AI for Coastal Erosion Monitoring
The use of satellite and LiDAR data to monitor coastal line dynamics, analyze sand transport, assess the effectiveness of shore reinforcements, create storm scenarios, and plan adaptation strategies is becoming increasingly prevalent.
Coastal erosion poses a significant challenge for coastal regions, particularly in the context of climate change and rising sea levels. AI assists in monitoring changes, predicting risks, and planning adaptive measures.
Infrastructure Assessment in High-Risk Zones
Evaluating the effectiveness of coastal defenses.
Predicting the impact of erosion on infrastructure assets.
Drone Imagery for Local Monitoring
Meteorological data (wind, waves, storms).
Weather conditions and clouds can affect the quality of satellite data.
Frequently asked questions
What types of data are required? A minimum: satellite?
A minimum set of data includes multispectral satellite imagery, topographic data. Additional data can include LiDAR data, meteorological records, and storm event information.
How much does implementation cost? Is it based on the amount spent?
The cost of implementation varies depending on scale: satellite data costs between $5,000 and $50,000 per year, LiDAR costs between $20,000 and $200,000, and the analysis system costs between $30,000 and $150,000. ROI is achieved through reduced losses.
How can measurement accuracy be ensured? What should be done?
High-resolution satellite data, calibration using LiDAR data, consideration of tidal fluctuations, and regular verification of accuracy are all crucial for ensuring precise measurements.
Can the system be integrated with other systems??
Yes, through APIs, data can be integrated with GIS systems, planning systems, environmental monitoring systems, and citizen portals.
▶ Try it live
Everything above runs in your browser — open Earthquake Wave Propagation Simulation and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.