Spatiotemporal analysis of impervious surface areas on the watersheds of Kaduna Metropolitan Area (PDF)
(Sprache: Englisch)
Master's Thesis from the year 2014 in the subject Geography / Earth Science - Demographics, Urban Management, Planning, Birkbeck, University of London, language: English, abstract: The thesis is the first attempt of mapping impervious surface that offers a...
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Master's Thesis from the year 2014 in the subject Geography / Earth Science - Demographics, Urban Management, Planning, Birkbeck, University of London, language: English, abstract: The thesis is the first attempt of mapping impervious surface that offers a very simple and visual understanding of the health status of the watersheds within Kaduna metropolitan area. It examined the spatiotemporal growth of impervious surface areas in Kaduna metropolitan area, Nigeria in relation to the watersheds using the SAVI differencing approach. A supervised maximum likelihood algorithm was used to classify image derived from the SAVI differencing approach, for the time periods. A random sampling scheme was conducted to complete an accuracy assessment of the classification.
Results from the watershed categorization indicate it took 36 years to establish the first degraded watershed, this is from 1973 to 2009, going by the prediction in the analysis, it will take less years, i.e. 20 years to establish the next degraded watershed in the study area. This study demonstrates the feasibility of mapping and categorizing watersheds associated with impervious surface areas, through the combination of remote sensing data (LANDSAT and ASTER) with the help of a GIS software (ArcGIS).
Results from the watershed categorization indicate it took 36 years to establish the first degraded watershed, this is from 1973 to 2009, going by the prediction in the analysis, it will take less years, i.e. 20 years to establish the next degraded watershed in the study area. This study demonstrates the feasibility of mapping and categorizing watersheds associated with impervious surface areas, through the combination of remote sensing data (LANDSAT and ASTER) with the help of a GIS software (ArcGIS).
Bibliographische Angaben
- Autor: Asadullah Muhammad
- 2020, 73 Seiten, Englisch
- Verlag: GRIN Verlag
- ISBN-10: 3346109615
- ISBN-13: 9783346109613
- Erscheinungsdatum: 07.02.2020
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
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Englisch
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