Remote sensing AI interpretation technology based on deep learning analyzes the damaged buildings in Gaza during the Palestinian-Israeli Conflict

The recent Palestinian-Israeli conflict has caused serious damage to many buildings in Gaza. In order to better analyze the impact of conflict on Gaza, this paper adopts AI analysis method of multi-source remote sensing data based on improved deep learning. Through accurate analysis and recognition of remote sensing images, detailed information about damaged buildings can be obtained in real time. The application of deep learning technology enables us to accurately locate and measure the losses suffered by Gaza. Compared with traditional manual analysis, deep learning algorithm can efficiently process a large amount of remote sensing data and find the damage degree and type of buildings. The advantage of this deep learning AI analysis method lies in its rapidity and accuracy, which provides us with comprehensive information and helps to estimate losses and make corresponding recovery plans. This information will help policy makers, aid workers and reconstruction agencies to formulate more effective recovery measures and help Gaza return to normal life as soon as possible. We hope that by intelligently analyzing the damage status of buildings in Gaza Strip with multi-source remote sensing images AI, we can provide data support for the peaceful settlement of the Palestinian-Israeli conflict and bring positive changes to local people's lives.