Most of spatial data extraction and updating procedures require digitization of geographical entities from satellite imagery. During digitization, errors are introduced by factors like instrument deficiencies or user errors. In this study positional uncertainty of geographical objects, digitized from high resolution Quickbird satellite imagery, is assessed using Data Uncertainty Engine (DUE). It is a software tool for assessing uncertainties in environmental data / and generating realisations of uncertain data for use in uncertainty propagation analyses. A case study area in Kocaeli, Turkey that mostly includes agricultural land parcels is selected in order to evaluate positional uncertainty and obtain uncertainty boundaries for manually digitized fields. Geostatistical evaluation of discrepancy between reference data and digitized polygons are undertaken to analyse auto and cross correlation structures of errors. This process is utilized in order to estimate error model parameters which are employed in defining an uncertainty model within DUE. Error model parameters obtained from training data, are used to generate simulations for test data. Realisations of data derived via Monte Carlo Simulation using DUE, are evaluated to generate uncertainty boundaries for each object guiding user for further analyses with pre-defined information related to the accuracy of spatial entities. It is also aimed to assess area uncertainties affected by the position of spatial entities. For all different correlation structures and object models, weighted average positional error for this study is between 2.66 to 2.91 meters. At the end of uncertainty analysis, deformable object model produced the smallest uncertainty bandwidth by modelling cross correlation.

Spatial Data Analysis (SDA) is relatively narrower and constitutes one of the areas of Spatial Analysis. Geographic Information System (GIS) offers a potentially valuable platform for supporting SDA techniques. Integration of SDA with GIS helps SDA to benefit from the data input, storage, retrieval, data manipulation and display capabilities of GIS. Also, GIS can benefit from SDA techniques in which the integration of these techniques can increase the analysis capabilities of GIS. This integration serves for disseminating and facilitating improved understanding of spatial phenomena. How SDA techniques should be integrated with GIS arise the coupling problem. The complete integration of SDA techniques in GIS can be applied without the support of GIS vendor when the free/libre and open source software (FLOSS) development methodology is properly followed. This approach causes to interpret the coupling problem in a new way. This thesis aims to develop a fully coupled SDA with GIS in FLOSS environment. A fully coupled SDA in free GIS software as FLOSS system is developed by writing nearly 13,000 line Python code in 2.5 years. Usage of this system has reached to nearly 1600 unique visitors, 3000 visits and 8600 page views in two years. As the current status of development in GIS is considered, it is unlikely in commercial market to have full coupled SDA techniques in GIS software. However, it is expected to have more SDA developments in proprietary GIS software in the near future as there is an increasing trend for requesting more sophisticated SDA tools.