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Geospatial technologies are rapidly becoming adopted by advocates of human rights abuses, engaged in non-governmental monitoring. Limited available funding puts constraints on the amount of time staff can perform Geographic Information System (GIS) and remote-sensing tasks. Therefore, semi-automated techniques are forthcoming in order to facilitate data-analysis tasks aimed at sharing information about violent conflict and human rights abuses. As a contribution to these efforts, this paper details classification of a pre-conflict image, binary partitioning of the classification results, application of morphological filters, estimation of total number of pre-conflict structures and overlay of the refined information onto the post-conflict image for damage assessment in Darfur, Sudan. We present a novel application of geospatial technologies and image-processing techniques aimed at expediting the dissemination of critical information necessary to inform the public and policy makers of detailed multi-temporal analyses of evidence of human rights abuses.
Sulik et al. (Thu,) studied this question.