@article{coffer_graybill_whitman_schaeffer_salls_zimmerman_hill_lebrasse_li_keith_et al._2023, title={Providing a framework for seagrass mapping in United States coastal ecosystems using high spatial resolution satellite imagery}, volume={337}, ISSN={["1095-8630"]}, DOI={10.1016/j.jenvman.2023.117669}, abstractNote={Seagrasses have been widely recognized for their ecosystem services, but traditional seagrass monitoring approaches emphasizing ground and aerial observations are costly, time-consuming, and lack standardization across datasets. This study leveraged satellite imagery from Maxar's WorldView-2 and WorldView-3 high spatial resolution, commercial satellite platforms to provide a consistent classification approach for monitoring seagrass at eleven study areas across the continental United States, representing geographically, ecologically, and climatically diverse regions. A single satellite image was selected at each of the eleven study areas to correspond temporally to reference data representing seagrass coverage and was classified into four general classes: land, seagrass, no seagrass, and no data. Satellite-derived seagrass coverage was then compared to reference data using either balanced agreement, the Mann-Whitney U test, or the Kruskal-Wallis test, depending on the format of the reference data used for comparison. Balanced agreement ranged from 58% to 86%, with better agreement between reference- and satellite-indicated seagrass absence (specificity ranged from 88% to 100%) than between reference- and satellite-indicated seagrass presence (sensitivity ranged from 17% to 73%). Results of the Mann-Whitney U and Kruskal-Wallis tests demonstrated that satellite-indicated seagrass percentage cover had moderate to large correlations with reference-indicated seagrass percentage cover, indicative of moderate to strong agreement between datasets. Satellite classification performed best in areas of dense, continuous seagrass compared to areas of sparse, discontinuous seagrass and provided a suitable spatial representation of seagrass distribution within each study area. This study demonstrates that the same methods can be applied across scenes spanning varying seagrass bioregions, atmospheric conditions, and optical water types, which is a significant step toward developing a consistent, operational approach for mapping seagrass coverage at the national and global scales. Accompanying this manuscript are instructional videos describing the processing workflow, including data acquisition, data processing, and satellite image classification. These instructional videos may serve as a management tool to complement field- and aerial-based mapping efforts for monitoring seagrass ecosystems.}, journal={JOURNAL OF ENVIRONMENTAL MANAGEMENT}, author={Coffer, Megan M. and Graybill, David D. and Whitman, Peter J. and Schaeffer, Blake A. and Salls, Wilson B. and Zimmerman, Richard C. and Hill, Victoria and Lebrasse, Marie Cindy and Li, Jiang and Keith, Darryl J. and et al.}, year={2023}, month={Jul} }
 @article{whitman_schaeffer_salls_coffer_mishra_seegers_loftin_stumpf_werdell_2022, title={A validation of satellite derived cyanobacteria detections with state reported events and recreation advisories across US lakes}, volume={115}, ISSN={["1878-1470"]}, DOI={10.1016/j.hal.2022.102191}, abstractNote={Cyanobacteria harmful algal blooms (cyanoHABs) negatively affect ecological, human, and animal health. Traditional methods of validating satellite algorithms with data from water samples are often inhibited by the expense of quantifying cyanobacteria indicators in the field and the lack of public data. However, state recreation advisories and other recorded events of cyanoHAB occurrence reported by local authorities can serve as an independent and publicly available dataset for validation. State recreation advisories were defined as a period delimited by a start and end date where a warning was issued due to detections of cyanoHABs over a state's risk threshold. State reported events were defined as any event that was documented with a single date related to cyanoHABs. This study examined the presence-absence agreement between 160 state reported cyanoHAB advisories and 1,343 events and cyanobacteria biomass estimated by a satellite algorithm called the Cyanobacteria Index (CIcyano). The true positive rate of agreement with state recreation advisories was 69% and 60% with state reported events. CIcyano detected a reduction or absence in cyanobacteria after 76% of the recreation advisories ended. CIcyano was used to quantify the magnitude, spatial extent, and temporal frequency of cyanoHABs; each of these three metrics were greater (r > 0.2) during state recreation advisories compared to non-advisory times with effect sizes ranging from small to large. This is the first study to quantitatively evaluate satellite algorithm performance for detecting cyanoHABs with state reported events and advisories and supports informed management decisions with satellite technologies that complement traditional field observations.}, journal={HARMFUL ALGAE}, author={Whitman, Peter and Schaeffer, Blake and Salls, Wilson and Coffer, Megan and Mishra, Sachidananda and Seegers, Bridget and Loftin, Keith and Stumpf, Richard and Werdell, P. Jeremy}, year={2022}, month={Jun} }
 @article{lebrasse_schaeffer_coffer_whitman_zimmerman_hill_islam_li_osburn_2022, title={Temporal Stability of Seagrass Extent, Leaf Area, and Carbon Storage in St. Joseph Bay, Florida: a Semi-automated Remote Sensing Analysis}, volume={3}, ISSN={["1559-2731"]}, DOI={10.1007/s12237-022-01050-4}, abstractNote={Abstract}, journal={ESTUARIES AND COASTS}, author={Lebrasse, Marie Cindy and Schaeffer, Blake A. and Coffer, Megan M. and Whitman, Peter J. and Zimmerman, Richard C. and Hill, Victoria J. and Islam, Kazi A. and Li, Jiang and Osburn, Christopher L.}, year={2022}, month={Mar} }
 @article{coffer_whitman_schaeffer_hill_zimmerman_salls_lebrasse_graybill_2022, title={Vertical artifacts in high-resolution WorldView-2 and WorldView-3 satellite imagery of aquatic systems}, volume={43}, ISSN={["1366-5901"]}, DOI={10.1080/01431161.2022.2030069}, abstractNote={ABSTRACT Satellite image artefacts are features that appear in an image but not in the original imaged object and can negatively impact the interpretation of satellite data. Vertical artefacts are linear features oriented in the along-track direction of an image system and can present as either banding or striping; banding are features with a consistent width, and striping are features with inconsistent widths. This study used high-resolution data from DigitalGlobeʻs (now Maxar) WorldView-3 satellite collected at Lake Okeechobee, Florida (FL), on 30 August 2017. This study investigated the impact of vertical artefacts on both at-sensor radiance and a spectral index for an aquatic target as WorldView-3 was primarily designed as a land sensor. At-sensor radiance measured by six of WorldView-3ʻs eight spectral bands exhibited banding, more specifically referred to as non-uniformity, at a width corresponding to the multispectral detector sub-arrays that comprise the WorldView-3 focal plane. At-sensor radiance measured by the remaining two spectral bands, red and near-infrared (NIR) #1, exhibited striping. Striping in these spectral bands can be attributed to their time delay integration (TDI) settings at the time of image acquisition, which were optimized for land. The impact of vertical striping on a spectral index leveraging the red, red edge, and NIR spectral bands—referred to here as the NIR maximum chlorophyll index (MCINIR)—was investigated. Temporally similar imagery from the European Space Agencyʻs Sentinel-3 and Sentinel-2 satellites were used as baseline references of expected chlorophyll values across Lake Okeechobee as neither Sentinel-3 nor Sentinel-2 imagery showed striping. Striping was highly prominent in the MCINIR product generated using WorldView-3 imagery, as noise in the at-sensor radiance exceeded any signal of chlorophyll in the image. Adjusting the image acquisition parameters for future tasking of WorldView-3 or the functionally similar WorldView-2 satellite may alleviate these artefacts. To test this, an additional WorldView-3 image was acquired at Lake Okeechobee, FL, on 26 May 2021 in which the TDI settings and scan line rate were adjusted to improve the signal-to-noise ratio. While some evidence of non-uniformity remained, striping was no longer noticeable in the MCINIR product. Future image tasking over aquatic targets should employ these updated image acquisition parameters. Since the red and NIR #1 spectral bands are critical for inland and coastal water applications, archived images not collected using these updated settings may be limited in their potential for analysis of aquatic variables that require these two spectral bands to derive.}, number={4}, journal={INTERNATIONAL JOURNAL OF REMOTE SENSING}, author={Coffer, Megan M. and Whitman, Peter J. and Schaeffer, Blake A. and Hill, Victoria and Zimmerman, Richard C. and Salls, Wilson B. and Lebrasse, Marie C. and Graybill, David D.}, year={2022}, month={Feb}, pages={1199–1225} }
 @article{wu_hilborn_schaeffer_urquhart_coffer_lin_egorov_2021, title={Acute health effects associated with satellite-determined cyanobacterial blooms in a drinking water source in Massachusetts}, volume={20}, ISSN={["1476-069X"]}, url={https://doi.org/10.1186/s12940-021-00755-6}, DOI={10.1186/s12940-021-00755-6}, abstractNote={Abstract}, number={1}, journal={ENVIRONMENTAL HEALTH}, author={Wu, Jianyong and Hilborn, Elizabeth D. and Schaeffer, Blake A. and Urquhart, Erin and Coffer, Megan M. and Lin, Cynthia J. and Egorov, Andrey I}, year={2021}, month={Jul} }
 @article{coffer_schaeffer_foreman_porteous_loftin_stumpf_werdell_urquhart_albert_darling_2021, title={Assessing cyanobacterial frequency and abundance at surface waters near drinking water intakes across the United States}, volume={201}, ISSN={["1879-2448"]}, DOI={10.1016/j.watres.2021.117377}, abstractNote={This study presents the first large-scale assessment of cyanobacterial frequency and abundance of surface water near drinking water intakes across the United States. Public water systems serve drinking water to nearly 90% of the United States population. Cyanobacteria and their toxins may degrade the quality of finished drinking water and can lead to negative health consequences. Satellite imagery can serve as a cost-effective and consistent monitoring technique for surface cyanobacterial blooms in source waters and can provide drinking water treatment operators information for managing their systems. This study uses satellite imagery from the European Space Agency's Ocean and Land Colour Instrument (OLCI) spanning June 2016 through April 2020. At 300-m spatial resolution, OLCI imagery can be used to monitor cyanobacteria in 685 drinking water sources across 285 lakes in 44 states, referred to here as resolvable drinking water sources. First, a subset of satellite data was compared to a subset of responses (n = 84) submitted as part of the U.S. Environmental Protection Agency's fourth Unregulated Contaminant Monitoring Rule (UCMR 4). These UCMR 4 qualitative responses included visual observations of algal bloom presence and absence near drinking water intakes from March 2018 through November 2019. Overall agreement between satellite imagery and UCMR 4 qualitative responses was 94% with a Kappa coefficient of 0.70. Next, temporal frequency of cyanobacterial blooms at all resolvable drinking water sources was assessed. In 2019, bloom frequency averaged 2% and peaked at 100%, where 100% indicated a bloom was always present at the source waters when satellite imagery was available. Monthly cyanobacterial abundances were used to assess short-term trends across all resolvable drinking water sources and effect size was computed to provide insight on the number of years of data that must be obtained to increase confidence in an observed change. Generally, 2016 through 2020 was an insufficient time period for confidently observing changes at these source waters; on average, a decade of satellite imagery would be required for observed environmental trends to outweigh variability in the data. However, five source waters did demonstrate a sustained short-term trend, with one increasing in cyanobacterial abundance from June 2016 to April 2020 and four decreasing.}, journal={WATER RESEARCH}, author={Coffer, Megan M. and Schaeffer, Blake A. and Foreman, Katherine and Porteous, Alex and Loftin, Keith A. and Stumpf, Richard P. and Werdell, P. Jeremy and Urquhart, Erin and Albert, Ryan J. and Darling, John A.}, year={2021}, month={Aug} }
 @article{coffer_schaeffer_salls_urquhart_loftin_stumpf_werdell_darling_2021, title={Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales}, volume={128}, ISSN={["1872-7034"]}, DOI={10.1016/j.ecolind.2021.107822}, abstractNote={Cyanobacterial blooms can have negative effects on human health and local ecosystems. Field monitoring of cyanobacterial blooms can be costly, but satellite remote sensing has shown utility for more efficient spatial and temporal monitoring across the United States. Here, satellite imagery was used to assess the annual frequency of surface cyanobacterial blooms, defined for each satellite pixel as the percentage of images for that pixel throughout the year exhibiting detectable cyanobacteria. Cyanobacterial frequency was assessed across 2,196 large lakes in 46 states across the continental United States (CONUS) using imagery from the European Space Agency’s Ocean and Land Colour Instrument for the years 2017 through 2019. In 2019, across all satellite pixels considered, annual bloom frequency had a median value of 4% and a maximum value of 100%, the latter indicating that for those satellite pixels, a cyanobacterial bloom was detected by the satellite sensor for every satellite image considered. In addition to annual pixel-scale cyanobacterial frequency, results were summarized at the lake- and state-scales by averaging annual pixel-scale results across each lake and state. For 2019, average annual lake-scale frequencies also had a maximum value of 100%, and Oregon and Ohio had the highest average annual state-scale frequencies at 65% and 52%. Pixel-scale frequency results can assist in identifying portions of a lake that are more prone to cyanobacterial blooms, while lake- and state-scale frequency results can assist in the prioritization of sampling resources and mitigation efforts. Satellite imagery is limited by the presence of snow and ice, as imagery collected in these conditions are quality flagged and discarded. Thus, annual bloom frequencies within nine climate regions were investigated to determine whether missing data biased results in climate regions more prone to snow and ice, given that their annual summaries would be weighted toward the summer months when cyanobacterial blooms tend to occur. Results were unbiased by the time period selected in most climate regions, but a large bias was observed for the Northwest Rockies and Plains climate region. Moderate biases were observed for the Ohio Valley and the Southeast climate regions. Finally, a clustering analysis was used to identify areas of high and low cyanobacterial frequency across CONUS based on average annual lake-scale cyanobacterial frequencies for 2019. Several clusters were identified that transcended state, watershed, and eco-regional boundaries. Combined with additional data, results from the clustering analysis may offer insight regarding large-scale drivers of cyanobacterial blooms.}, journal={ECOLOGICAL INDICATORS}, author={Coffer, Megan M. and Schaeffer, Blake A. and Salls, Wilson B. and Urquhart, Erin and Loftin, Keith A. and Stumpf, Richard P. and Werdell, P. Jeremy and Darling, John A.}, year={2021}, month={Sep} }
 @article{yoshizumi_coffer_collins_gaines_gao_jones_mcgregor_mcquillan_perin_tomkins_et al._2020, title={A Review of Geospatial Content in IEEE Visualization Publications}, DOI={10.1109/VIS47514.2020.00017}, abstractNote={Geospatial analysis is crucial for addressing many of the world’s most pressing challenges. Given this, there is immense value in improving and expanding the visualization techniques used to communicate geospatial data. In this work, we explore this important intersection – between geospatial analytics and visualization – by examining a set of recent IEEE VIS Conference papers (a selection from 2017-2019) to assess the inclusion of geospatial data and geospatial analyses within these papers. After removing the papers with no geospatial data, we organize the remaining literature into geospatial data domain categories and provide insight into how these categories relate to VIS Conference paper types. We also contextualize our results by investigating the use of geospatial terms in IEEE Visualization publications over the last 30 years. Our work provides an understanding of the quantity and role of geospatial subject matter in recent IEEE VIS publications and supplies a foundation for future meta-analytical work around geospatial analytics and geovisualization that may shed light on opportunities for innovation.}, journal={2020 IEEE VISUALIZATION CONFERENCE - SHORT PAPERS (VIS 2020)}, author={Yoshizumi, Alexander and Coffer, Megan M. and Collins, Elyssa L. and Gaines, Mollie D. and Gao, Xiaojie and Jones, Kate and McGregor, Ian R. and McQuillan, Katie A. and Perin, Vinicius and Tomkins, Laura M. and et al.}, year={2020}, pages={51–55} }
 @article{coffer_2020, title={Balancing Privacy Rights and the Production of High-Quality Satellite Imagery}, volume={54}, ISSN={["1520-5851"]}, DOI={10.1021/acs.est.0c02365}, abstractNote={ADVERTISEMENT RETURN TO ISSUEPREVViewpointNEXTBalancing Privacy Rights and the Production of High-Quality Satellite ImageryMegan M. CofferMegan M. CofferCenter for Geospatial Analytics, North Carolina State University, Raleigh, North Carolina 27513, United StatesMore by Megan M. Cofferhttp://orcid.org/0000-0003-3188-4729Cite this: Environ. Sci. Technol. 2020, 54, 11, 6453–6455Publication Date (Web):May 11, 2020Publication History Received15 April 2020Published online11 May 2020Published inissue 2 June 2020https://doi.org/10.1021/acs.est.0c02365Copyright © 2020 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views5804Altmetric-Citations4LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (1 MB) Get e-AlertsSUBJECTS:Analytical apparatus,Atmospheric chemistry,Imaging,Planets,Sensors Get e-Alerts}, number={11}, journal={ENVIRONMENTAL SCIENCE & TECHNOLOGY}, author={Coffer, Megan M.}, year={2020}, month={Jun}, pages={6453–6455} }
 @article{coffer_schaeffer_zimmerman_hill_li_islam_whitman_2020, title={Performance across WorldView-2 and RapidEye for reproducible seagrass mapping}, volume={250}, ISSN={["1879-0704"]}, DOI={10.1016/j.rse.2020.112036}, abstractNote={Satellite remote sensing offers an effective remedy to challenges in ground-based and aerial mapping that have previously impeded quantitative assessments of global seagrass extent. Commercial satellite platforms offer fine spatial resolution, an important consideration in patchy seagrass ecosystems. Currently, no consistent protocol exists for image processing of commercial data, limiting reproducibility and comparison across space and time. Additionally, the radiometric performance of commercial satellite sensors has not been assessed against the dark and variable targets characteristic of coastal waters. This study compared data products derived from two commercial satellites: DigitalGlobe's WorldView-2 and Planet's RapidEye. A single scene from each platform was obtained at St. Joseph Bay in Florida, USA, corresponding to a November 2010 field campaign. A reproducible processing regime was developed to transform imagery from basic products, as delivered from each company, into analysis-ready data usable for various scientific applications. Satellite-derived surface reflectances were compared against field measurements. WorldView-2 imagery exhibited high disagreement in the coastal blue and blue spectral bands, chronically overpredicting. RapidEye exhibited better agreement than WorldView-2, but overpredicted slightly across all spectral bands. A deep convolutional neural network was used to classify imagery into deep water, land, submerged sand, seagrass, and intertidal classes. Classification results were compared to seagrass maps derived from photointerpreted aerial imagery. This study offers the first radiometric assessment of WorldView-2 and RapidEye over a coastal system, revealing inherent calibration issues in shorter wavelengths of WorldView-2. Both platforms demonstrated as much as 97% agreement with aerial estimates, despite differing resolutions. Thus, calibration issues in WorldView-2 did not appear to interfere with classification accuracy, but could be problematic if estimating biomass. The image processing routine developed here offers a reproducible workflow for WorldView-2 and RapidEye imagery, which was tested in two additional coastal systems. This approach may become platform independent as more sensors become available.}, journal={REMOTE SENSING OF ENVIRONMENT}, author={Coffer, Megan M. and Schaeffer, Blake A. and Zimmerman, Richard C. and Hill, Victoria and Li, Jiang and Islam, Kazi A. and Whitman, Peter J.}, year={2020}, month={Dec} }
 @article{coffer_schaeffer_darling_urquhart_salls_2020, title={Quantifying national and regional cyanobacterial occurrence in US lakes using satellite remote sensing}, volume={111}, ISSN={["1872-7034"]}, DOI={10.1016/j.ecolind.2019.105976}, abstractNote={Cyanobacterial harmful algal blooms are the most common form of harmful algal blooms in freshwater systems throughout the world. However, in situ sampling of cyanobacteria in inland lakes is limited both spatially and temporally. Satellite data has proven to be an effective tool to monitor cyanobacteria in freshwater lakes across the United States. This study uses data from the European Space Agency Envisat MEdium Resolution Imaging Spectrometer and the Sentinel-3 Ocean and Land Color Instrument to provide a national overview of the percentage of lakes experiencing a cyanobacterial bloom on a weekly basis for 2008–2011, 2017, and 2018. A total of 2321 lakes across the contiguous United States were included in the analysis. We examined four different thresholds to define when a waterbody is classified as experiencing a bloom. Across these four thresholds, we explored variability in bloom percentage with changes in seasonality and lake size. As a validation of algorithm performance, we analyzed the agreement between satellite observations and previously established ecological patterns, although data availability in the wintertime limited these comparisons on a year-round basis. Changes in cyanobacterial bloom percentage at the national scale followed the well-known temporal pattern of freshwater blooms. The percentage of lakes experiencing a bloom increased throughout the year, reached a maximum in fall, and decreased through the winter. Wintertime data, particularly in northern regions, were consistently limited due to snow and ice cover. With the exception of the Southeast and South, regional patterns mimicked patterns found at the national scale. The Southeast and South exhibited an unexpected pattern as cyanobacterial bloom percentage reached a maximum in the winter rather than the summer. Lake Jesup in Florida was used as a case study to validate this observed pattern against field observations of chlorophyll a. Results from this research establish a baseline of annual occurrence of cyanobacterial blooms in inland lakes across the United States. In addition, methods presented in this study can be tailored to fit the specific requirements of an individual system or region.}, journal={ECOLOGICAL INDICATORS}, author={Coffer, Megan M. and Schaeffer, Blake A. and Darling, John A. and Urquhart, Erin A. and Salls, Wilson B.}, year={2020}, month={Apr} }
 @article{coffer_hestir_2019, title={Variability in Trends and Indicators of CO2 Exchange Across Arctic Wetlands}, volume={124}, ISSN={["2169-8961"]}, DOI={10.1029/2018JG004775}, abstractNote={Abstract}, number={5}, journal={JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES}, author={Coffer, Megan M. and Hestir, Erin L.}, year={2019}, month={May}, pages={1248–1264} }