We are thrilled to announce the upcoming second edition of the highly anticipated Copernicus Land User Event! Following the success and positive feedback received from last year's event, we couldn't be more excited to bring together industry leaders, experts, and enthusiasts once again.

NASA’s Applied Remote Sensing Training Program (ARSET) has opened a new open, online webinar series: Monitoring Water Quality of Inland Lakes using Remote Sensing. This advanced-level training will focus on using remote sensing observations from Landsat 8 and 9, Sentinel-2, and Sentinel-3 for assessing water quality parameters, including chlorophyll-a concentration, turbidity, and Total Suspended Solids (TSS) in inland lakes. This training will also highlight the importance of in situ measurements of these parameters, coincident with satellite observations, in developing methodologies for operational water quality monitoring.

NASA’s Applied Remote Sensing Training Program (ARSET) has opened a new open, online webinar series: Application of NASA SPoRT-Land Information System (SPoRT-LIS) Soil Moisture Data for Drought. This 3-part webinar series is focused on the introduction of the NASA Land Information System (LIS) output of soil moisture at various depths for drought analysis and monitoring. Examples from operational applications as well as practice exercises (for using LIS data for drought monitoring) will be included in this course. Access to the SPoRT-LIS products via online viewer, in GIS formats, and GIS-based display tools, will also be included. Moreover, self-paced microlessons will be available to help users confirm their understanding and improve their skill via homework lessons between live sessions.

NASA’s Applied Remote Sensing Training Program (ARSET) has opened a new online advanced webinar series: Crop Mapping using Synthetic Aperture Radar (SAR) and Optical Remote Sensing. This three-part training, presented in English and Spanish, is open to the public and builds on previous ARSET agricultural trainings. Here we present more advanced radar remote sensing techniques using polarimetry and a canopy structure dynamic model to monitor crop growth. The training will also cover methods that use machine learning methods to classify crop type using a time series of Sentinel-1 & Sentinel-2 imagery. This series will include practical exercises using the Sentinel Application Platform (SNAP) and Python code written in Python Jupyter Notebooks, a web-based interactive development environment for scientific computing and machine learning.

Copernicus Land User Event - Register now!

European and global land surface applications