M.Sc in Space Sciences (with Specialization in Geoinformatics and GIS Applications)

This Space Science course consists of: Geoinformatics, Geostatistics, Remote Sensing Applications, Security and Defense GIS Applications, Spatial Data Structures. Land-use/Land-cover Applications, Geometric and Physical Geodesy, Cartographic Techiniques and Space-Based Vector Diseases Mapping.

Geoinformatics: Relational Database Design: Normalization and implementation; Object – oriented Database Design and Implementation; Building of Topographic Information System; topographic database, data requirements, design steps and implementation.

Geo-statistics: Probability and statistical distributions, binomial, decision making; central limit theorem; hypothesis testing – t-test, z-test, f-test, kolmogoro-Smirnov, v-test, Krusklwallid analysis of variance, correlation analysis: Pearson product moment, Spearman’s rank and Kendall rank correlation analysis and sample linear regression.

Remote Sensing Applications: Electromagnetic spectrum, remote sensors aircraft and spacecraft remote sensing systems. Landsat, NigeriaSat satellites system data. Atmospheric error in remotely sensed data. Reflection, spectral characteristics of objects; vegetation, soil, water. Analysis of data; qualitative and quantitative. Statistical properties of digital data. Pattern recognition. Digital image classification supervised and un-supervised methods. Mathematical algorithms for image classification duster analysis, maximum likelihood, separating hyper planes. Cartographic accuracy of digital satellite imagery. Comparison of Landsat, NigeriaSat and spot satellites digital image reflection. Computer supported production of thematic maps.

Security and Defense GIS Applications: Security and Defense applications in GIS: Theory and field application of Geographical Information Systems. Historical perspectives of the development of GIS. The role of remote sensing and computer cartography. Definition, scope and nature of GIS structure, data acquisition and output, data and formats; Vector and raster structure systems, digitization systems and computer.

Spatial Data Structures: Data modelling: definition, purpose, components, methodology, raster and vector data models. Raster and quad tree data structures. Spatial relationships, emergence of database technology, different views of the database, architecture. Database design: relational, network, hierarchical and binary relationship models. Database query and manipulation. Distributed databases. Arc-node topology, using a database linking spatial and attribute information. Producing maps. GIS functionality: point-and line-in-polygon, buffering, overlays. Implementation details and exercises using PC Arc/Info and Oracle.

Land Use/ Land Cover Applications: Land Use/ land Cover applications in GIS: Theory and field application of Geographical Information Systems. Historical perspectives of the development of GIS. The role of remote sensing and computer cartography. Definition, scope and nature of GIS structure, data acquisition and output, data and formats; Vector and raster structure systems, digitization systems and computer.

Geometric and Physical Geodesy: Geometric and Physical Geodesy; Best Transformation. Geometric Methods of Satellite Geodesy. The Earth’s external gravity field and the figure of the earth. The boundary value problem of physical geodesy. The problem of the geoid, regularized and actual geoid. Reduction to the geoid. Direct determination of the physical surface of the earth. Astrogeodetic, gravimetric and Astrogravimetric methods of geoid determination.

Cartographic Techniques: Techniques of map making; Basic drawing materials and equipment; Cartographic data collections and analysis; Map projections; Cartography design and presentation; Map reduction techniques; Introduction to digital cartography.

Space-Based Vector Diseases Mapping: Space-Based Vector Diseases Mapping: Overview of the utility of GIS and remote sensing for mapping landscape dynamics. Basic knowledge in GIS, geospatial analysis and field mapping. GIS map making, visualization and analysis of point (field) data in GIS and extracting remote sensing variables for land productivity and water dynamics mapping. Geographical Information Systems (GIS) and remote sensing will be used to map landscape dynamics related to vector occurrences.