This special session collects papers in the most advanced and trendy areas interested in exploiting new high-performance and distributed computing technologies and algorithms to expedite the processing and analysis of big remote sensing data.
Following the success of the 11th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS 2020), this special issue is to provide an updated snapshot of recent advances in the use of pattern recognition techniques to address the challenges in new-generation remote sensing data.
Recent advances in satellite technology have led to a regular, frequent, and high-resolution monitoring of Earth at the global scale, providing an unprecedented amount of Earth observation (EO) data. This Special Issue aims at gathering a collection of papers in areas interested in learning from data with applications to remote sensing image analysis.
This workshop has established itself as an important event for scientists involved in the combined fields of pattern recognition and remote sensing. These two research fields have always overlapped, but an ever-increasing amount of observations at varying scale, temporal, and spatial resolution provided by a multitude of different sensors require novel advanced algorithms and techniques for automated analysis.