Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.Environmental monitoring and management systems in most cases deal with models and
spatial analytics that involve the integration of in-situ and remote sensor observations. In-situ
sensor observations and those gathered by remote sensors are usually provided by different databases and services in real-time dynamic service systems like the Geo-Web Services. Thus,
data have to be pulled from different databases and transferred over the web before they are
fused and processed on the service middleware. This process is very massive and unnecessary
communication and work load on the service, especially when retrieving massive raster
coverage data. Thus in this research, we propose a database model for heterogeneous sensortypes
that enables geo-scientific processing and spatial analytics involving remote and in-situ
sensor observations at the database level of the Sensor Observation Service, SOS. This
approach would be used to reduce communication and massive workload on the Geospatial
Web Service, as well make query request from the user end a lot more flexible. Hence the
challenging task is to develop a heterogeneous sensor database model that enables geoprocessing
and spatial analytics at the database level and how this could be integrated with the
geo-web services to reduce communication and workload on the service and as well make
query request from the client end more flexible through the use of SQL statements
