Application of multispectral Sentinel-2 images for Geo-environmental terrain classification mapping based on landforms: an example of the Campo de Cartagena, SE Spain

The terrain classification through Terrain Mapping Units (TMU) consists of the definition of homogeneous relief units that integrate different aspects of the natural environment (geology, geomorphology, drainage, land use, vegetation, etc.), providing a solid basis for multidisciplinary studies focused on aspects such as mining, geotechnics, natural hazard analysis and environmental assessment, among others. This approach may be of particular interest in countries that lack a comprehensive geological and geomorphological mapping infrastructure, providing a basic characterization of their main geographical, geological and environmental characteristics. Currently, the wide variety of available remote sensing products constitutes an advantage when tackling this type of cartography.

The main goal of this study is to evaluate the usefulness of freely available remote sensing products, accessible online on a global scale, for producing TMUs. To achieve this goal, a combined analysis of several remote sensing products was addressed for the Campo de Cartagena (SE Spain), a semi-arid and heavily anthropized area including the Mar Menor lagoon, the Neogene and Quaternary detrital deposits from the Campo de Cartagena plain and the surrounding mountain ranges, formed by Palaeozoic, Permian and Triassic metamorphic rocks.

Remote sensing products used are: (1) a digital elevation model – DEM with spatial resolution of 30 m, derived from the Shuttle Radar Topography Mission (SRTM, NASA), and (2) a multispectral Sentinel-2 dataset, with spatial resolutions of 10 and 20 m. On this basis, two different spatial resolution TMU maps were developed and compared to test their different capabilities for mapping purposes: (1) based on the 30 m spatial scale DEM and Sentinel-2 bands at 20 m spatial resolution, and (2) based on the 30 m spatial scale DEM and the Sentinel-2 bands at 10 m spatial resolution. Processing the DEM using a Geographic Information System – GIS resulted in hillshade, slope and flow accumulation models, which were used to characterise the main topographic features. In addition, the combination of different spectral bands and the application of digital image processing techniques enabled the identification of differences in surface composition. Based on these observations, homogeneous TMUs were delineated according to three main criteria: (1) relief, (2) drainage network and (3) surface composition variability. Accuracy analysis and validation were implemented by field-work observations and by comparing the resulting terrain classification map with the already existing geological and geomorphological maps at 1:50000 scale from the Spanish Geological Survey (IGME). This study highlights the potential of freely available remote sensing products, accessible online on a global scale for mapping TMUs in an area affected by intense agricultural and mining activities.

Acknowledgements: Research Project PID2023-150229OB-100 (HYPERLANDFORM) financed by MICIU/AEI/10.13039/501100011033 and by FEDER, UE. The participation of Inés Pereira was supported by an FPU (FPU21/04495) contract from the Spanish Ministry of Universities.