Geology topics

Molly Reif

Publications and source records attributed to Molly Reif.

4 recordsLinked to original sources

USGS2026

Cyanobacteria Assessment Network: Pilot study with Sentinel-2 derived chlorophyll data

Harmful algal blooms (HABs) affect global water quality, limiting uses like recreation and consumption because of excessive algal biomass and toxin production. These blooms cause surface scums, taste and odor issues, hypoxia, and negative health and socioeconomic impacts. The US Army Corps of Engineers (USACE) manages over 400 lakes and reservoirs and seeks to improve monitoring of HABs through Sentinel-2 (S2) satellite imagery. The purpose of this project is to develop workflows for a national chlorophyll-a product with 20 m spatial resolution, enabling HAB monitoring for over 270,000 lakes and reservoirs. The 1-year pilot study established a federal partnership to conduct preliminary S2 processing steps, using datasets from Florida, Ohio, and Oregon. Key steps included in situ data aggregation, data assimilation, S2 algorithm evaluation, spatial and temporal compositing, satellite sensor cross-validation, and web hosting of an example prototype product. The study covers 29 USACE reservoirs, with cross-validation using Sentinel-3 (S3) data from 212 lakes. The multiagency initiative aligns with federal agency missions to protect health and the environment, supports acts like the 2017 Harmful Algal Bloom and Hypoxia Research and Control Act, and has annual potential avoided costs of $42 million.

contiguous United States↗

USGS2026

Sentinel-2 for chlorophyll-a water quality monitoring: A review of validation evidence and application potential

Water quality monitoring is integral to preserving the health of freshwater ecosystems, and satellite remote sensing has emerged as one monitoring method. Sentinel-2, in particular, has been valuable for water quality monitoring due to its 5-day global temporal revisit time and spatial resolution that ranges from 10 to 60 metres. Sentinel-2 can be used to measure and monitor chlorophyll-a, which historically has been used as an indicator of water quality, eutrophication and harmful algal blooms. Our goal was to review aquatic chlorophyll-a Sentinel-2 research to assess the types of validation evidence reported. Validation evidence is defined here as the set of information key to assessing algorithm performance, and include the spatial and temporal scales of satellite validation, reported in situ sampling method context information, demonstration of validation results through plots, and appropriate algorithm performance metrics. We highlight how the body of literature collectively contributes to advancing a national scale chlorophyll-a product that could support future resource management applications. Our review of 122 published studies indicated that much of the validation evidence corresponded to early stages, as defined by the NASA data maturity framework, due to a limited focus on individual lakes and limited detail on methodology for reproducibility. Prioritizing data accessibility for both in situ data and satellite workflows used in published studies; reporting methods with transparency and consistency; and using standard algorithm performance metrics could provide a consistent framework to support and enhance the utility of satellite inland water quality research. These three quality assurance mechanisms can promote effective evaluation of approaches for remote sensing of chlorophyll-a. Adopting these quality criteria could enable the integration of validation evidence from multiple studies, supporting more spatially and temporally representative products that would advance these approaches towards maturation for broader application.

International Journal of Remote Sensing↗

USGS2024

Restoration monitoring metric framework: Integrating innovative remote-sensing technologies: Comparisons between field and remotely sensed vegetation surveys of restored forested and grassland sites in Ohio

Restoration monitoring is generally perceived as costly and time-consuming, yet the concept of universal restoration monitoring metrics is trending for evaluation of restoration performance across spatial scales, project boundaries, and jurisdictions. Natural Resource Damage Assessment and Restoration (NRDAR) practitioners seek to restore natural resources injured by oil spills or hazardous substance releases into the environment. Therefore, a multiagency team [US Army Engineer Research and Development Center (ERDC), US Department of the Interior (DOI), and US Department of Energy (DOE)] developed and field-tested a multitiered monitoring framework, illustrating a range of field and remote-sensing techniques and methodologies. The restoration monitoring framework and field demonstration offer a unique methodology to acquire and evaluate simultaneously collected, multiscale/multiplatform data. The result of this research provides new insights to (1) assist planning, implementing, and monitoring restoration progress and effectiveness; and (2) apply common monitoring methods, endpoints, and metrics to other types of ecosystem restoration initiatives. Although the aim was to inform monitoring and management of areas that had been injured, these methods could also be used to inform restoration monitoring practices in a broader context, benefiting environmental stewardship missions of all project partners.

Final Technical Report↗

USGS2012

State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill

The vast and persistent Deepwater Horizon (DWH) spill challenged response capabilities, which required accurate, quantitative oil assessment at synoptic and operational scales. Although experienced observers are a spill response's mainstay, few trained observers and confounding factors including weather, oil emulsification, and scene illumination geometry present challenges. DWH spill and impact monitoring was aided by extensive airborne and spaceborne passive and active remote sensing. Oil slick thickness and oil-to-water emulsion ratios are key spill response parameters for containment/cleanup and were derived quantitatively for thick (> 0.1 mm) slicks from AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data using a spectral library approach based on the shape and depth of near infrared spectral absorption features. MODIS (Moderate Resolution Imaging Spectroradiometer) satellite, visible-spectrum broadband data of surface-slick modulation of sunglint reflection allowed extrapolation to the total slick. A multispectral expert system used a neural network approach to provide Rapid Response thickness class maps. Airborne and satellite synthetic aperture radar (SAR) provides synoptic data under all-sky conditions; however, SAR generally cannot discriminate thick (> 100 μm) oil slicks from thin sheens (to 0.1 μm). The UAVSAR's (Uninhabited Aerial Vehicle SAR) significantly greater signal-to-noise ratio and finer spatial resolution allowed successful pattern discrimination related to a combination of oil slick thickness, fractional surface coverage, and emulsification. In situ burning and smoke plumes were studied with AVIRIS and corroborated spaceborne CALIPSO (Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation) observations of combustion aerosols. CALIPSO and bathymetry lidar data documented shallow subsurface oil, although ancillary data were required for confirmation. Airborne hyperspectral, thermal infrared data have nighttime and overcast collection advantages and were collected as well as MODIS thermal data. However, interpretation challenges and a lack of Rapid Response Products prevented significant use. Rapid Response Products were key to response utilization—data needs are time critical; thus, a high technological readiness level is critical to operational use of remote sensing products. DWH's experience demonstrated that development and operationalization of new spill response remote sensing tools must precede the next major oil spill.

Remote Sensing of Environment↗