Towards deep probabilistic graph neural network for natural gas leak detection and localization without labeled anomaly data

Deep learning has been widely applied to automated leakage detection and location of natural gas pipe networks. Prevalent deep learning approaches do not consider the spatial dependency of sensors, which limits leakage detection performance. Graph deep learning is a promising alternative to prevailing approaches as it can model spatial...

Development of spectral-phenological features for deep learning to understand Spartina alterniflora invasion

Invasive Spartina alterniflora (S. alterniflora), a native riparian species in the U.S. Gulf of Mexico, has led to serious degradation to the ecosystem and biodiversity as well as economic losses since it was introduced to China in 1979. Although multi-temporal remote sensing offers unique capability to monitor S. alterniflora over large...

The application model of 3D cadastre in practical registration for real estate in China

Since the introduction of the concept of 3D cadastre, a great many of significant research results have been done. To promote the development of 3D cadatre, 3D cadastre working group sponsored by International Federation Surveyors (FIG) commissions 3 and 7 was organized by Delft University of Technology in 2001. This working group provides a...