| dc.description.abstract | Lake Victoria Fisheries Organization and the Ministry of Fisheries collected large
volumes of data on fishery resources from the year 1977 to the year 2008. The data
which had increasingly become voluminous and geographical required a rapid system
of analysis, processing and reporting to supplement their system of analysis. The
developed "Samaki Database" which was in use had limitations in functionalities to
process geographic information and visualization.
The research project involved developing a GIS system that was used to process the
geographic information and enhanced its visualization. This was achieved through
development of a prototype geo-database based on conversion of raster images, georeferencing
base map, digitization, vector modeling and overlay of different datasets
from a created geo-database. The database design involved three stages namely:conceptual,
logical and physical designs.
The system was tested using the data collected from the Ministry of Fisheries, Lake
Victoria Fisheries Organization and other Government Agencies. Data from the
Beaches were aggregated to form Divisional and Districts data reducing data
fragmentation. Retrieval of information was easily achieved through Queries which
gave the same results for both geographical and statistical information. These were in
agreement with the statistics provided by the Fisheries Organizations.
Relationships between the identified Variables i.e. Fish-catch, Fishermen, Hyacinth,
Illegal Nets and Rainfall were tested and confirmed by Pearson's Correlation Index
(SPSS Application).
The developed GIS system would be useful to the Ministry of Fisheries and Lake
Victoria Fisheries Organization (LVFO) in Kenya for storage, retrieval, analysis and
visual display for both geographical and statistical information. The system
performance requirements were minimal i.e. 24MB of RAM and 261 MB of virtual
memory when executing. Strategies were suggested on how to make the system Webbased
and incorporate Mobile Phone technology in data capture. | en |
