Satellite-based assessment of invasive vegetation in Lake Chad Basin, West Africa

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Satellite-based assessment of invasive vegetation in Lake Chad Basin, West Africa

Please use this identifier to cite or link to this item: http://hdl.handle.net/10355/12593

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dc.contributor.advisor Adegoke, Jimmy O. en
dc.contributor.author Aligeti, Naresh, 1984-
dc.coverage.spatial Chad, Lake en
dc.coverage.spatial Africa, West en
dc.date.accessioned 2012-01-31T16:05:44Z
dc.date.available 2012-01-31T16:05:44Z
dc.date.issued 2012-01-31
dc.date.submitted 2011 Fall en
dc.identifier.uri http://hdl.handle.net/10355/12593
dc.description Title from PDF of title page, viewed on January 31, 2012 en
dc.description Thesis advisor: Jimmy O. Adegoke en
dc.description Vita en
dc.description Includes bibliographic references (p. 53-56) en
dc.description Thesis (M.S.)--Dept. of Geosciences. University of Missouri--Kansas City, 2011 en
dc.description.abstract Invasive 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.tableofcontents Overview -- Approaches for identifying invasive species -- Data preparation -- Methodology -- Results and discussion -- Conclusion en
dc.format.extent xiii, 57 pages en
dc.language.iso en_US en_US
dc.publisher University of Missouri--Kansas City en
dc.subject.lcsh Invasive plants en
dc.subject.lcsh Remote-sensing images en
dc.subject.lcsh Typha en
dc.subject.other Thesis -- University of Missouri--Kansas City -- Geosciences en
dc.title Satellite-based assessment of invasive vegetation in Lake Chad Basin, West Africa en_US
dc.type Thesis en_US
MARC.362
thesis.degree.discipline Environmental and Urban Geosciences en
thesis.degree.grantor University of Missouri--Kansas City en
thesis.degree.name Ph.D. en
thesis.degree.level Doctoral en


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