The Influence of Constantinople on Middle Byzantine Architecture (843-1204) : A typological and morphological approach at the provincial level.

The influence of the architecture of the Byzantine capital spread to the Mediterranean provinces with travelling masters and architects. In this study the architecture of the Constantinopolitan School has been detected on the basis of the typology of churches, completed by certain morphological aspects when necessary. The impact of the Constantinopolitan workshops appears to have been more important than previously realized. This research revealed that the Constantinopolitan composite domed inscribed-cross type or cross-in-square spread everywhere to the Balkans and it was assumed soon by the local schools of architecture. In addition, two novel variants were invented on the basis of this model: the semi-composite type and the so-called Athonite type. In the latter variant lateral conches, choroi, were added for liturgical reasons. Instead, the origin of the domed ambulatory church was partly provincial. One result of this study is that the origin of the Middle Byzantine domed octagonal types was traced to Constantinople. This is attested on the basis of the archaeological evidence. Also some other architectural elements that have not been preserved in the destroyed capital have survived at the provincial level: the domed hexagonal type, the multi-domed superstructure, the pseudo-octagon and the narthex known as the lite. The Constantinopolitan architecture during the period in question was based on the Early Christian and Late Antique forms, practices and innovations and this also emerges at the provincial level.

Digital elevation model error in terrain analysis

Digital elevation models (DEMs) have been an important topic in geography and surveying sciences for decades due to their geomorphological importance as the reference surface for gravita-tion-driven material flow, as well as the wide range of uses and applications. When DEM is used in terrain analysis, for example in automatic drainage basin delineation, errors of the model collect in the analysis results. Investigation of this phenomenon is known as error propagation analysis, which has a direct influence on the decision-making process based on interpretations and applications of terrain analysis. Additionally, it may have an indirect influence on data acquisition and the DEM generation. The focus of the thesis was on the fine toposcale DEMs, which are typically represented in a 5-50m grid and used in the application scale 1:10 000-1:50 000. The thesis presents a three-step framework for investigating error propagation in DEM-based terrain analysis. The framework includes methods for visualising the morphological gross errors of DEMs, exploring the statistical and spatial characteristics of the DEM error, making analytical and simulation-based error propagation analysis and interpreting the error propagation analysis results. The DEM error model was built using geostatistical methods. The results show that appropriate and exhaustive reporting of various aspects of fine toposcale DEM error is a complex task. This is due to the high number of outliers in the error distribution and morphological gross errors, which are detectable with presented visualisation methods. In ad-dition, the use of global characterisation of DEM error is a gross generalisation of reality due to the small extent of the areas in which the decision of stationarity is not violated. This was shown using exhaustive high-quality reference DEM based on airborne laser scanning and local semivariogram analysis. The error propagation analysis revealed that, as expected, an increase in the DEM vertical error will increase the error in surface derivatives. However, contrary to expectations, the spatial au-tocorrelation of the model appears to have varying effects on the error propagation analysis depend-ing on the application. The use of a spatially uncorrelated DEM error model has been considered as a 'worst-case scenario', but this opinion is now challenged because none of the DEM derivatives investigated in the study had maximum variation with spatially uncorrelated random error. Sig-nificant performance improvement was achieved in simulation-based error propagation analysis by applying process convolution in generating realisations of the DEM error model. In addition, typology of uncertainty in drainage basin delineations is presented.