Satellite Data and Changing Shorelines: Observing Environmental Dynamics in Lake Urmia

Water bodies are among the most dynamic elements of natural landscapes. Lakes and reservoirs constantly change under the influence of climate variability, hydrological processes, and human activity. When water levels fluctuate, shorelines shift, ecosystems adapt, and the surrounding landscape gradually transforms. For this reason, monitoring water dynamics has become an important part of environmental research.

Modern remote sensing technologies have significantly expanded our ability to observe these processes. The growing availability of open satellite data makes it possible to analyse environmental change across large areas and over long time periods. In my experience, access to these datasets has fundamentally changed how we approach environmental analysis, making it possible to work with time series and large territories in ways that were not feasible before.

In my work in geospatial analysis, I focus on how satellite data can be used to study water bodies and shoreline dynamics. One of the main challenges I often encounter when working with optical satellite imagery is cloud contamination. Even small amounts of cloud cover can obscure large parts of the Earth's surface and reduce the reliability of environmental analysis.

To address this issue, I developed a workflow that combines Sentinel-2 Surface Reflectance imagery with the Sentinel-2 Cloud Probability dataset. In practice, this approach allows me to generate cleaner image composites that are more suitable for further analysis.

Most of the data processing is carried out using Google Earth Engine, a cloud-based platform designed for large-scale geospatial analysis. By using scripts, I am able to automate key steps of the workflow, including filtering satellite imagery, masking clouds, and generating image composites. For spatial analysis and map visualisation I also use QGIS.

As a practical example, I applied this approach to analyse shoreline changes in Lake Urmia. Located in northwestern Iran, Lake Urmia has experienced significant fluctuations in water extent over the past decades. From my perspective, this case clearly illustrates how environmental change can be observed through satellite data and how these changes reflect broader processes related to climate and water management.

By processing satellite imagery from different years, it becomes possible to observe how the lake’s surface area changes and how the shoreline shifts over time. What I find particularly important is that such visualisations make environmental change more tangible and easier to communicate, not only within the scientific community but also to a wider audience.

To visualise these results, I created an interactive web map that allows users to explore the changes in the lake’s water surface: Lake Urmia Web Map

I also prepared a short video demonstrating the satellite data workflow and the process of monitoring water bodies:

Projects like this make me reflect on a broader question: as satellite data becomes increasingly accessible, how can we use these tools not only to observe environmental change, but also to better support environmental decision-making and public awareness?

In my view, even relatively simple geospatial workflows can reveal long-term environmental trends that might otherwise remain unnoticed. Expanding the use of these approaches could help bridge the gap between technical analysis and real-world environmental challenges.

About the Author

Ayazhan Karabayeva is a GIS and Earth Observation specialist with a Master’s degree in geospatial technologies. Her work focuses on satellite imagery analysis and spatial data processing for studying environmental processes and landscape change.