Using machine learning to build safer cities
In eThekwini, researchers have harnessed machine learning and satellite data to spot the city's most landslide-prone zones. A new study published in Scientific Reports has found that urban development activities, including road construction, property development and vegetation loss, are significantly increasing landslide susceptibility across parts of eThekwini.
Key Takeaways
- In eThekwini, researchers have harnessed machine learning and satellite data to spot the city's most landslide-prone zones.
- A new study published in Scientific Reports has found that urban development activities, including road construction, property development and vegetation loss, are significantly increasing landslide susceptibility across parts of eThekwini.
- Full details and original dispatch available below.
In eThekwini, researchers have harnessed machine learning and satellite data to spot the city's most landslide-prone zones. A new study published in Scientific Reports has found that urban development activities, including road construction, property development and vegetation loss, are significantly increasing landslide susceptibility across parts of eThekwini.
Original Publisher Attribution
This summary was curated from Phys.org.