21-23 October 2021 | Hyderabad
3-day Summer School
Artificial Intelligence in Remote Sensing Applications
In Collaboration with
Remote sensing has long been a primary source of geospatial data. Many national and global scale applications in natural resource inventory and management, climate change, environmental and urban monitoring, agriculture, flood prediction etc., have been operationally developed and deployed. Matching with developments in miniaturized sensors, aerial vehicles (e.g. drones), a host of remote sensors offering high quality multispectral, hyperspectral, and SAR images are routinely available. Thanks to the launch of constellations of high spatial-spectral-temporal resolution, remote sensing satellites (e.g. Sentinel series), the daily accumulated remote sensing data far exceeds the typical limits of big data. Therefore, the classical approaches and algorithms used for remote sensing processing and analysis are grossly insufficient and call for a great degree of automation in the processing, analysis, and application developments. In recent years, Artificial intelligence (AI) has advanced at a breakneck pace, approaching or surpassing human capabilities in areas like computer vision, natural language processing etc. Coupled with the recent developments in ‘spatial’ data handling algorithms in AI and ML-based architectures, there has been a paradigm shift in the way remote sensing data has been processed - leading to automated-predictive analytics based remote sensing data processing and application development.
Composed with the right blend of crisp sessions on theoretical frameworks and hands-on training, this School aims at equipping the participants with a fair degree of overview and practical knowledge on various remote sensing application developments using advanced AI and ML approaches. In addition, this School is an excellent venue for networking students, young professionals, and faculty members with renowned practicing experts in multidisciplinary remote sensing research.