NASA LIVE VIDEO PODCAST

Welcome to Part 2 of our specialized series on coastal remote sensing and altimetry data: "NASA ARSET: Techniques for Plotting and Analyzing ATL24 Coastal Bathymetry Part 2."
In this episode of the NASA Live Video Podcast, we advance from our foundational overview into the practical, hands-on programming and analytical workflows required to process coastal data. Mapping the shallow waters of our global coastlines is critical for marine navigation, habitat conservation, and coastal vulnerability assessments—and NASA's ICESat-2 ATL24 product provides some of the most precise spaceborne LiDAR bathymetry data available today.
Through the framework of NASA’s Applied Remote Sensing Training (ARSET) program, we dive deep into the technical methods used to plot and analyze these complex photon-return profiles. We discuss how to handle the ATL24 HDF5 data structure, utilize open-source Python libraries (such as h5py, pandas, and matplotlib) for visualization, isolate sea-surface vs. sea-floor returns, and account for water column refraction to ensure highly accurate depth measurements along dynamic coastal zones.
Whether you are a marine scientist, a coastal engineer, a GIS developer, or a space enthusiast eager to see how advanced laser altimetry maps the ocean floor from orbit, this second installment delivers essential technical insights. Subscribe to the NASA Live Video Podcast to catch up on Part 1 and stay connected with the absolute frontier of space exploration, remote sensing, and cutting-edge earth science!

Welcome to this vital and highly informative episode of the NASA Live Video Podcast: "NASA ARSET: Imágenes Satelitales Posteriores a un Incendio y Monitoreo del Humo."
In this episode, we explore how spaceborne technology operates on the frontlines of disaster management and environmental recovery. When massive wildfires strike, the danger doesn't end when the flames are extinguished. Tracking the ecological damage left behind and monitoring the toxic smoke plumes that travel across continents are critical tasks for public safety and atmospheric science.
Through the framework of NASA’s Applied Remote Sensing Training (ARSET) program, we break down the methodologies used to analyze post-fire satellite imagery and monitor smoke progression. We discuss how thermal, optical, and infrared sensors help scientists map burn severity, assess vegetation loss, and identify areas prone to post-fire mudslides. Furthermore, we dive into how satellite assets track atmospheric aerosol transport, helping meteorological agencies predict air quality degradation downwind from active burn zones.
Whether you are a forestry professional, an air quality specialist, an emergency responder, or a space enthusiast curious about how NASA monitors planetary health during climate extremes, this episode offers essential insights into modern remote sensing. Subscribe to the NASA Live Video Podcast to stay connected with the frontier of space exploration, disaster response, and cutting-edge earth science!

Welcome to Part 2 of our specialized series on advanced data management and Earth intelligence: "NASA ARSET: Análisis y Visualización de Datos - Parte 2."
In this episode of the NASA Live Video Podcast, we move forward from our introductory concepts into the practical and powerful workflows used to analyze and visualize complex satellite datasets. As the volume of global Earth observation data continues to grow, mastering the tools and platforms needed to extract actionable insights from raw spatial information is essential for modern environmental and climate research.
Through the framework of NASA’s Applied Remote Sensing Training (ARSET) program, we dive deep into the specific analytical workflows and open-access visualization platforms utilized by scientists worldwide. We discuss how to handle multi-temporal data layers, generate statistical analysis from satellite time-series, and use specialized software and cloud-based environments to create compelling, professional visual representations that effectively communicate scientific findings to stakeholders and decision-makers.
Whether you are a GIS analyst, an environmental researcher, a data scientist, or a space enthusiast curious about how satellite observations are transformed into clear visual maps, this second installment offers vital, practical insights. Subscribe to the NASA Live Video Podcast to catch up on Part 1 and stay connected with the frontier of space exploration, remote sensing, and cutting-edge earth science!

Welcome to Part 2 of our specialized series on environmental data science: "Introduction to a Machine Learning Model to Estimate Water Quality Parameters Part 2."
In this episode of the NASA Live Video Podcast, we move beyond the foundational concepts and dive deep into the practical deployment, training, and validation of machine learning algorithms for aquatic monitoring. Accurately assessing water quality across vast geographical scales requires a powerful combination of remote sensing data and predictive intelligence to turn raw satellite observations into real-time environmental insights.
We break down the technical workflows involved in modeling critical water quality parameters—such as Chlorophyll-a concentrations, Total Suspended Solids (TSS), Colored Dissolved Organic Matter (CDOM), and sea/lake surface temperatures. We discuss how regression and classification models utilize satellite-derived surface reflectance data, how to address overfitting, and the importance of ground-truth validation using in-situ data networks to ensure your model's accuracy.
Whether you are a data scientist, a hydrologist, an environmental engineer, or a space enthusiast curious about how artificial intelligence intersects with Earth observation, this second installment offers vital, technical insights. Subscribe to the NASA Live Video Podcast to catch up on Part 1 and stay connected with the absolute frontier of space exploration, remote sensing, and cutting-edge earth science!

Welcome to another highly technical and informative episode of the NASA Live Video Podcast: "NASA ARSET: Classification Methods for Land Cover."
In this episode, we dive into the core engine of geospatial analysis—turning raw satellite imagery into meaningful, actionable maps. Mapping Earth's surface is essential for tracking urbanization, agricultural expansion, and ecosystem health, but achieving this requires robust, scientific image classification methods.
Through the framework of NASA’s Applied Remote Sensing Training (ARSET) program, we provide a comprehensive overview of the primary classification techniques used in remote sensing today. We break down the differences between pixel-based and object-based image analysis (OBIA), and contrast traditional methods like Supervised and Unsupervised classification with modern Machine Learning approaches—including Random Forest, Support Vector Machines (SVM), and Classification and Regression Trees (CART). Additionally, we discuss how to assess map accuracy to ensure your land cover datasets are reliable for decision-making.
Whether you are a GIS professional, an urban planner, an environmental scientist, or a space enthusiast curious about how computer algorithms read satellite data from orbit, this episode offers essential insights into modern data processing. Subscribe to the NASA Live Video Podcast to stay updated on the frontier of earth science, satellite imagery, and global exploration!

Welcome to Part 1 of our specialized series on global hydrology and gravity anomalies: "NASA ARSET: Overview and Analysis of NASA Terrestrial Water Storage Data from GRACE/GRACE-FO Pt. 1."
In this episode of the NASA Live Video Podcast, we embark on a fascinating journey to explore how space technology tracks water that is completely hidden from human sight. We focus our attention on the revolutionary GRACE (Gravity Recovery and Climate Experiment) and its successor, GRACE-FO (Follow-On) missions—twin satellite systems that measure variations in Earth’s gravity field to monitor mass distribution changes, primarily driven by water movement.
Through the framework of NASA’s Applied Remote Sensing Training (ARSET) program, we break down the foundational concepts behind Terrestrial Water Storage (TWS). We discuss how GRACE/GRACE-FO data allows scientists to look beyond the surface, aggregating groundwater, soil moisture, surface water, snow, and ice into a comprehensive monthly global dataset. This opening part provides an essential overview of how to access and interpret these gravity-based observations to detect massive hydrologic changes across the globe.
Whether you are a hydrologist, a climate scientist, a water resource manager, or a space enthusiast eager to understand how NASA weighs the Earth's water from orbit, this episode delivers critical foundational insights. Subscribe to the NASA Live Video Podcast to catch this entire series and stay connected with the frontier of space exploration, remote sensing, and cutting-edge earth science!

Welcome to this highly informative and exclusive archive episode of the NASA Live Video Podcast: "NISAR Science Team Meeting - Town Hall and Data Access Webinar (Feb 2026)."
In this episode, we take you inside the official briefing rooms to cover the latest critical updates from the NISAR Science Team Meeting and Town Hall held in February 2026. As the historic NASA-ISRO Synthetic Aperture Radar (NISAR) mission approaches its full operational phase, understanding how to navigate, download, and utilize the upcoming massive influx of dual-frequency (L-band and S-band) radar data is essential for the global scientific community.
This comprehensive webinar overview breaks down the core discussions from the science team, focusing heavily on data access pathways, open-source tools, and distribution platforms. We outline how researchers, GIS analysts, and environmental scientists can prepare their workflows to handle NISAR’s high-resolution datasets—which will monitor Earth’s land and ice surfaces globally every 12 days to track crustal deformation, ecosystem disruptions, and natural hazards.
Whether you are a remote sensing specialist preparing your data pipelines, a climate scientist, or a space enthusiast eager to follow the exact roadmap of this groundbreaking Earth-observing mission, this episode offers vital technical insights straight from the mission's leading minds. Subscribe to the NASA Live Video Podcast to stay at the absolute forefront of space exploration, satellite data applications, and cutting-edge earth science!

Welcome to Part 2 of our specialized series on environmental monitoring and geospatial analysis: "NASA ARSET: Visualizing Land Cover Change P2."
In this episode of the NASA Live Video Podcast, we advance from our foundational concepts into the practical and powerful workflows used to visualize and interpret changes on the Earth's surface over time. Rapid urbanization, deforestation, and agricultural expansion are continuously reshaping our planet, making the ability to accurately track and visualize these transitions essential for modern environmental conservation.
Through the framework of NASA’s Applied Remote Sensing Training (ARSET) program, we dive deep into the specific tools, platforms, and open-access datasets that allow scientists to map land cover dynamics across different time scales. We discuss effective visualization techniques, how to generate change detection matrices, and how to utilize satellite archives—such as Landsat and Sentinel—to turn raw geospatial data into compelling visual stories that drive policy and planning.
Whether you are an urban planner, an ecologist, a GIS analyst, or someone deeply fascinated by how remote sensing reveals the shifting footprint of humanity on Earth, this episode offers vital, hands-on insights. Subscribe to the NASA Live Video Podcast to catch up on Part 1 and stay connected with the frontier of space exploration, satellite imagery, and cutting-edge earth science!

NASA ARSET  Overview and Applications of GLDAS Groundwater Data Products at Regional Scale Part 2
Welcome to Part 2 of our specialized series on global water resources and land modeling: "NASA ARSET: Overview and Applications of GLDAS Groundwater Data Products at Regional Scale."
In this episode of the NASA Live Video Podcast, we expand on our foundational knowledge to explore the regional applications of the Global Land Data Assimilation System (GLDAS). Groundwater management is heavily dependent on accurate spatial data, and GLDAS plays a critical role by integrating satellite and ground-based observations within advanced land surface models to generate optimal fields of land surface states and fluxes—including deep groundwater storage.
Through the framework of NASA’s Applied Remote Sensing Training (ARSET) program, we break down how GLDAS groundwater data products are downscaled and applied at regional and catchment levels. We discuss how hydrologists, agricultural planners, and environmental agencies utilize these datasets to assess regional aquifer depletion, manage water scarcity, monitor severe drought trends, and inform sustainable policy decisions where ground-based monitoring infrastructure is limited.
Whether you are a water resource manager, a climate scientist, a GIS professional, or someone passionate about how NASA's data modeling helps protect vital freshwater supplies on Earth, this episode offers essential, practical insights. Subscribe to the NASA Live Video Podcast to catch up on the series and stay connected with the frontier of space exploration and cutting-edge earth science!

Welcome to Part 3 of our advanced series on environmental monitoring and radar data: "NASA ARSET: Overview and Applications of OPERA-DISP to Monitor Groundwater Changes."
In this episode of the NASA Live Video Podcast, we shift our focus underground to address one of the most critical resource challenges of our time—groundwater depletion. While groundwater cannot be seen directly from space, its movement and extraction cause subtle surface displacements. To track these changes, we dive deep into OPERA-DISP (Observational Products for End-Users from Remote Sensing Analysis - Displacement Product), a state-of-the-art radar dataset designed to map land subsidence and surface deformation with incredible precision.
Through the framework of NASA’s Applied Remote Sensing Training (ARSET) program, we break down how OPERA-DISP utilizes Interferometric Synthetic Aperture Radar (InSAR) to detect surface changes over time. We discuss how hydrologists, geologists, and water resource managers apply this high-resolution displacement data to infer aquifer compaction, monitor groundwater storage changes, and build sustainable water management strategies.
Whether you are a water management professional, a GIS analyst, an environmental scientist, or someone fascinated by how satellite radar technology reveals hidden underground resources, this episode concludes our series with vital real-world insights. Subscribe to the NASA Live Video Podcast to catch up on previous parts and stay connected with the frontier of space exploration and earth science!