SBIR-STTR Award

The broader impact/ commercial potential of this SBIR Phase I project is to support sustainable coastal communities and infrastructure facing risks due to erosion, sea level rise, and coastal storms. Approximately 50% of the world’s population lives within 50 miles of the coast and migration toward coastal areas is increasing. The risks to these areas are reflected in the substantial increase in insurance and FEMA claims. This project will research and develop software systems that streamline the analysis, permitting, and implementation of nature-based coastal protection solutions that have been proven to adapt to these risks and provide environmental benefits. This project will develop cross-cutting technologies that will enhance our knowledge of coastal sciences and engineering and leverage nature-based approaches to coastal integrity issues, leading to increasing ecological, cost, and performance advantages compared to traditional manual methods of data collection, analysis and engineering. The empowerment of more resilient coastal communities, enhanced fisheries, and adaptive infrastructure solutions will incentivize private sector investment in these regions. This SBIR Phase I project proposes to develop an integrated software system to prescribe intelligent coastal maintenance solutions through the automated characterization of the relationship of near-shore vegetative indicator species with shoreline protective actions. It is generally understood that shoreline stability is related to nearshore vegetative health, but the difficulty of analyzing and interpreting the complex data sets with certainty levels sufficient to prescribe specific maintenance actions necessitates the investigation and development of a new analytical framework. The principal technical objective is the development of a machine learning and bayesian inference decision support tool incorporating data from existing imagery databases, multispectral UAV imagery, RTK bathymetry, and shoreline maintenance actions for experimental validation. This approach would be applicable to a wide variety of vegetated erosional shoreline systems (i.e. wetlands, coastal dunes, and mangroves). The anticipated result is the technical foundation of a commercial system to more efficiently manage coastal infrastructure risk at lower costs and with enhanced ecological benefits for society.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.

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is to drive restoration and preservation of coastal wetlands by unlocking their ecosystem value. Many coastal communities are underserved and do not have resources to adapt to increasing risks from erosion, storms, and sea level rise. Enhanced coastal resilience and restoration promotes biodiversity, which bolsters coastal communities through improved fisheries, tourism, and water quality, as well as other "blue economy" benefits. This project will enable coastal communities to access funds from monetizing project co-benefits and promote nature-based solutions with economic and environmental benefits. This project advances NSF?s mission by developing analytical tools that can directly benefit national welfare. The project can create significant impact by enabling more environmentally sustainable adaptation techniques, expanding financing alternatives for coastal wetlands restoration, and promoting equitable actions. This solution creates ecological and socio-economic benefits by addressing the need for more sustainable communities given coastal migration trends and rising sea levels and increased storm intensities. This approach utilizes high-resolution satellite imagery and artificial intelligence to accurately and systematically measure the carbon stock in coastal wetlands. The project will include an integrated suite of technologies for new datasets, a modeling framework to identify coastal shorelines at risk of erosion, high fidelity maps of blue carbon stock, and the characterization of biodiversity in relation to the environment. This project is expected to make significant contributions to the protection of coastal wetlands and the development of novel methods to analyze blue carbon stocks. The project will build on the existing software platform developed during Phase I and extend its application to determine the different blue carbon pools in marshes and mangrove ecosystems. By accurately measuring erosive conditions and carbon stock at a high spatial resolution in coastal wetlands, this solution has the potential to enable markets to meet sustainability goals while preserving the numerous benefits that wetlands provide to the environment and communities. The project would also decrease the uncertainty in the measurement of blue carbon at a high spatial resolution, a critical factor for creating trustworthy and reliable carbon credits, which can be used to finance the restoration and preservation of coastal wetlands.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.