One of the DronSe Laboratory’s strengths is its focus on research.

Full list of research activities conducted within the DronSe Lab and published in scientific journals.

  • Colacicco, R., La Salandra, M., Lapietra, I., Refice, A., & Capolongo, D. (2025). Remote sensing techniques to assess badlands dynamics: insights from a systematic review. GIScience & Remote Sensing, 62(1), 2516347, https://doi.org/10.1080/15481603.2025.2516347
  • La Salandra, M., Colacicco, R., Dellino, P., & Capolongo, D. (2025). RivAIrSet: A multitemporal high-resolution UAV imagery dataset for machine learning-based river water segmentation. Data in Brief, 112356, https://doi.org/10.1016/j.dib.2025.112356
  • La Salandra, M., Colacicco, R., Panza, S., Fumai, G., Dellino, P., & Capolongo, D. (2025). RivAIr: A custom-designed UAV-based sensor for real-time water area segmentation and surface velocity estimation. International Journal of Applied Earth Observation and Geoinformation, 142, 104720, https://doi.org/10.1016/j.jag.2025.104720
  • La Salandra, M., Nicotri, S., Donvito, G., Italiano, A., Colacicco, R., Miniello, G., … & Capolongo, D. (2024). A paradigm shift in processing large UAV image datasets for emergency management of natural hazards. International journal of applied earth observation and geoinformation, 132, 103996, https://doi.org/10.1016/j.jag.2024.103996
  • Colacicco, R., La Salandra, M., Refice, A., & Capolongo, D. (2024, July). Exploring the potential of multi-sensor and multi-scale remotely sensed data integration to improve flood monitoring. In IGARSS 2024-2024 IEEE International Geoscience and Remote Sensing Symposium (pp. 3265-3268), https://doi.org/10.1109/IGARSS53475.2024.10640962
  • Colacicco, R., Refice, A., Nutricato, R., Bovenga, F., Caporusso, G., D’Addabbo, A., … & Capolongo, D. (2024). High-Resolution Flood Monitoring Based on Advanced Statistical Modeling of Sentinel-1 Multi-Temporal Stacks. Remote Sensing, 16(2), 294, https://doi.org/10.3390/rs16020294
  • La Salandra, M., Colacicco, R., Dellino, P., & Capolongo, D. (2023). An effective approach for automatic river features extraction using High-Resolution UAV imagery. Drones, 7(2), 70, https://doi.org/10.3390/drones7020070.
  • La Salandra, M., Roseto, R., Mele, D., Dellino, P., & Capolongo, D. (2022). Probabilistic hydro-geomorphological hazard assessment based on UAV-derived high-resolution topographic data: The case of Basento river (Southern Italy). Science of The Total Environment, 842, 156736, https://doi.org/10.1016/j.scitotenv.2022.156736
  • Miniello, G., La Salandra, M., & Vino, G. (2022, July). Deep Neural Networks for Remote Sensing Image Classification. In Science and Information Conference (pp. 117-128). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-10464-0_9
  • La Salandra, M., Miniello, G., Nicotri, S., Italiano, A., Donvito, G., Maggi, G., Dellino, P., & Capolongo, D. (2021). Generating UAV high-resolution topographic data within a FOSS photogrammetric workflow using high-performance computing clusters. International Journal of Applied Earth Observation and Geoinformation, 105, 102600, https://doi.org/10.1016/j.jag.2021.102600
  • Miniello, G., & La Salandra, M. (2021, October). A new method for geomorphological studies and land cover classification using Machine Learning techniques. In Proceedings of the International Symposium on Grids & Clouds. https://pos.sissa.it/378/031/pdf
  • Miniello, G., & La Salandra, M. (2021, September). A new method for geomorphological studies on aerial images and land-cover classification using machine learning techniques. In Image and Signal Processing for Remote Sensing XXVII (Vol. 11862, pp. 52-59). SPIE. https://doi.org/10.1117/12.2593110
  • Miniello, G., & La Salandra, M. (2021). HIGH RESOLUTION IMAGE PROCESSING AND LAND COVER CLASSIFICATION FOR HYDRO-GEOMORPHOLOGICAL HIGH-RISK AREA MONITORING. CEUR Workshop Proceedings, 3041, pp. 304 – 309. https://ceur-ws.org/Vol-3041/304-309-paper-56.pdf