Stakeholder Engagement Program (SEP)
NASA's Satellite Needs Working Group Management Office (SNWG MO) includes a Stakeholder Engagement Program (SEP) focused on supporting SNWG product user communities with relevant training and end-user engagement activities. SEP efforts include aggregation and delivery of relevant training in remote sensing topics, background on developed products, and training on how to efficiently access and utilize new products for stakeholder decision-making. Resources aggregated or provided by SEP focus on NASA and partner contributions in areas of remote sensing training, code recipes, and data processing.
The biennial SNWG survey and assessment cycles have led to the funding of new solutions which undergo processes for their formulation, implementation, and operational deployment. Solutions developed and deployed for operational use through new web portals, data products, and other capabilities are referenced below with links that direct users to more information.
Catalog of Archived Suborbital Earth Science Investigations (CASEI)
CASEI facilitates quick access to detailed information about NASA’s Earth Science airborne and field investigations and provides curated information about the context, research motivation, funding, and details of non-satellite instruments and platforms.
Commercial Smallsat Data Acquisition (CSDA) Program
NASA began exploring the purchase of commercial land surface imagery and other products in 2018 and based upon needs stated by agency partners, recently expanded license agreements to facilitate access to commercial imagery for researchers and many federal agencies. Read more about CSDA.
Planet Resource List
Focus Area | Topic | Title | Source |
---|---|---|---|
Fundamentals of Remote Sensing | Background on Remote Sensing | Fundamentals of Remote Sensing | NASA ARSET |
Orbits, Sensors, and Spatial Resolutions | What is Remote Sensing? | NASA Earthdata | |
Remote Sensing Overview | From Pixels to Products: An Overview of Satellite Remote Sensing | Earthdata / IMPACT | |
Missions and Instruments | Overview of Planet Constellations | Planet | Insights - Our Constellations | Planet |
PlanetScope Overview | PlanetScope | Planet | |
PlanetScope Mission and Instrument Specifications | PlanetScope - Earth Online | European Space Agency (ESA) | |
SkySat Overview | SkySat | Planet | |
SkySat Mission and Instrument Specifications | SkySat - Earth Online | ESA | |
Data Products and Descriptions | Summary of Planet Products | Satellite Imagery Products | Planet | Planet |
Planet Imagery Product Specifications | Planet Imagery Product Specifications | Planet | |
Data Access and Code Examples | Planet Data Access | CSDA Commercial Datasets | NASA |
Open-Source Tools for Planet Data Users | Resources for Planet Users | Planet | |
Tool for Searching and Accessing Commercial Smallsat Data Acquired by NASA | CSDA Smallsat Data Explorer | CSDA | |
Use Case and Application Examples | Overview of Planet and Potential Applications | Planet Overview | Planet |
On-demand Webinars and Use Cases for Planet Data | Planet Resources | Planet | |
Using Planet Data to Complete a Growing Season Assessment | USDA’s National Agricultural Statistics Service To Use Planet Basemaps To Support Their 2021 Growing Season Assessment | Planet | |
Using PlanetScope Data for Air Quality Research | Exploring the Use of PlanetScope Data for Particulate Matter Air Quality Research | MDPI Remote Sensing | |
Using PlanetScope Imagery to Assess Crop Yield Variability | Assessing within-Field Corn and Soybean Yield Variability from WorldView-3, Planet, Sentinel-2, and Landsat 8 Satellite Imagery | MDPI Remote Sensing | |
Generating Automated DEMs from Planet SkySat Imagery | Automated DEM generation from very-high-resolution Planet SkySat triplet stereo and video imagery | Elsevier ISPRS Journal of Photogrammetry and Remote Sensing |
Maxar Resource List
Focus Area | Topic | Title | Source |
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Fundamentals of Remote Sensing | Background on Remote Sensing | Fundamentals of Remote Sensing | ARSET |
Orbits, Sensors, and Spatial Resolutions | What is Remote Sensing? | Earthdata | |
Remote Sensing Overview | From Pixels to Products: An Overview of Satellite Remote Sensing | Earthdata / IMPACT | |
Series on satellite imagery basics | Satellite Imagery Basics | Maxar | |
Missions and Instruments | Overview of WorldView series | WorldView Series | ESA |
WorldView-1 Technical Specifications | WorldView-1 Data Sheet | Maxar | |
WorldView-2 Technical Specifications | WorldView-2 Data Sheet | Maxar | |
WorldView-3 Technical Specifications | WorldView-3 Data Sheet | Maxar | |
WorldView-4 Technical Specifications | WorldView-4 Data Sheet | Maxar | |
Data Products and Descriptions | Maxar Product Overview | Product Overview | Maxar |
View-Ready Data Product Specifications | View-Ready (2A) Imagery | Maxar | |
Analysis-Ready Data Product Specifications | Analysis Ready Data | Maxar | |
ESA WorldView Data Products | ESA WorldView Data Products | ESA | |
Data Access and Code Examples | WorldView Data Access | NASA CSDA Program Commercial Datasets | NASA |
Maxar High-Resolution Satellite Data Access through NASA / NGA | NASA / NGA Commercial Archive Data | NASA / NGA | |
Maxar Data Viewer | Maxar - Archive Search & Discovery | Maxar | |
WorldView Data Access through Sentinel Hub | Sentinel Hub WorldView Data Access | Sentinel Hub | |
Maxar On-Demand Imagery Access | Maxar SecureWatch | Maxar | |
Use Case and Application Examples | Government and Commercial Use Cases for Maxar products | Maxar Product Use Cases | Maxar |
Mapping Methane Plumes | WorldView-3 satellite maps methane plumes at very high spatial resolution | ESA | |
High-resolution DEMs from CSDA and PGC | New in CSDA: High Resolution Digital Elevation Models | CSDA | |
Monitoring Shoreline Change in Coastal Wetlands | Coastal Wetland Shoreline Change Monitoring | MDPI Remote Sensing | |
Counting Trees in Africa’s Drylands | Counting Trees in Africa’s Drylands | NASA |
Harmonized Landsat Sentinel-2 (HLS)
HLS provides consistent surface reflectance (SR) data from the Operational Land Imager (OLI) aboard the joint NASA/USGS Landsat 8 satellite and the Multi-Spectral Instrument (MSI) aboard the European Space Agency’s (ESA) Copernicus Sentinel-2A and Sentinel-2B satellites. The combined measurement enables global observations of land every 2–3 days at 30 m spatial resolution. Our SEP effort provides resources on the use of HLS in collaboration with NASA’s LP DAAC, Applied Science: Capacity Building program, and other partners.
Focus Area | Topic | Title | Source |
---|---|---|---|
Fundamentals of Land Surface Remote Sensing | Background on Remote Sensing | Fundamentals of Remote Sensing | ARSET |
Background on Remote Sensing | From Pixels to Products: An Overview of Satellite Remote Sensing | Earthdata / IMPACT | |
Orbits, Sensors, and Spatial Resolutions | What is Remote Sensing? | Earthdata | |
Missions and Instruments | Landsat Series | Landsat | NASA |
Sentinel-2 Series | Sentinel-2 Missions | ESA | |
Combined Orbits | Landsat with Sentinel: Global Coverage | Goddard Scientific Visualization Studio | |
Data Products and Descriptions | Harmonized Landsat Sentinel-2 (HLS) | Harmonized Landsat Sentinel-2 (HLS) | Earthdata |
HLS L30 Dataset Landing Page | HLSL30 v2.0 | LP DAAC | |
HLS S30 Dataset Landing Page | HLSS30 v2.0 | LP DAAC | |
HLS Algorithm | Algorithm Theoretical Basis Document | LP DAAC | |
HLS User Guide | HLS User Guide | LP DAAC | |
Details about HLS Imagery Products | HLS SNWG Product Fact Sheet (PDF) | IMPACT |
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Data Access and Code Examples | Data Access and Manipulation | Getting Started with Cloud-Native HLS Data in Python | LP DAAC |
Details about the STAC API | STAC API | RadiantEarth / StacSpec | |
Use Case and Application Examples | Example Applications | Harmonized Landsat 8 and Sentinel-2 Data | Goddard Scientific Visualization Studio |
True and False Color Combinations | Common Landsat Band RGB Composites | USGS | |
Vegetation Indices | Creating and Using NDVI from Satellite Imagery | ARSET | |
Crop and Vegetation Phenology | Understanding Phenology Using Remote Sensing | ARSET | |
Burn Scar Mapping | Techniques for Wildfire Detection and Monitoring | ARSET | |
Land Cover Classification | Land Cover Classification with Satellite Imagery | ARSET |
Ice, Cloud & Land Elevation Satellite-2 (ICESat-2) Quick Look Products
Users of ICESat-2 data for various atmospheric, land, and ice analysis submitted needs for products to be generated with reduced latency. As a result, an SNWG MO solution focused on the generation of ICESat-2 “Quick Look” products, that can be delivered at reduced latency relative to the standard ICESat-2 products permanently archived by NSIDC DAAC. Quick Look versions of products focus on latency of 3-5 days versus the typical 45-day latency of standard products.
Products to be developed as Quick Look versions include atmospheric profiles, along-track sea ice, vegetation and canopy height, and inland water bodies. In addition, the ICESat-2 team will explore development of a new Lake Ice Freeboard product with standard and quick-look latency. ICESat-2 Quick Look products will be released to the community as they are developed, with training and engagement supported by the SNWG Stakeholder Engagement Program.
Focus Area | Topic | Title | Source |
---|---|---|---|
Fundamentals of LiDAR Remote Sensing | Background on LiDAR Remote Sensing | The Fundamentals of LiDAR | ARSET |
Background on LiDAR Remote Sensing | Sensing Our Earth from Above | NASA's Langley Research Center/ASDC | |
Background on LiDAR Remote Sensing | The Basics of LiDAR - Light Detection and Ranging - Remote Sensing | NSF | |
Missions and Instruments | ICESat-2 Mission | ICESat-2 Mission Page | NASA's Goddard Space Flight Center |
ICESat-2 Technical Specifications | ICESat-2 Technical Specs | Goddard | |
ICESat-2 ATLAS | Space Lasers | Goddard | |
ICESat-2 Overview | About ICESat-2 | Goddard | |
Data Products and Descriptions | ICESat-2 Data Description | ICESat-2 Data Usher in a New Age of Exploration | Earthdata |
ICESat-2 Data Products (includes ATBDs) | ICESat-2 Data Products | Goddard | |
ICESat-2 Data Products (includes User Guides) | ICESat-2 Data Sets at NSIDC | NSIDC | |
ICESat-2 Product Descriptions | ICESat-2 Product Descriptions | NSIDC | |
Details about ICESat-2 Quick Look Data Products | ICESat-2 SNWG Product Fact Sheet | IMPACT | |
Data Access and Code Examples | Browse ICESat-2 Data | OpenAltimetry | NASA |
Browse ICESat-2 Data | Earthdata Search | NASA | |
ICESat-2 Data Access and Services | ICESat-2 Data Access and Services | ARSET | |
Open-source Resource Library for Working with ICESat-2 Data | icepyx: Python tools for obtaining and working with ICESat-2 data | NSIDC | |
Cloud-based Data Processing Service for ICESat-2 Data Products | ICESat-2 SlideRule | University of Washington / ICESat-2 Program | |
Use Case and Application Examples | ICESat-2 Applications | ICESat-2 Applications | NASA |
Monitoring Water Level Height | Mapping and Monitoring Lakes and Reservoirs with Satellite Observations | ARSET | |
ICESat-2 Hackweek | Hacking ICESat-2: How an Open Science Workshop Helped Scientists Wrangle Big Data | NCCS | |
ICESat-2 Hackweek | ICESat-2 Hackweek Learning Resources | University of Washington eScience Institute | |
Monitoring Wildlife Hazard Potential | Wildfires | Goddard | |
Mitigating Volcanic Events | Volcanic Hazards | Goddard | |
Identifying and Tracking Icebergs | Iceberg Hazards | Goddard |
Observation Products for End-Users for Remote Sensing Analysis (OPERA)
Started in April 2021, the Observation Products for End-Users for Remote Sensing Analysis (OPERA) project at the Jet Propulsion Laboratory collects data from satellite radar and optical instruments to generate three products that respond to the needs identified by various federal agencies during the 2018 cycle (a.k.a., Cycle 2) of the SNWG MO development activities, namely:
- a near-global Surface Water Extent product suite,
- a near-global Surface Disturbance product suite, and
- a North-America Displacement product suite.
The first is generated from synthetic aperture radar (SAR) and optical data. The second is generated from optical data only. The third is generated from Interferometric SAR data. In addition, OPERA is producing two intermediate SAR data products:
- a North America land coregistered single-look complex (CSLC) product suite; and
- a near-global land-surface radiometric terrain-corrected (RTC) product.
The OPERA data products and time series are derived from measurements made by the instruments aboard the Sentinel-1A/1B, Sentinel-2A/2B, and Landsat-8 satellites, to be augmented by the measurements from the radars on the soon-to-be-launched NISAR and SWOT satellites. All products will be distributed though NASA's Distributed Active Archive Centers (DAACs).
As part of its SNWG activities the OPERA team engages in coordination with the overall SNWG SEP managed by the SNWG program office at IMPACT. This includes end-user engagement and training with federal agencies, interested satellite data users, and members of the broader science and applications communities.
For more information on the project and its activities visit the OPERA website.
Page Last Updated: Apr 4, 2022 at 11:29 AM EDT