2024 Applied Earth Observations Innovation Partnership (AEOIP) Annual Workshop

Co-producing EO-driven solutions for fire, forest, ecosystem, and rangeland management

23 - 25 April 2024, Ann Arbor, Michigan

Sign-Up, Agenda, and Logistics Form

2024 Workshop Objectives:

• Meet AEOIP’s mission to serve as a boundary-spanning organization between NASA and Forest and Rangeland Management (FRM) organizations in the U.S.
• Meet AEOIP’s mission by providing a forum for building new relationships among Earth observations data providers, users, and beneficiaries.
• Explicitly incorporate co-production into AEOIP discussions.
• Gather and/or co-develop shovel-ready ideas that would leverage Earth observations to meet science and management priorities of U.S. land and natural resource management agencies.
   

Applied Earth Observations Innovation Partnership (AEOIP)

Photo Credit

Andy Hudak, USDA Forest Service

Earth Observation (EO) data is remotely sensed data about Earth’s land, water, and atmosphere that come from NASA satellites and other instruments. Earth Observation data products can be used to efficiently monitor land condition and help predict the results of land management actions. There are many applications for the data products in land management including: predicting forest fire risk, monitoring impacts of climate change on water or land resources, calculating carbon stocks and fluxes, monitoring greenhouse gas inventories, measuring forest structure, estimating habitat quality, monitoring forest/range condition changes, and more. However, Earth Observation technologies have often not been fully integrated into land management operations and activities. 

The Applied Earth Observations Innovation Partnership (AEOIP) was created to foster collaboration between land managers and the producers of remotely sensed EO data products as well as to promote better integration of these products into land management operations. The partnership works to identify and resolve barriers to access and use of EO data products in land management. Some objectives include understanding land manager needs, improving communication, and providing examples and assistance on using EO products through workshops, webinar series, research examples, and training. Remotely sensed EO datasets and data products collected from NASA satellites are already being used in land management – the Partnership is working towards even greater use and integration. 

The Applied Earth Innovative Partnership strives to host annual meetings (virtual or in-person) to: 

• Strengthen partnerships and communication between the producers of various Earth Observation (EO) data products and the land managers using them.
• Provide data and derived tools that are applicable for land managers.
• Provide webinars, working groups, and research examples that exemplify how the EO data can be used to monitor and manage natural resources.
• Learn from stakeholders through an iterative process; adjusting strategies to improve EO data applicability and use.

Key Findings

A summary of the key findings from the USFS-NASA Joint Applications Workshops are published as a framework to work towards the Applied Earth Innovative Partnership’s goals:

• Key Opportunity Areas for NASA-Forest Service Collaboration (2019)
• Summary of the USFS–NASA Joint Applications Workshop on Satellite Data for Natural Resource Management (2019)

Available and emerging remotely sensed Earth Observation datasets for land managers include:

• Carbon Monitoring System (CMS): Data products developed from the CMS Initiative are to support stakeholder needs for carbon monitoring, biomass monitoring, and climate mitigation across a range of scales. The CMS Initiative uses the full range of NASA satellite observations, modeling/analysis capabilities, and commercial off-the-shelf technologies to establish products for supporting national and international policy, regulation, and management of carbon stores.
  • Archived CMS Data Products: 
    • https://daac.ornl.gov/cgi-bin/dataset_lister.pl?p=33 
    • https://disc.gsfc.nasa.gov/datasets?keywords=cms&page=1
• Global Ecosystem Dynamics Investigation (GEDI): GEDI is a full-waveform lidar instrument (NASA) that will provide precise measurements of forest canopy height, canopy vertical structure, and surface elevation. GEDI will advance applications in several fields including forest management and carbon cycling. GEDI’s high resolution and very dense spatial sampling will enhance our knowledge of forest height, cover, vertical structure, habitat quality, carbon sinks & sources, and more.
• Landsat: Landsat-derived science data products include surface reflectance, surface temperature, spectral indices, dynamic surface water extent, fractional snow-covered area, burned area, and provisional evapotranspiration and aquatic reflectance products. Landsat-derived information is routinely used for water, fire, food, and carbon management across the globe.
• Soil Moisture Active Passive Data (SMAP): SMAP provides direct sensing of soil moisture globally in the top 5 cm of the soil column. In addition, SMAP provides model-derived root-zone soil moisture in the top 1 m of the soil column. SMAP-derived soil moisture can provide critical information for wildfire, drought, and flood risk assessments and early warning, and ecological, weather, and hydrological forecasting.
• NASA Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) datasets: ICESat-2 measurements include estimates of canopy height, canopy cover, and terrain height. These measurements can be used for plant biomass estimations, forest structure mapping, and global digital terrain models.
• NASA-ISRO Synthetic Aperture Radar (NISAR): The NISAR mission, expected to launch in early 2023, will provide a variety of products to support management of ecosystem goods and services. NISAR will monitor global forest extent and quality by providing a time series of global radar imagery with a 12-day repeat cycle, even in regions where cloud cover has been a challenge for other remote sensing observations. NISAR data can be used to generate time series information on forest biomass, disturbance detection, and vegetation/soil water content.