  Accurate estimation of Network Performance is crucial for several tasks in
telecom networks. Telecom networks regularly serve a vast number of radio
nodes. Each radio node provides services to end-users in the associated
coverage areas. The task of predicting Network Performance for telecom networks
necessitates considering complex spatio-temporal interactions and incorporating
geospatial information where the radio nodes are deployed. Instead of relying
on historical data alone, our approach augments network historical performance
datasets with satellite imagery data. Our comprehensive experiments, using
real-world data collected from multiple different regions of an operational
network, show that the model is robust and can generalize across different
scenarios. The results indicate that the model, utilizing satellite imagery,
performs very well across the tested regions. Additionally, the model
demonstrates a robust approach to the cold-start problem, offering a promising
alternative for initial performance estimation in newly deployed sites.
