Sign up to save your podcasts
Or
Share NASA ARSET NISAR Data Access and Tools Session 2-3
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
NASA ARSET NISAR Data Access and Tools Session 2-3
Welcome to Sessions 2 & 3 of our specialized series on next-generation radar data: "NASA ARSET: NISAR Data Access and Tools - Session 2_3."
In this advanced double-session episode of the NASA Live Video Podcast, we shift our focus from the theoretical parameters of radar science to the actual infrastructure built for retrieving and processing cloud-free planetary data. The upcoming NISAR (NASA-ISRO Synthetic Aperture Radar) mission is set to generate an unprecedented volume of high-resolution L-band and S-band SAR data, making it essential for researchers worldwide to master the specialized data pipelines and cloud architectures designed to handle it.
Through the framework of NASA’s Applied Remote Sensing Training (ARSET) program, we provide a hands-on guide to navigating the primary data portals and open-access toolkits developed for the NISAR ecosystem. We break down how to discover, filter, and download sample and simulated NISAR datasets through platforms like NASA's ASF DAAC (Alaska Satellite Facility Distributed Active Archive Center). Furthermore, we demonstrate how to utilize open-source Python libraries, Jupyter Notebooks, and cloud-optimized data formats to perform core pre-processing steps—including geocoding, radiometric calibration, and interferometric workflows.
Whether you are a GIS expert, a disaster response coordinator, an environmental scientist, or a space enthusiast eager to prepare for the most ambitious radar mapping mission in history, these sessions deliver critical technical workflows. Subscribe to the NASA Live Video Podcast to catch up on the entire series and stay connected with the absolute frontier of space exploration, remote sensing tools, and cutting-edge earth science!
In this advanced double-session episode of the NASA Live Video Podcast, we shift our focus from the theoretical parameters of radar science to the actual infrastructure built for retrieving and processing cloud-free planetary data. The upcoming NISAR (NASA-ISRO Synthetic Aperture Radar) mission is set to generate an unprecedented volume of high-resolution L-band and S-band SAR data, making it essential for researchers worldwide to master the specialized data pipelines and cloud architectures designed to handle it.
Through the framework of NASA’s Applied Remote Sensing Training (ARSET) program, we provide a hands-on guide to navigating the primary data portals and open-access toolkits developed for the NISAR ecosystem. We break down how to discover, filter, and download sample and simulated NISAR datasets through platforms like NASA's ASF DAAC (Alaska Satellite Facility Distributed Active Archive Center). Furthermore, we demonstrate how to utilize open-source Python libraries, Jupyter Notebooks, and cloud-optimized data formats to perform core pre-processing steps—including geocoding, radiometric calibration, and interferometric workflows.
Whether you are a GIS expert, a disaster response coordinator, an environmental scientist, or a space enthusiast eager to prepare for the most ambitious radar mapping mission in history, these sessions deliver critical technical workflows. Subscribe to the NASA Live Video Podcast to catch up on the entire series and stay connected with the absolute frontier of space exploration, remote sensing tools, and cutting-edge earth science!
View all episodes
By NASAWelcome to Sessions 2 & 3 of our specialized series on next-generation radar data: "NASA ARSET: NISAR Data Access and Tools - Session 2_3."
In this advanced double-session episode of the NASA Live Video Podcast, we shift our focus from the theoretical parameters of radar science to the actual infrastructure built for retrieving and processing cloud-free planetary data. The upcoming NISAR (NASA-ISRO Synthetic Aperture Radar) mission is set to generate an unprecedented volume of high-resolution L-band and S-band SAR data, making it essential for researchers worldwide to master the specialized data pipelines and cloud architectures designed to handle it.
Through the framework of NASA’s Applied Remote Sensing Training (ARSET) program, we provide a hands-on guide to navigating the primary data portals and open-access toolkits developed for the NISAR ecosystem. We break down how to discover, filter, and download sample and simulated NISAR datasets through platforms like NASA's ASF DAAC (Alaska Satellite Facility Distributed Active Archive Center). Furthermore, we demonstrate how to utilize open-source Python libraries, Jupyter Notebooks, and cloud-optimized data formats to perform core pre-processing steps—including geocoding, radiometric calibration, and interferometric workflows.
Whether you are a GIS expert, a disaster response coordinator, an environmental scientist, or a space enthusiast eager to prepare for the most ambitious radar mapping mission in history, these sessions deliver critical technical workflows. Subscribe to the NASA Live Video Podcast to catch up on the entire series and stay connected with the absolute frontier of space exploration, remote sensing tools, and cutting-edge earth science!
In this advanced double-session episode of the NASA Live Video Podcast, we shift our focus from the theoretical parameters of radar science to the actual infrastructure built for retrieving and processing cloud-free planetary data. The upcoming NISAR (NASA-ISRO Synthetic Aperture Radar) mission is set to generate an unprecedented volume of high-resolution L-band and S-band SAR data, making it essential for researchers worldwide to master the specialized data pipelines and cloud architectures designed to handle it.
Through the framework of NASA’s Applied Remote Sensing Training (ARSET) program, we provide a hands-on guide to navigating the primary data portals and open-access toolkits developed for the NISAR ecosystem. We break down how to discover, filter, and download sample and simulated NISAR datasets through platforms like NASA's ASF DAAC (Alaska Satellite Facility Distributed Active Archive Center). Furthermore, we demonstrate how to utilize open-source Python libraries, Jupyter Notebooks, and cloud-optimized data formats to perform core pre-processing steps—including geocoding, radiometric calibration, and interferometric workflows.
Whether you are a GIS expert, a disaster response coordinator, an environmental scientist, or a space enthusiast eager to prepare for the most ambitious radar mapping mission in history, these sessions deliver critical technical workflows. Subscribe to the NASA Live Video Podcast to catch up on the entire series and stay connected with the absolute frontier of space exploration, remote sensing tools, and cutting-edge earth science!