More than a satellite image – a mini-interview on the potential of spaceborne remote sensing
Spaceborne remote sensing means much more than just a few spectacular satellite images: we can track decades of changes, regularly examine vast areas, and access data more and more easily. We talked with Dr. Dániel Kristóf, Head of the Space Remote Sensing Department at Lechner and the Hungarian delegate to the European Space Agency's (ESA) Earth Observation Programme Board, about how this vast amount of knowledge can be used in practice, how satellite observation opportunities are developing, and what kind of change artificial intelligence can bring.
What is the one thing most people don’t know about space-based remote sensing?
In fact, it can be stated that Europe possesses one of the world's most advanced Earth observation systems. The Sentinel satellites of the Copernicus program, along with upcoming developments in the years ahead, provide world-class capabilities for continuous monitoring of the Earth's surface. A key factor driving its significance is that we do not work with isolated snapshots; the satellites continuously collect data, capturing new imagery of the same area every few days. This allows us not only to record a specific state but also to monitor changes and track long-term processes. Furthermore, Copernicus imagery is freely available and accessible to everyone; however, properly analyzing and interpreting the data still requires specialized expertise
In which areas does space-based remote sensing offer the greatest added value today?
Spaceborne remote sensing can be compared to radiology: it helps in establishing a 'diagnosis'—providing a picture of current or even past conditions—but determining the underlying causes of the observed phenomena and deciding on the required intervention remains the responsibility of the domian-specific field. We can contribute to this process through geospatial and temporal analyses.
It provides significant added value in areas such as agriculture, environmental protection, and construction, where various remote sensing methods can be used to examine the Earth's surface and the processes taking place there. The data obtained in this manner also plays an important role in decision support, enabling decisions that are firmly grounded in observations and measurements, and even allowing us to re-evaluate our previous assumptions.It is particularly valuable that time-series datasets spanning several decades are also available to us. Imagery from the Landsat satellites, for instance, has enabled the investigation of long-term processes since the 1970s, making it possible to track land-use change or the spatial expansion of specific phenomena.
How have the capabilities of spaceborne remote sensing changed the most over the past ten years?
In recent years, the capabilities of satellite observation have expanded significantly. Sensors are increasingly available across a wider range of spectral bands and spatial resolutions, and in the coming years, new satellites will surpass the capabilities of current systems even further. For instance, more precise monitoring in the thermal infrared range could bring breakthroughs in examining soil temperature and drought, while L-band radar can penetrate deeper into the surface, thereby providing more information on soil moisture conditions.
Regarding satellite imagery, achieving the highest possible spatial resolution is often considered the primary benchmark of development, yet this is not everything—in fact, for many applications, it is not even the most critical feature. While targeted imaging can produce highly detailed images, continuous Earth observation generates data across vast areas simultaneously. For a satellite acquiring data over a swath that is up to several hundred kilometers wide, a massive volume of data must be recorded, stored, and transmitted; therefore, a different balance must be struck here between level of detail and regular, large-scale observation.
A significant change has also occurred in data accessibility and processing. Continuously updated imagery is becoming more widely available, while the barrier to entry for its utilization has significantly decreased. Artificial intelligence could accelerate this even further, helping to perform complex analytics that previously required deep remote sensing expertise.
What will be one of the most exciting questions in this field at the International Spatial Data Conference 2026?
For me, one of the most exciting questions is how artificial intelligence will transform the utilization of spaceborne remote sensing data. In recent years, the barrier to entry has significantly decreased: while previously expensive, hard-to-access software and serious expertise were required, today we can work with freely available satellite imagery, open-source software, and cloud-based processing.
Artificial intelligence can accelerate this process further: it can make analytics more accessible to users who are not remote sensing experts, and provide complex support for processing the available data. Information that previously required highly specialized knowledge can thus become accessible to an increasingly broader audience. However, this does not automatically guarantee that these data and analytics will actually be integrated into decision-making. In my view, one of the most critical questions will be precisely how we can translate this technological capability and accessibility into real, practical utility.