2026-09-03 –, Conference Management Room1
This study analyzes multi decadal spatiotemporal land cover change in Dammam, Saudi Arabia (1986–2025) to establish a green infrastructure baseline. An open source data, Landsat and Sentinel-2 data classified using Random Forest in QGIS reveal urban expansion patterns and support greening priority planning using NDVI and NDBI.
The rapid expansion of metropolitan areas in arid regions necessitates a sophisticated approach to environmental management and urban planning. Dammam, the primary administrative and industrial hub of Saudi Arabia’s Eastern Province, has undergone significant transformation over the past four decades. As the city generates substantial solid waste, estimated between 20000 and 35000 m³ per month, maintaining a balance between built-up infrastructure and ecological health has become a central priority for local authorities. In these hyper-arid climates, urban vegetation is vital for improving air quality and elevating overall livability. However, rapid development and climatic stress frequently reduce the available green cover, requiring proactive monitoring and strategic intervention.
To address these environmental challenges, the Kingdom has established a comprehensive regulatory and strategic framework under Saudi Vision 2030 and the Saudi Green Initiative. These national objectives, supported by the MAWAN Vision 2040, emphasize the integration of advanced technology to ensure sustainable land use and environmental protection.
Remote sensing provides a powerful longitudinal tool for monitoring these complex urban dynamics across varying scales, especially open-source geospatial tools and data that play a crucial role in advancing accessible spatial analysis. The continuous archives of the Landsat mission, including Landsat 5, 7, 8, and 9, offer an unparalleled 40-year record of land cover changes. This allows for the tracking of urban footprints through indices like the Normalized Difference Built-up Index. and the Normalized Difference Vegetation Index.
This study presents a multi-scale assessment of Dammam’s evolution from 1986 to 2025 by fusing decadal spatiotemporal analysis with high-precision baseline mapping. By implementing a Random Forest classification for four distinct land classes, which include Vegetation, Built-up, Water, and Barren land, and integrating sub-meter vegetation inventories, this research provides a comprehensive evidence base for environmental enforcement and greening strategy. The resulting neighborhood-level analytical profiles and Greening Priority Index offer a specialized framework for municipal resource allocation, directly supporting the Kingdom’s mandate for a resilient and sustainable urban future.
The long-term analysis of the Dammam metropolitan landscape between 1986 and 2025 reveals a significant imbalance between rapid urban expansion and the growth of green infrastructure. Across the three study areas, urban development has progressed much faster than vegetation expansion, creating increasing ecological pressure. Area 1 experienced rapid residential growth after 2016, resulting in a large gap between built-up land and vegetation. Area 3 shows similar patterns driven by industrial expansion, where infrastructure development far exceeded the establishment of green spaces. In contrast, Area 2 highlights the gradual loss of traditional agricultural landscapes due to continuous urban encroachment.
The MCDA analysis indicates that roadside corridors and residential areas are the most suitable locations for greening interventions across the study areas. Prioritizing vegetation in these spaces can maximize environmental benefits while directly improving the quality of everyday urban life. these findings indicate that urban growth has occurred with limited ecological compensation, emphasizing the urgent need for more strategic and integrated urban greening policies to support sustainable metropolitan development.
QGIS and Copernicus Data Space
I make my conference contribution available under the CC BY 4.0 license. The conference contribution comprises the abstract, the text contribution for the conference proceedings, the presentation materials as well as the video recording and live transmission of the presentation:Dr. Sultan Al Sultan, leading an era of open-source Geospatial Technology Software in Saudi Arabia, Tokyo Institute of Technology PhD, a senior researcher at NASA, USGS, and has been a researcher in JAXA, RESTEC-Japan. he graduate from MIT Massachusetts Institute of Technology, and previously from George Washington University, USA. He represented Univeristy Space Engineering Consortium (UNISEC) for Saudi Arabia Universities. He is Saudi Arabia Parliament Member 2013-2017. Today he is the Founder and CEO of Environmental Remote Sensing Lab (TECRS-Lab).