<p>Urban environments present unique challenges for geospatial data management and analysis due to their complexity and dynamic nature. In this paper, we introduce GeoMarX, a new tool designed to empower <b>geo</b>spatial <b>mar</b>king and annotation of comple<b>x</b> targets in urban environments. The complex targets in this context are high-level concepts composed of simpler spatial elements, such as urban informal settlements, rather than basic objects like buildings or trees. GeoMarX addresses the need for precise marking and annotation by providing a user-friendly platform equipped with integrated mapping functionalities and annotation tools as well as leveraging cutting-edge machine learning technologies, which enables users to accurately mark specific points/areas of interest and annotate them with rich contextual information to further facilitate efficient data management and decision-making processes in urban planning, transportation management, environmental monitoring, and other urban-related domains. We illustrate the utility of GeoMarX through a case study of the marking and annotation of urban informal settlements, highlighting its effectiveness in enhancing geospatial data analysis and visualization in complex urban contexts. Overall, GeoMarX represents a valuable resource for researchers, practitioners, and policymakers seeking to harness the power of geospatial data for informed decision-making and sustainable urban development. The software and accompanying documentation are available at <a href="https://github.com/rui-research/GeoMarX">https://github.com/rui-research/GeoMarX</a>.</p>