Shoreline mapping, determination of
itsdeterioration and bathymetry overtime resulting
from the socio-economic activities are of high
importance. Satellite remote sensing offers an
alternative to conventional topographic mapping and
hydrographic surveys for measuring the extent of Land
Use-Land cover changes and water depth, with the
advantage of low cost and large area coverage. The use
of multi –spectral image of Spot-5 and Landsat ETM7+
with high resolution provides possibility for shoreline
variation and bathymetry mapping. This study mapped
and analyzed variations along the Eagle Island
Shoreline from the year 1986 to 2015 using Landsat
ETM-7+ and Spot-5 imageries. The images were preprocessed and classified using ENVI 4.5 software and
ArcGIS 10.0 software, while Surfer 10.0 was used for
the 3-D modeling of the Echo sounding in situ
measurement. The Midas Echo sounder was used for in
situ measurement of the depth of the study area. The
result showed a shoreline decrease of 1000 square
meters from 2,745,000 square meters in 1986 to
1,457,731 square meters in 2015. The area occupied by
water body decreased from 594,900 square meters to
440,918.75 square meters that’s an increase of 400,000
square meters that is 40%, the built-up area increased
from 1,001,700 square meters in 1986 to 1,401,575
square meters in 2015. The lengths of the shoreline for
the various years were found to be 3.761 kilometer in
1986, 3.832 kilometers in 2000, and 3.743 kilometers in
2015, showing a decrease of 18m in 30 years. The study
demonstrated the relevance of satellite imagery in
mapping shoreline changes and the use of echo
sounding technique in determining depth useful for
navigational decision making. Regular shoreline
mapping is recommended to avoid costly structure
placement along shorelines, shoreline mapping aids in
better boundary definition among communities near
shorelines, and better-quality images free of cloud cover
and haze would allow for a more accurate assessment of
bathymetry, potentially removing the majority of error
affecting classification methods, according to the study
