Identify quality checking parameters which can be considered in a routine quality checking and develop models of QC model based on ArcGIS Data review and FME and presents comparison results between these two models in terms of accuracy, speed and efficiency.

To compare various image classification method coupled with a surface model to extract road data in terms of quality (mainly accuracy and completion). The aim of the study is to give the most accurate geospatial analysis model that can be used in road data updating. The model should cater for shadows, tree crown cover, flyovers, bridges, interchanges, tunnels etc..

To compare various image classification method coupled with a surface model to extract building data in terms of quality (mainly accuracy and completion). The aim of the study is to give the most accurate geospatial analysis model that can be used in building data updating. The model shall classify extracted buildings into various building classes such as warehouses, multi-story commercial buildings, residential buildings etc. as may deem necessary.

To study monitoring high rising buildings and major structures using InSAR data to assess their shifts and settlement over time periods.

Using OpenStreetMap to enrich existing Geospatial database in Dubai Municipality. Research and develop tools to download QC and ingest data from OSM.

In this study models for machine learning applied to image classification to aid in change detection and extraction of vector data regarding roads, buildings and green vegetation surfaces for spatial data updating.