Integrated Analysis of Satellite and Geological Data to Characterize Ground Deformation in the Area of Bologna (Northern Italy) Using a Cluster Analysis-Based Approach
Abstract
1. Introduction
2. Materials and Methods
2.1. Geological Framework
2.2. Study Area
- “Area 1” focuses on the Metropolitan City of Bologna characterized by numerous industrial activities, a strong water production and a specific geological framework. It has been analyzed by numerous studies regarding the overall trend of ground deformation, focusing on the city of Bologna, which has been affected by intensive subsidence related to groundwater exploitation, e.g., [31,32,33].
- “Area 2” is located to the NE of Bologna and is characterized by a low concentration of urban areas and industrial activities, and by negligeable water production, suggesting a stable condition.
- “Area 3”, in between, shows poor and scattered urban and industrial areas, numerous widespread water production wells with average production volume, and is marked by the presence of a UGS system. It represents a transition zone with superimposed effects from superficial aquifer exploitation and deep subsurface operations.
2.3. Datasets
- Land use maps from the geoportal of Regione Emilia-Romagna;
- Ground movement surveys:
- Groundwater production volumes (in 106 m3/yr) in the time frame 2016–2018, and well positions;
- Well use: for agricultural, civil, and industrial purposes;
- piezometric data measurements publicly available on the Open Data portal of ARPAE (Agenzia Prevenzione Ambiente Energia Emilia-Romagna);
- Geological data collected from technical literature and the geoportal of Regione Emilia-Romagna:
- Geological cross-sections;
- Hydrodynamic aquifer parametrization.
2.4. P-SBAS DInSAR
2.5. Seasonal and Trend Decomposition Using Loess
2.6. Cluster Analysis—K-Means
2.7. Methodology
- The relative P-SBAS DInSAR vertical measurements were compared with the GNSS absolute vertical measurements from the “BOLG00ITA” station located close to the city of Bologna (Figure 3);
- P-SBAS DInSAR vertical time-series were processed through STL and successive cluster analysis on seasonal and trend components using the methodology developed by [18];
- The behavior and magnitude of the identified clusters (where a cluster groups objects based on the similarity of some shared properties or features [41]) were compared with both groundwater production and UGS information;
- The geological framework of the superficial aquifers from [4] was further investigated for the specific area under analysis and, together with the general geological framework of the Po Plain, they were related to the phenomena identified by the cluster analysis output.
3. Results
3.1. Analyses of Ground Movement Survey Data: P-SBAS DInSAR and GNSS
3.2. Analyses of Seasonal and Trend Behavior of Ground Movements: Regional Scale
3.3. Analyses of Seasonal and Trend Behavior of Ground Movements: Local Scale
3.3.1. Area 1
3.3.2. Area 2
3.3.3. Area 3
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
ARPAE | Agenzia Prevenzione Ambiente Energia Emlia-Romagna |
CNR-IREA | National Research Council—Institute for the Electromagnetic Sensing of the Environment |
DInSAR | Diferential Interferometry Synthetic Aperture Radar |
EPN | EUREF Permanent Network |
EUREF | Regional Reference Frame Sub-Commission for Europe |
GIS | Geographic Information Systems |
GNSS | Global Navigation Satellite Systems |
INGV | Istituto Nazionale di Geofisica e Vulcanologia |
IWS | Interferometric Wide Swath |
LOS | Line of Sight |
MP | Measuring point |
NE | North East |
NW | North West |
P-SBAS | Parallel Computing Small BAseline Subset |
SAR | Synthetic Aperture Radar |
SBAS | Small BAseline Subset |
STL | Seasonal and Trend decomposition by Loess |
UGS | Underground Gas Storage |
Appendix A
Appendix A.1
Appendix A.2
Appendix A.3
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Category | Extended Area | Area 1 | Area 2 | Area 3 |
---|---|---|---|---|
Agricultural and green areas | 81.6 | 61.5 | 88.8 | 86.0 |
Urban areas | 10.5 | 21.4 | 6.2 | 6.9 |
Industrial areas | 2.5 | 6.0 | 0.6 | 1.3 |
Road and railway networks | 2.8 | 7.4 | 1.2 | 1.5 |
Others | 2.6 | 3.7 | 3.2 | 4.4 |
Covered Area (km × km) | Number of Measuring Points (MPs) | MPs Density (MP/km2) | Grid Spatial Resolution (m × m) | Satellite | Processing Algorithm | Time Frame |
---|---|---|---|---|---|---|
1850 | 223,311 | 121 | 40 × 30 | Sentinel 1 | Parallel SBAS Interferometry Chain (*) | June–2016 October–2021 |
Azimuth Multilook Factor (Pixels) | Range Multilook Factor (Pixels) | Maximum Temporal Baseline (Days) | Maximum Spatial Baseline (m) | Temporal Coherence Threshold |
---|---|---|---|---|
5 | 20 | 360 | 200 | 0.85 |
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Navarro, A.M.G.; Eid, C.; Rocca, V.; Benetatos, C.; De Luca, C.; Onorato, G.; Lanari, R. Integrated Analysis of Satellite and Geological Data to Characterize Ground Deformation in the Area of Bologna (Northern Italy) Using a Cluster Analysis-Based Approach. Remote Sens. 2025, 17, 2645. https://doi.org/10.3390/rs17152645
Navarro AMG, Eid C, Rocca V, Benetatos C, De Luca C, Onorato G, Lanari R. Integrated Analysis of Satellite and Geological Data to Characterize Ground Deformation in the Area of Bologna (Northern Italy) Using a Cluster Analysis-Based Approach. Remote Sensing. 2025; 17(15):2645. https://doi.org/10.3390/rs17152645
Chicago/Turabian StyleNavarro, Alberto Manuel Garcia, Celine Eid, Vera Rocca, Christoforos Benetatos, Claudio De Luca, Giovanni Onorato, and Riccardo Lanari. 2025. "Integrated Analysis of Satellite and Geological Data to Characterize Ground Deformation in the Area of Bologna (Northern Italy) Using a Cluster Analysis-Based Approach" Remote Sensing 17, no. 15: 2645. https://doi.org/10.3390/rs17152645
APA StyleNavarro, A. M. G., Eid, C., Rocca, V., Benetatos, C., De Luca, C., Onorato, G., & Lanari, R. (2025). Integrated Analysis of Satellite and Geological Data to Characterize Ground Deformation in the Area of Bologna (Northern Italy) Using a Cluster Analysis-Based Approach. Remote Sensing, 17(15), 2645. https://doi.org/10.3390/rs17152645