Recent research published in ‘Open Geosciences’ has unveiled critical insights into landslide susceptibility in Smederevo, Serbia, with significant implications for agricultural practices in the region. The study, led by Deđanski Vojislav from the Faculty of Geography at the University of Belgrade, employed advanced Geographic Information System (GIS) techniques to assess areas at risk of landslides, a natural hazard that poses substantial threats to both property and human safety.
Landslides are particularly prevalent in valleys near major rivers, and the right bank of the Danube River in Smederevo has been identified as especially vulnerable. The research highlights that approximately 4% of the city’s territory, equating to around 19.3 km², is classified as highly or very highly susceptible to landslides. This susceptibility is influenced by a combination of natural conditions and human activities, necessitating a comprehensive understanding of the landscape for effective risk management.
The study’s methodology involved creating a geospatial database and generating thematic maps that illustrate various factors contributing to landslide risk. By utilizing the Best-Worst Method (BWM) to assign weight coefficients to these factors, researchers developed a Landslide Susceptibility Index (LSI). The high predictive power of the model, indicated by a receiver operating characteristic-area under the curve value close to one, underscores the reliability of the findings.
For the agriculture sector, these insights are invaluable. Farmers and agricultural planners can leverage this data to make informed decisions about land use and crop selection, particularly in areas identified as having a high risk of landslides. By avoiding planting in the most susceptible zones, farmers can mitigate the risk of crop loss and ensure more sustainable agricultural practices.
Moreover, the research empowers policymakers to implement effective environmental protection measures. By understanding the geographic distribution of landslide susceptibility, local governments can prioritize areas for intervention, such as reforestation or the construction of retaining walls, which can help stabilize slopes and protect agricultural land.
This study represents a pioneering effort to integrate remote sensing techniques with interdisciplinary research to provide a deeper understanding of landslide dynamics in Smederevo. As agriculture increasingly faces challenges from climate change and natural disasters, such innovative approaches are essential for developing resilient farming strategies.
In summary, the findings from this research not only enhance our understanding of landslide risks but also open up new opportunities for the agricultural sector in Smederevo. By utilizing the insights gained from this study, farmers can better navigate the challenges posed by natural hazards, ultimately leading to more sustainable and productive agricultural practices.