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NOBEL PRIZE 2026

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NSFDirectorate for Computer and Information Science and Engineering

Collaborative Research: Frameworks: OpenForest4D - A web- based cyberinfrastructure platform for next generation 4D forest mapping and monitoring

Active
Institution
University of California-San Diego, CA
Principal investigator
Viswanath Nandigam
Funding
$1.6M
Duration
2024–2028
Open portfolio

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Still being scored

Abstract

Nearly one-third of the Earth's land surface is covered by forests, which host the majority of terrestrial biodiversity. Accurate mapping and monitoring of forests across large regions and over time is critical for mitigating climate and natural hazards, managing natural resources and protection of vital ecosystems. While traditional ground-based measurements of plant species and size provide the most accurate data on forest structure and above ground biomass, these methods become impractical when covering large areas with high-frequency repeat cycles. Airborne and Space-based remote sensing techniques provide a timely and cost-effective way to assess forest structure and biomass on regional to global scales. Satellite missions from NASA and ESA have sensors that gather data with significantly more frequent repeat cycles compared to in situ measurements or aerial surveys. While these satellite missions offer global coverage, some provide only sparse data on forest structure and need to be combined with other data sources for producing comprehensive and accurate wall-to-wall maps. There is a lack of efficient frameworks that utilize multi-source remote sensing data to produce wall-to-wall forest structure or above ground biomass at temporal and spatial scales necessary for effective forest management or use in hazard mitigation and monitoring applications. Without significant improvements to existing methodologies and looking beyond traditional data sources, efficient and accurate monitoring of forest structure and above ground biomass will remain limited. OpenForest4D will allow a wide range of users to generate on-demand and up-to-date research-grade forest structure and above ground biomass estimates across a range of timescales. This will be achieved by applying novel statistical models and artificial intelligence methodologies on a fusion of multi-source remote sensing data from ground, airborne and spaceborne platforms. Providing these cyberinfrastructure services through easily accessible interactive web-based interfaces, along with educational resources focused on the underlying domain science, will facilitate transformative research in forest sciences and ecology and encourage broad community participation. OpenForest4D's web-based educational resources, published curriculum materials, and live webinars will help develop a diverse, globally competitive STEM workforce. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Biological Infrastructure within the Directorate for Biological Sciences and NSF's National Discovery Cloud for Climate initiative. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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Directorate for Computer and Information Science and EngineeringINTERDISCIPLINARY PROPOSALSSoftware InstitutesADVANCES IN BIO INFORMATICSCapacity: CyberinfrastructureNDCC-Natl Discvry Cloud Climatcyberinfrastructuregroundforestairborneremote sensingbiomasssensing dataforests

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