This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License Newcastle University ePrints -eprint.ncl.ac.uk Hameed M, Fairbairn D, Speak S. Determining the potential role of VGI in improving land administration systems in Iraq.

Abstract:The article explores the process of Volunteered Geographic Information (VGI) collection by assessing the relative usability and accuracy of a range of different methods (smartphone GPS, tablet, and analogue maps) for data collection among different demographic and educational groups, and in different geographical contexts within a study area. Assessments are made of positional accuracy, completeness, and the experiences of citizen data collectors with reference to the official cadastral data and the land administration system. Ownership data were validated by crowd agreement. The outcomes of this research show the varying effects of volunteers, data collection method, geographical area, and application field, on geospatial data handling in the VGI arena. An overview of the many issues affecting the development and implementation of VGI projects is included. These are focused on the specific example of VGI data handling presented here: a case study area where instability and lack of resources are found alongside strong communities and a pressing need for more robust and effective official structures. The chosen example relates to the administration of land in an area of Iraq.

Recently, the advancement of remote sensing technology played a key role in urban land/cover mapping, planning, tourism, and environmental management. Images with a high spatial resolution for urban classification are widely used. Despite the high spectral resolution of the image, spectral confusion happens among different land covers. Furthermore, the shadow problem also causes poor results in the classification based on traditional per-pixel spectral approaches. This study looks at ways of improving the classification of urban land cover using QuickBird images. Maximum likelihood (ML) pixel-based supervised as well as Rule-based object-based approaches were examined on high-resolution QuickBird satellite images in Karbala City, Iraq. This study indicates that the use of textural attributes during the rule-based classification procedure can significantly improve land-use classification performance. Furthermore, the results show that rule-based results are highly effective in improving classification accuracy than pixel-based. The results of this study provide further clarity and insight into the implementation of using the object-based approach with various classifiers for the extended study. In addition, the finding demonstrated the integration of high-resolution QuickBird data and a set of attributes derived from the visible bands and geometric rule set resulted in superior class separability, thus higher classification accuracies in mapping complex urban environments.