dc.contributor.author | Aketch, Newton D | |
dc.date.accessioned | 2023-12-05T06:13:14Z | |
dc.date.available | 2023-12-05T06:13:14Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | http://erepository.uonbi.ac.ke/handle/11295/164195 | |
dc.description.abstract | Coastal zones are the epicenter of economic activities in most developing countries in the world hence
are bound to change. With advancement in technology monitoring such degradation has become
critical subject for scientific research. This study reports a remarkable shoreline change; an aftermath
of hydrodynamic effects and human influence on the Kenyan coastline. The sequential accumulation
of sediments on Kenya North coast over the past three decades (1990-2021) using Remote sensing
and GIS is tracked. Literature on this chronological evolution and its impacts along this coastline is
meagre; it is therefore anticipated that the outcome of this study will initiate an elaborate probe into
circumstances that contributed to landscape change along this coast. Multispectral Landsat and
Sentinel-2 images respectively, display a prograding beach along Mto Tamamba Delta (Kenyan
North Coast) a consequence of coastal erosion. These change in coastal morphology poses a threat
to marine ecosystems, riparian communities and tourism industry. Prior reports indicate that research
work done along this coastline were by field survey. This study is aimed at monitoring coastal
erosion and accretion using satellite sensors. To achieve these, coastline data for these years were
drawn numerically with the aid of RS and Arc GIS on ENVI 5.3 software. Maximum likelihood
and Spectral angular mapper algorithms were used to classify the images due to their threshold
input ability that ensures optimum classification results. Time series methodology on classified
endmembers was then used to infer the presence of erosion and accretion. Using the image subset
technique, areas prone to erosion and accretion within the coastal datum were identified and cut.
The patterns of spatiotemporal trend of these endmembers were effectively employed to
corroborate these findings. To explain reasons for change, time series analysis and confusion
matrix were used. Change in distribution of endmembers over the 31 years’ period was assessed
using thematic change technique; an approach not previously applied in this study area. From the
classified Mto Tamamba image, the pixel coverage area for each endmember was extracted. The
regression analysis from class statistics obtained from Mto Tamamba area for bare land and water
showed a correlation with R2 =0.5138 with a P-value ˂ 0.005 on Landsat data. On the other hand,
Sentinel-2 classified image a correlation of R2= 0.7857 for the same endmembers. Validation using
field campaign data gave an overall accuracy of 84% and kappa coefficient of 0.799 for Landsat
while for sentinel-2 an overall accuracy of 88% and Kappa coefficient of 0.849. The fact that
validation of resampled classified Landsat image using a higher spatial resolution satellite
(Sentinel-2) gave a better result of 92% implies that adoption of higher resolution data as validation
process can aid in assessing impact of resolution on classification results. | en_US |
dc.language.iso | en | en_US |
dc.publisher | University of Nairobi | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | Remote sensing, Landsat, Coastal evolution, Accretion, Erosion, GIS, Monitoring. | en_US |
dc.title | Monitoring Evolution of Coastline Along Mto Tamamba Delta in Kenya North Coast Using Satellite Images | en_US |
dc.type | Thesis | en_US |