Events

Artificial Intelligence (AI) for Earth Observation (EO) is largely an interdisciplinary field. The lecture presents selected topics of AI algorithms specific for EO encompassing: orbit, mission, sensor networks, intelligent agents, communication, coding, signal processing, machine learning, deep learning, data indexing, data bases, network theories, simulation, modeling, inverse problem, model assimilation, or parameters retrieval.

This webinar will present an overview of NASA's Earth science data system and its shift from supporting Open data to Open science. The webinar will also provide examples of activities and tool development currently underway that support this shift to Open science.

In this presentation, analysis of data the first three years of ROHP operations are presented. The ROHP calibration has been performed using data co-located with independent information from the NASA/JAXA Global Precipitation Mission (GPM) precipitation products and ionospheric activity. For a PRO observation, the induced cross polarization represents a cumulative effect from aspherical hydrometeors encountered anywhere along the propagation path. Analysis of ROHP data exhibit not only depolarization from the liquid phase (oblate-shaped rain) precipitation hydrometeors, but also positive differential phase signatures into and well above the freezing level, indicating possible sensitivity to frozen hydrometeors and the cloud vertical structure. These findings suggest the use of PRO data for evaluating of the representation of convection precipitation and moisture in global weather and climate models.

In this session we will explore some latest EO technologies and applications, and share the lessons learned from the previous efforts of technology transfer and engineering implementation, then address the issues from technology to solutions, further we discuss the idea to establish an operational application solutions pool for EO community.