Multi-source system for accurate urban extension detection

Abstract

This paper proposed a novel observation system that is based on multi sources of collected data for urban extension detection. In addition to the satellite image processing, the evolution of unmanned aerial vehicle (UAV) technology created a practical data source for image classification and mapping. For the detected data analysis, storage and processing, a big data framework for urban extension detection was presented. In this Framework, Deep Learning (DL) algorithms were used for the classification and the analysis of multi source images.