net/10355/12593
dc.publisherUniversity of Missouri--Kansas Cityen
dc.subject.lcshInvasive plantsen
dc.subject.lcshRemote-sensing imagesen
dc.subject.lcshTyphaen
dc.subject.otherThesis -- University of Missouri--Kansas City -- Geosciencesen
dc.titleSatellite-based assessment of invasive vegetation in Lake Chad Basin, West Africaen_US
dc.typeThesisen_US
thesis.degree.disciplineGeoscienceseng
thesis.degree.grantorUniversity of Missouri--Kansas Cityen
thesis.degree.levelDoctoralen
thesis.degree.namePh.D.en


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