News

TC Webinar - ESI

VEDA: An Open, Interoperable Platform for Open Science

This presentation will demonstrate the VEDA system’s practical use, focusing on visualizing and analyzing NASA’s earth science data, navigating its STAC, and leveraging its open-source features for analysis and visualization. Speakers: Brian Freitag, Slesa Adhikari

GRSS, AP-S and MTT-S explore new possibilities with partnership

As the partnership with IEEE Geoscience and Remote Sensing Society (GRSS), IEEE Antennas and Propagation Society (AP-S) and IEEE Microwave Theory and Techniques Society (MTT-S) continues this year, Maci and Carvalho expressed in an interview with GRSS their optimism in the outcome of this collaboration.

IADF-TC

Multi-Sensor Anomalous Change Detection: a New Paradigm for Rapid Change Detection in Remote Sensing Imagery

Combining multiple satellite remote sensing sources can provide a far richer, more frequent view of the earth than that of any single source; the challenge is in distilling this large volume of heterogeneous sensor imagery into meaningful characterizations of the imaged areas. This talk will present recent research in this area, discuss what worked and what didn’t work, and highlight opportunities for future research directions by the community.

REACT-TC Webinar

EO4SDG Mini Projects and Earth at Risk Image Contest 2023 Award Ceremony

We are delighted to announce the joint award ceremony of the second edition of EO4SDG Mini-projects, and the Earth at Risk image contest organized by the IEEE Geoscience and Remote Sensing Society. The winners of the two competitions will get the chance to present their proposals and talk about the stories behind their outstanding EO data images followed by a Q&A session.

TC Webinar

Geospatial AI for Monitoring Food Security and Climate Resilient Agriculture

Amid the rising food insecurity and climate challenges, there is a need for some urgent and crucial, coordinated actions. In this session, we will be focusing on these two different sub-saharan countries where we used geospatial data along with our pre-trained models (unsupervised and supervised models) to identify agricultural activity and, type of crops grown and estimate the yields for the crop of interest.