183 research outputs found

    Impact of Atmospheric Correction on Classification and Quantification of Seagrass Density from WorldView-2 Imagery

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    Mapping the seagrass distribution and density in the underwater landscape can improve global Blue Carbon estimates. However, atmospheric absorption and scattering introduce errors in space-based sensorsā€™ retrieval of sea surface reflectance, affecting seagrass presence, density, and above-ground carbon (AGCseagrass) estimates. This study assessed atmospheric correctionā€™s impact on mapping seagrass using WorldView-2 satellite imagery from Saint Joseph Bay, Saint George Sound, and Keaton Beach in Florida, USA. Coincident in situ measurements of water-leaving radiance (Lw), optical properties, and seagrass leaf area index (LAI) were collected. Seagrass classification and the retrieval of LAI were compared after empirical line height (ELH) and dark-object subtraction (DOS) methods were used for atmospheric correction. DOS left residual brightness in the blue and green bands but had minimal impact on the seagrass classification accuracy. However, the brighter reflectance values reduced LAI retrievals by up to 50% compared to ELH-corrected images and ground-based observations. This study offers a potential correction for LAI underestimation due to incomplete atmospheric correction, enhancing the retrieval of seagrass density and above-ground Blue Carbon from WorldView-2 imagery without in situ observations for accurate atmospheric interference correction

    Performance Across Worldview-2 and RapidEye for Reproducible Seagrass Mapping

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    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\u27s WorldView-2 and Planet\u27s 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

    Vertical Artifacts in High-Resolution WorldView-2 and Worldview-3 Satellite Imagery of Aquatic Systems

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    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 DigitalGlobeŹ»s (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-3Ź»s 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 bandsā€”referred to here as the NIR maximum chlorophyll index (MCINIR)ā€”was investigated. Temporally similar imagery from the European Space AgencyŹ»s 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

    Investigation of Heavy Metals in a Large Mortality Event in Caribou of Northern Alaska

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    We measured element concentrations (As, Cd, Cu, Pb, Zn, Fe) and body condition (gross and histologic endpoints) of animals from a caribou (Rangifer tarandus) mortality event that occurred in Alaska, in the area of Point Hope and Cape Thompson (including the Chariot site), in 1995. These were compared to results from hunter-killed caribou from reference sites (Barrow and Teshekpuk Lake, Alaska) and from the area of a mine (Red Dog Mine) to determine whether heavy metals had played a role in the mortality event or whether any elements were at concentrations of concern for human consumers. Starvation and malnutrition were major factors leading to death or severe weakness, as very little or no fat (very low body condition scores) and serous atrophy of fat (observed as watery contents of the marrow cavity, with no apparent fat, and histologically) were more prevalent in caribou associated with the mortality event than in hunter-killed animals from reference sites. Accumulation of hepatic (liver) hemosiderin in Kupffer cells (macrophages) was noted as an indicator of cachexia. Concentrations of lead in feces and liver, copper in the rumen contents, and arsenic in muscle were higher in caribou harvested near Red Dog Mine, as might be expected in that mineral-rich area, but were not at levels of concern for toxicoses. Kidney concentrations of cadmium, which increased significantly with increasing age, present a potential concern for human consumers, and this is an expected finding. We concluded that caribou had starved and that heavy metals had played no role in the mortality event. Further investigation of regional mineral differences is required to understand the sources and transport mechanisms that explain these findings and to properly address mining activity. Mortality events on the north slope of Alaska are common and likely involve starvation as described here, but in most cases they are not investigated, even though recent industrial activities have heightened concern among some local residents and wildlife managers.On a mesurĆ© la concentration en Ć©lĆ©ments (As, Cd, Cu, Pb, Zn, Fe) et l'Ć©tat corporel (points limites bruts et histologiques) de caribous (Rangifer tarandus) prĆ©levĆ©s lors d'un Ć©pisode de mortalitĆ© qui s'est produit en 1995 en Alaska, dans la rĆ©gion de Point Hope et de Cape Thompson (y compris le site Chariot). On a comparĆ© ces rĆ©sultats Ć  ceux de caribous tuĆ©s par des chasseurs Ć  des emplacements tĆ©moins (Barrow et Teshekpuk Lake, en Alaska) et Ć  proximitĆ© d'une mine (Red Dog Mine) pour trouver si les mĆ©taux lourds avaient jouĆ© un rĆ“le dans l'Ć©pisode de mortalitĆ© ou si la concentration d'un ou plusieurs Ć©lĆ©ments pouvait constituer un risque pour la consommation humaine. La famine et la malnutrition Ć©taient des facteurs majeurs ayant causĆ© la mort ou une extrĆŖme faiblesse, vu que la prĆ©sence minime ou l'absence de graisse (trĆØs basses notes d'Ć©tat corporel) et une atrophie sĆ©reuse de la graisse (observĆ©e sous forme de contenu aqueux de la cavitĆ© mĆ©dullaire, sans graisse visible, et Ć  la suite de l'examen histologique) Ć©taient plus courantes chez le caribou associĆ© Ć  l'Ć©pisode de mortalitĆ© que chez les animaux des emplacements tĆ©moins tuĆ©s par les chasseurs. On a notĆ© dans le foie une accumulation d'hĆ©mosidĆ©rine hĆ©patique des cellules de Kupffer (cellules macrophages) tĆ©moignant d'une cachexie. La concentration de plomb dans les matiĆØres fĆ©cales et le foie, de cuivre dans le rumen et d'arsenic dans le tissu musculaire Ć©tait plus Ć©levĆ©e chez le caribou provenant de Red Dog Mine, comme on pouvait s'y attendre dans cette zone riche en minĆ©raux, mais cette concentration n'atteignait pas un niveau pouvant provoquer des toxicoses. La concentration de cadmium dans le rein, qui augmentait de faƧon significative avec l'Ć¢ge, pourrait constituer un risque pour la consommation humaine, ce qui n'est pas surprenant. On a conclu que les caribous Ć©taient morts de faim et que les mĆ©taux lourds n'avaient jouĆ© aucun rĆ“le dans l'Ć©pisode de mortalitĆ©. Il faudrait effectuer des recherches plus poussĆ©es sur les diffĆ©rences rĆ©gionales en minĆ©raux afin de comprendre les mĆ©canismes d'origine et de transport qui expliquent ces rĆ©sultats et d'aborder comme il le faut les activitĆ©s miniĆØres. Les Ć©pisodes de mortalitĆ© sont courants sur le versant Nord de l'Alaska et sont probablement liĆ©s Ć  la famine, comme le dĆ©crit cet article, mais dans la plupart des cas ils ne font pas l'objet d'une enquĆŖte, mĆŖme si l'activitĆ© industrielle rĆ©cente est un sujet qui prĆ©occupe de plus en plus certains rĆ©sidents et gestionnaires locaux de la faune

    Temporal Stability of Seagrass Extent, Leaf Area, and Carbon Storage in St. Joseph Bay, Florida: A Semi-Automated Remote Sensing Analysis

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    Seagrasses are globally recognized for their contribution to blue carbon sequestration. However, accurate quantification of their carbon storage capacity remains uncertain due, in part, to an incomplete inventory of global seagrass extent and assessment of its temporal variability. Furthermore, seagrasses are undergoing significant decline globally, which highlights the urgent need to develop change detection techniques applicable to both the scale of loss and the spatial complexity of coastal environments. This study applied a deep learning algorithm to a 30-year time series of Landsat 5 through 8 imagery to quantify seagrass extent, leaf area index (LAI), and belowground organic carbon (BGC) in St. Joseph Bay, Florida, between 1990 and 2020. Consistent with previous field-based observations regarding stability of seagrass extent throughout St. Joseph Bay, there was no temporal trend in seagrass extent (23ā€‰Ā±ā€‰3 km2, Ļ„ = 0.09, pā€‰=ā€‰0.59, nā€‰=ā€‰31), LAI (1.6ā€‰Ā±ā€‰0.2, Ļ„ = -0.13, pā€‰=ā€‰0.42, nā€‰=ā€‰31), or BGC (165ā€‰Ā±ā€‰19 g C māˆ’2, Ļ„ = - 0.01, pā€‰=ā€‰0.1, nā€‰=ā€‰31) over the 30-year study period. There were, however, six brief declines in seagrass extent between the years 2004 and 2019 following tropical cyclones, from which seagrasses recovered rapidly. Fine-scale interannual variability in seagrass extent, LAI, and BGC was unrelated to sea surface temperature or to climate variability associated with the El NiƱo-Southern Oscillation or the North Atlantic Oscillation. Although our temporal assessment showed that seagrass and its belowground carbon were stable in St. Joseph Bay from 1990 to 2020, forecasts suggest that environmental and climate pressures are ongoing, which highlights the importance of the method and time series presented here as a valuable tool to quantify decadal-scale variability in seagrass dynamics. Perhaps more importantly, our results can serve as a baseline against which we can monitor future change in seagrass communities and their blue carbon

    Simulated Response of St. Joseph Bay, Florida, Seagrass Meadows and Their Belowground Carbon to Anthropogenic and Climate Impacts

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    Seagrass meadows are degraded globally and continue to decline in areal extent due to human pressures and climate change. This study used the bio-optical model GrassLight to explore the impact of climate change and anthropogenic stressors on seagrass extent, leaf area index (LAI) and belowground organic carbon (BGC) in St. Joseph Bay, Florida, using water quality data and remotely-sensed sea surface temperature (SST) from 2002 to 2020. Model predictions were compared with satellite-derived measurements of seagrass extent and shoot density from the Landsat images for the same period. The GrassLight-derived area of potential seagrass habitat ranged from 36.2 km2 to 39.2 km2, averaging 38.0 Ā± 0.8 km2 compared to an observed seagrass extent of 23.0 Ā± 3.0 km2 derived from Landsat (range = 17.9ā€“27.4 km2). GrassLight predicted a mean seagrass LAI of 2.7 m2 leaf māˆ’2 seabed, compared to a mean LAI of 1.9 m2 māˆ’2 estimated from Landsat, indicating that seagrass density in St. Joseph Bay may have been below its light-limited ecological potential. Climate and anthropogenic change simulations using GrassLight predicted the impact of changes in temperature, pH, chlorophyll a, chromophoric dissolved organic matter and turbidity on seagrass meadows. Simulations predicted a 2ā€“8% decline in seagrass extent with rising temperatures that was offset by a 3ā€“11% expansion in seagrass extent in response to ocean acidification when compared to present conditions. Simulations of water quality impacts showed that a doubling of turbidity would reduce seagrass extent by 18% and total leaf area by 21%. Combining climate and water quality scenarios showed that ocean acidification may increase seagrass productivity to offset the negative effects of both thermal stress and declining water quality on the seagrasses growing in St. Joseph Bay. This research highlights the importance of considering multiple limiting factors in understanding the effects of environmental change on seagrass ecosystems

    Assessing karyotype precision by microarray-based comparative genomic hybridization in the myelodysplastic/myeloproliferative syndromes

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    <p>Abstract</p> <p>Background</p> <p>Recent genome-wide microarray-based research investigations have revealed a high frequency of submicroscopic copy number alterations (CNAs) in the myelodysplastic syndromes (MDS), suggesting microarray-based comparative genomic hybridization (aCGH) has the potential to detect new clinically relevant genomic markers in a diagnostic laboratory.</p> <p>Results</p> <p>We performed an exploratory study on 30 cases of MDS, myeloproliferative neoplasia (MPN) or evolving acute myeloid leukemia (AML) (% bone marrow blasts ā‰¤ 30%, range 0-30%, median, 8%) by aCGH, using a genome-wide bacterial artificial chromosome (BAC) microarray. The sample data were compared to corresponding cytogenetics, fluorescence <it>in situ </it>hybridization (FISH), and clinical-pathological findings. Previously unidentified imbalances, in particular those considered submicroscopic aberrations (< 10 Mb), were confirmed by FISH analysis. CNAs identified by aCGH were concordant with the cytogenetic/FISH results in 25/30 (83%) of the samples tested. aCGH revealed new CNAs in 14/30 (47%) patients, including 28 submicroscopic or hidden aberrations verified by FISH studies. Cryptic 344-kb <it>RUNX1 </it>deletions were found in three patients at time of AML transformation. Other hidden CNAs involved 3q26.2/EVI1, 5q22/APC, 5q32/TCERG1,12p13.1/EMP1, 12q21.3/KITLG, and 17q11.2/NF1. Gains of CCND2/12p13.32 were detected in two patients. aCGH failed to detect a balanced translocation (n = 1) and low-level clonality (n = 4) in five karyotypically aberrant samples, revealing clinically important assay limitations.</p> <p>Conclusions</p> <p>The detection of previously known and unknown genomic alterations suggests that aCGH has considerable promise for identification of both recurring microscopic and submicroscopic genomic imbalances that contribute to myeloid disease pathogenesis and progression. These findings suggest that development of higher-resolution microarray platforms could improve karyotyping in clinical practice.</p

    Providing a Framework for Seagrass Mapping in United States Coastal Ecosystems Using High Spatial Resolution Satellite Imagery

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    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\u27s 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

    Evaluation of chronic lymphocytic leukemia by oligonucleotide-based microarray analysis uncovers novel aberrations not detected by FISH or cytogenetic analysis

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    <p>Abstract</p> <p>Background</p> <p>Cytogenetic evaluation is a key component of the diagnosis and prognosis of chronic lymphocytic leukemia (CLL). We performed oligonucleotide-based comparative genomic hybridization microarray analysis on 34 samples with CLL and known abnormal karyotypes previously determined by cytogenetics and/or fluorescence <it>in situ </it>hybridization (FISH).</p> <p>Results</p> <p>Using a custom designed microarray that targets >1800 genes involved in hematologic disease and other malignancies, we identified additional cryptic aberrations and novel findings in 59% of cases. These included gains and losses of genes associated with cell cycle regulation, apoptosis and susceptibility loci on 3p21.31, 5q35.2q35.3, 10q23.31q23.33, 11q22.3, and 22q11.23.</p> <p>Conclusions</p> <p>Our results show that microarray analysis will detect known aberrations, including microscopic and cryptic alterations. In addition, novel genomic changes will be uncovered that may become important prognostic predictors or treatment targets for CLL in the future.</p
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