Review of Artificial Intelligence Applications in the Geomatics Field


  • Amal Mahdi Ali University of Baghdad / College of Engineering / Department of Civil Engineering, Baghdad 10071, Iraq


Geomatics, Artificial intelligence (AI), Data processing and analysis, 3D modeling and visualization, Infrastructure design


Artificial intelligence (AI) is rapidly transforming the field of geomatics, which is the science of collecting, managing, and analyzing spatial data. AI is being used to automate tasks, improve accuracy, and enable new applications in geomatics.

One of the most significant impacts of AI in geomatics is in the area of data processing and analysis. AI can be used to automate the processing of large amounts of geospatial data, which can lead to improved accuracy and efficiency in tasks such as land surveying, cartography, and environmental monitoring. For example, AI can be used to identify patterns and trends in data that would be difficult or impossible to detect by human analysts. Another area where AI is having a major impact in geomatics is in 3D modeling and visualization. AI can be used to create 3D models of the real world, which can be used for applications such as urban planning, infrastructure design, and disaster management. For example, AI can be used to create digital twins of cities, which can be used to simulate the impact of different planning decisions. Machine learning is a type of AI that allows computers to learn from data without being explicitly programmed. Machine learning is being used in a variety of geomatics applications, such as image classification, object detection, and natural language processing. For example, machine learning can be used to identify objects in satellite images, such as buildings or roads. Robotics is another area where AI is having a major impact in geomatics. Robots can be used to perform tasks in dangerous or inaccessible environments. They can also be used to collect data in remote areas. For example, robots can be used to survey disaster areas or to collect data in the ocean.

The impact of AI on geomatics is still in its early stages, but it has the potential to be transformative. AI is already being used in a variety of geomatics applications, and its use is only going to increase in the future.


. Ghamisi, P., Rasti, B., Yokoya, N., Wang, Q., Hofle, B., Bruzzone, L., Bovolo, F., Chi, M., Anders, K., Gloaguen, R. and Atkinson, P.M., 2019. Multisource and multitemporal data fusion in remote sensing: A comprehensive review of the state of the art. IEEE Geoscience and Remote Sensing Magazine, 7(1), pp.6-39.

. Jeansoulin, R., 2016. Review of forty years of technological changes in geomatics toward the big data paradigm. ISPRS International Journal of Geo-Information, 5(9), p.155.

. Kersten, T.P., Tschirschwitz, F., Deggim, S. and Lindstaedt, M., 2018. Virtual reality for cultural heritage monuments–from 3D data recording to immersive visualisation. In Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection: 7th International Conference, EuroMed 2018, Nicosia, Cyprus, October 29–November 3, 2018, Proceedings, Part II 7 (pp. 74-83). Springer International Publishing.

. Mithra, S. and Nagamalleswari, T.Y.J., 2022. An analysis of deep learning models for dry land farming applications. Applied Geomatics, pp.1-7.

. Jeansoulin, R., 2016. Review of forty years of technological changes in geomatics toward the big data paradigm. ISPRS International Journal of Geo-Information, 5(9), p.155.

. Fisher, C., 2021. Artificial Intelligence in GIS or “GeoAI”.[Online] Available at: https://www. linkedin. com/pulse/artificial-intelligence-gis-geoai-chase-fisher/(Accessed: 19 August 2023). Suggestion for Citation: Amerudin, S.(2023). Simplifying Automated Building Footprint Extraction with Deep Learning in GIS.

. Nikitas, A., Michalakopoulou, K., Njoya, E.T. and Karampatzakis, D., 2020. Artificial intelligence, transport and the smart city: Definitions and dimensions of a new mobility era. Sustainability, 12(7), p.2789.

. Bordogna, G. and Fugazza, C., 2022. Artificial Intelligence for Multisource Geospatial Information. ISPRS International Journal of Geo-Information, 12(1), p.10.

. Gao, S., 2021. Geospatial artificial intelligence (GeoAI). New York: Oxford University Press.

. Pierdicca, R. and Paolanti, M., 2022. GeoAI: a review of artificial intelligence approaches for the interpretation of complex geomatics data. Geoscientific Instrumentation, Methods and Data Systems, 11(1), pp.195-218.

. Döllner, J., 2020. Geospatial artificial intelligence: potentials of machine learning for 3D point clouds and geospatial digital twins. PFG–Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 88, pp.15-24.

. VoPham, T., Hart, J.E., Laden, F. and Chiang, Y.Y., 2018. Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology. Environmental Health, 17(1), pp.1-6.

. Li, D., Shao, Z. and Zhang, R., 2020. Advances of geo-spatial intelligence at LIESMARS. Geo-spatial Information Science, 23(1), pp.40-51.

. Abid, S.K., Sulaiman, N., Chan, S.W., Nazir, U., Abid, M., Han, H., Ariza-Montes, A. and Vega-Muñoz, A., 2021. Toward an integrated disaster management approach: how artificial intelligence can boost disaster management. Sustainability, 13(22), p.12560.

. Vozenilek, V., 2023. ARTIFICIAL INTELLIGENCE FOR GEOSPATIAL APPLICATIONS. The Routledge Handbook of Geospatial Technologies and Society.

. Bhatti, U.A., Yu, Z., Yuan, L., Zeeshan, Z., Nawaz, S.A., Bhatti, M., Mehmood, A., Ain, Q.U. and Wen, L., 2020. Geometric algebra applications in geospatial artificial intelligence and remote sensing image processing. IEEE Access, 8, pp.155783-155796.

. Haldorai, A., Ramu, A., Murugan, S., Haldorai, A., Ramu, A. and Murugan, S., 2019. Artificial intelligence and machine learning for future urban development. Computing and Communication Systems in Urban Development: A Detailed Perspective, pp.91-113.




How to Cite

Ali, A. M. (2023). Review of Artificial Intelligence Applications in the Geomatics Field. International Journal of Applied Sciences: Current and Future Research Trends, 20(1), 1–12. Retrieved from