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On the Advantages of Using Harmonized Landsat Sentinel-2 Data for Monitoring Environmental Change

NASA coordinates the Satellite Needs Working Group, dedicated to identifying, communicating, and addressing Earth observation needs of federal agencies. In 2016, the Harmonized Landsat Sentinel-2 (HLS) dataset was formulated and implemented to fulfill multiple needs. The combination of acquisitions from the Landsat and Sentinel-2 platforms results in a global dataset of surface reflectance with a temporal resolution of two days, while retaining the geometry and 30-meter spatial resolution of Landsat data. This harmonization allows for seamless integration with the 40-year archive of Landsat data. The HLS dataset is now available on the Google Earth Engine, enabling HLS utilization in various algorithms and frameworks essential for monitoring environmental change worldwide. During this presentation, we will demonstrate and discuss the advantages of using HLS data in comparison to using separate streams of Landsat and Sentinel-2 data in existing time series-based frameworks for change monitoring. Specifically, we will explore the application of HLS for continuous monitoring of deforestation using time series-based algorithms traditionally run with Landsat data. Additionally, we will showcase the benefits of HLS data for near real-time monitoring of forest disturbance in tropical regions. These examples underscore the value and utility of the HLS dataset for environmental monitoring and analysis.

Pontus Olofsson↗
NASA NTRS2024

Sentinel-1 Snow Depth Assimilation to Improve River Discharge Estimates in the Western European Alps

Seasonal snow is an important water source and contributor to river discharge in mountainous regions. Therefore the amount of snow and its distribution are necessary inputs for hydrological modeling. Recent research has shown the potential of the Sentinel-1 radar satellite to map snow depth (SD) at sub-kilometer resolution in mountainous regions. In this study we assimilate these new SD retrievals into the Noah-Multiparameterization land surface model using an ensemble Kalman filter for the western European Alps. The land surface model was coupled to the Hydrological Modeling and Analysis Platform (HyMAP), a global flow routing scheme that provides simulations of routed river discharge. The performance with different precipitation forcing inputs, namely MERRA-2 (with and without gauge based correction) and ERA5, was compared based on in situ precipitation and SD stations, with ERA5 leading to the best SD performance. The Sentinel-1 based data assimilation (DA) results show small but systematic improvements for SD estimates, with the mean absolute error reducing from 36.4 cm for the open loop (OL) to 35.6 cm for the DA across all stations and timesteps, improving 318 out of 516 in situ sites. The DA updates in SD also result in enhanced snow water equivalent and discharge simulations. The median temporal correlation between discharge simulations and measurements increases from 0.73 to 0.78 for the DA. This study demonstrates the utility of the Sentinel-1 SD retrievals to improve not only the representation of snow in mountain ranges, but also the snow melt contribution to river discharge, and hydrological modeling in general.

Isis Brangers↗
DOE OSTI2016

Sensor sentinel computing device

Technologies pertaining to authenticating data output by sensors in an industrial environment are described herein. A sensor sentinel computing device receives time-series data from a sensor by way of a wireline connection. The sensor sentinel computing device generates a validation signal that is a function of the time-series signal. The sensor sentinel computing device then transmits the validation signal to a programmable logic controller in the industrial environment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Applicability of Sentinel-1 Terrain Observation by Progressive Scans multitemporal interferometry for monitoring slow ground motions in the San Francisco Bay Area

Data from the Sentinel-1 satellite have already proven useful for investigating seismic and volcanic events since its launch in April 2014. The requirement of ultrahigh coregistration accuracy and the current relatively short time of Sentinel-1 acquisitions make its application challenging for studying slow deformation processes, such as fault creep and land subsidence. Here in this paper we analyze a set of 14 SAR images over the San Francisco Bay Area spanning 1 year from early 2015 to 2016. We show that implementing an existing Enhanced Spectral Diversity algorithm or using precise orbits together with a reference digital elevation model both yield the required coregistration accuracy for making use of the phase measurements in time series analysis of ground deformation. Following a thorough validation test, we update our estimates of Hayward Fault creep rate and confirm uplift due to recharge of the Santa Clara Valley aquifer system during the final summer of 4 year drought.

58 GEOSCIENCES↗
DOE OSTI2020

Evaluation of camera-based freehand SPECT in preoperative sentinel lymph node mapping for melanoma patients

Assessment of lymphatic status via sentinel lymph node (SLN) biopsy is an integral and crucial part of melanoma surgical oncology. The most common technique for sentinel node mapping is preoperative planar scintigraphy of an injected gamma-emitting lymphatic tracer followed by intraoperative node localization using a non-imaging gamma probe with auditory feedback. In recent years, intraoperative visualization of SLNs in 3D has become possible by coupling the probe to an external system capable of tracking its location and orientation as it is read out, thereby enabling computation of the 3D distribution of the tracer (freehand SPECT). In this project, the non-imaging probe of the fhSPECT system was replaced by a unique handheld gamma camera containing an array of sodium iodide crystals optically coupled to an array of silicon photomultipliers (SiPMs). A feasibility study was performed in which preoperative SLN mapping was performed using camera fhSPECT and the number of detected nodes was compared to that visualized by lymphoscintigraphy, probe fhSPECT, and to the number ultimately excised under non-imaging probe guidance. Among five subjects, SLNs were detected in nine lymphatic basins, with one to five SLNs detected per basin. A basin-by-basin comparison showed that the number of SLNs detected using camera fhSPECT exceeded that using lymphoscintigraphy and probe fhSPECT in seven of nine basins and five of five basins, respectively. (Probe fhSPECT scans were not performed for four basins.) It exceeded the number excised under non-imaging probe guidance for seven of nine basins and equaled the number excised for the other two basins. Freehand SPECT using a prototype SiPM-based gamma camera demonstrates high sensitivity for detection of SLNs in a preoperative setting. Camera fhSPECT is a potential means for efficiently obtaining real-time 3D activity distribution maps in applications such as image-guided percutaneous biopsy, and surgical SLN biopsy or radioguided tumor excision.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Envisat Track 349 and Sentinel-1A Track 64 Interferometric Synthetic Aperture Radar Data of Coso Geothermal Field, California, USA, 2004-2016

This submission contains tarred pair directories for interferometric synthetic aperture radar (InSAR) data covering Coso Geothermal Field in California, USA. Explanation of pair subdirectories: Pairs are formed using the InSAR processing software GMT5SAR (Sandwell et al., 2011). Pair subdirectories are named by starting and ending epochs in YYYYMMDD_YYYYMMDD format. Each tarred pair directory contains GRD files for phase data (radians), unwrapped range change (drhomaskd, in m), and unwrapped range change rate (drange, in m/yr). The data are given in both latitude/longitude and Universal Transverse Mercator (Zone 11N). Raw Synthetic Aperture Radar (SAR) data from the Envisat satellite mission operated by the European Space Agency (ESA) are copyrighted by ESA and were provided through the WInSAR consortium at the UNAVCO facility. Raw Synthetic Aperture Radar (SAR) data from the Sentinel-1A satellite mission operated by ESA were available free of charge through the Distributed Active Archive Center (DAAC) at the Alaska Satellite Facility (ASF) and through the Sentinels Scientific Data Hub. References: Farr, T.G.; Rosen, P.A.; Caro, E.; Crippen, R.; Duren, R.; Hensley, S.; Kobrick, M.; Paller, M.; Rodriguez, E.; Roth, L.; Seal, D.; Shaffer, S.; Shimada, J.; Umland, J.; Werner, M.; Oskin, M.; Burbank, D.; Alsdorf, D. The Shuttle Radar Topography Mission. Reviews of Geophysics 2007, 45, RG2004. doi:10.1029/2005RG000183. Sandwell, D.; Mellors, R.; Tong, X.; Wei, M.; Wessel, P. Open radar interferometry software for mapping surface deformation. Eos, Transactions American Geophysical Union 2011, 92, 234?234. http://dx.doi.org/10.1029/2011EO280002. doi:10.1029/2011EO280002.

15 GEOTHERMAL ENERGY↗
NASA NTRS2017

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

Cropland mapping; cropland areas; 30-m; Landsat-8;↗
NASA NTRS2018

Toward Landsat and Sentinel-2 BRDF Normalization and Albedo Estimation: A Case Study in the Peruvian Amazon Forest

The Amazon forest has been the focus of study by the science community during the last few decades. Remote sensing data analysis is the only way to study such a large geographical extent during an extended period of time. Since the launch in 2015 of Sentinel 2 and its increase in temporal resolution through the combination with Landsat sensors, a strong emphasis has been put on exploiting these data. Though these satellites provide near nadir observations, surface reflectance time series are affected by illumination variability throughout the year. These effects can be corrected using a Bidirectional Reflectance Distribution Function (BRDF) model. Franch et al. (2014a) developed a methodology to derive Landsat surface albedo and BRDF. It is based on the BRDF parameters from the MODerate Resolution Imaging Spectroradiometer (MODIS) which are disaggregated at Landsat spatial resolution (30 m). In this work, we apply the Franch et al. (2014a) method to normalize the surface reflectance for BRDF effects using the NASA's Harmonized Landsat Sentinel-2 (HLS) product. We apply this method to the Tambopata region in Peru from 2013 to 2017 and validate it using ground-based albedometer measurements. The results show that the near infrared reflectance can increase up to 0.06 (20%) for low solar angles while the impact on the red range and the NDVI is minor (<0.01). The evaluation of the surface albedo against field measurements shows an error of 0.01.

Landsat 8↗
NASA NTRS2019

Performance of Landsat-8 and Sentinel-2 Surface Reflectance Products for River Remote Sensing Retrievals of Chlorophyll-A and Turbidity

Rivers and other freshwater systems play a crucial role in ecosystems, industry, transportation and agriculture. Despite the more than 40 years of inland water observations made possible by optical remote sensing, a standardized reflectance product for inland waters is yet forthcoming. The aim of this work is to compare the standard USGS land surface reflectance product to two Landsat-8 and Sentinel-2 aquatic remote sensing reflectance products over the Amazon, Columbia and Mississippi rivers. Landsat-8 reflectance products from all three routines are then evaluated for their comparative performance in retrieving chlorophyll-a and turbidity in reference to shipborne, underway in situ validation measurements. The land surface product shows the best agreement (4 percent Mean Absolute Percent Difference) with field measurements of radiometry collected on the Amazon River and generates 36 percent higher reflectance values in the visible bands compared to aquatic methods (ACOLITE (Atmospheric Correction for OLI (Operational Land Imager) 'lite') and SeaDAS (Sea-viewing Wide Field-of-View Sensor (SeaWiFS) Data Analysis System)) with larger differences between land and aquatic products observed in Sentinel-2 (0.01 per steraradian) compared to Landsat-8 (0.001 per steraradian). Choice of atmospheric correction routine can bias Landsat-8 retrievals of chlorophyll-a and turbidity by as much as 59 percent and 35 percent respectively. Using a more restrictive time window for matching in situ and satellite imagery can reduce differences by 5–31 percent depending on correction technique. This work highlights the challenges of satellite retrievals over rivers and underscores the need for future optical and biogeochemical research aimed at improving our understanding of the absorbing and scattering properties of river water and their relationships to remote sensing reflectance.

Landsat-8↗
NASA NTRS2019

Winter Wheat Yield Assessment from Landsat 8 and Sentinel-2 Data: Incorporating Surface Reflectance, Through Phenological Fitting, into Regression Yield Models

A combination of Landsat 8 and Sentinel-2 offers a high frequency of observations (3–5 days) at moderate spatial resolution (10–30 m), which is essential for crop yield studies. Existing methods traditionally apply vegetation indices (VIs) that incorporate surface reflectances (SRs) in two or more spectral bands into a single variable, and rarely address the incorporation of SRs into empirical regression models of crop yield. In this work, we address these issues by normalizing satellite data (both VIs and SRs) derived from NASA’s Harmonized Landsat Sentinel-2 (HLS) product, through a phenological fitting. We apply a quadratic function to fit VIs or SRs against accumulated growing degree days (AGDDs), which affects the rate of crop development. The derived phenological metrics for VIs and SRs, namely peak, area under curve (AUC), and fitting coefficients from a quadratic function, were used to build empirical regression winter wheat models at a regional scale in Ukraine for three years, 2016–2018. The best results were achieved for the model with near infrared (NIR) and red spectral bands and derived AUC, constant, linear, and quadratic coefficients of the quadratic model. The best model yielded a root mean square error (RMSE) of 0.201 t/ha (5.4%) and coefficient of determination R2 = 0.73 on cross-validation.

phenological fitting↗
NASA NTRS2023

Estimating the concentration of total suspended solids in inland and coastal waters from Sentinel-2 MSI: A semi-analytical approach

Inland and coastal waters provide key ecosystem services and are closely linked to human well-being. In this study, we propose a semi-analytical method, which can be applied to Sentinel-2 MultiSpectral Instrument (MSI) images to retrieve high spatial-resolution total suspended solids (TSS) concentration in a broad spectrum of aquatic ecosystems ranging from clear to extremely turbid waters. The presented approach has four main steps. First, the remote sensing reflectance ( R rs ) at a band lacking in MSI (620 nm) is estimated through an empirical relationship from R rs at 665 nm. Second, waters are classified into four types (clear, moderately turbid, highly turbid, and extremely turbid). Third, semi-analytical algorithms are used to estimate the particulate backscattering coefficient ( b bp ) at a reference band depending on the water types. Last, TSS is estimated from bbp at the reference band. Validation and comparison of the proposed method with three existing methods are performed using a simulated dataset ( N = 1000), an in situ dataset collected from global inland and coastal waters ( N = 1265) and satellite matchups ( N = 40). Results indicate that the proposed method can improve TSS estimation and provide accurate retrievals of TSS from all three datasets, with a median absolute percentage error (MAPE) of 14.88 %, 31.50 % and 41.69 % respectively. We also present comparisons of TSS mapping between the Sentinel-3 Ocean and Land Colour Instrument (OLCI) and MSI in Lake Kasumigaura, Japan and the Tagus Estuary, Portugal. Results clearly demonstrate the advantages of using MSI for TSS monitoring in small water bodies such as rivers, river mouths and other nearshore waters. MSI can provide more detailed and realistic TSS estimates than OLCI in these water bodies. The proposed TSS estimation method was applied to MSI images to produce TSS time-series in Lake Kasumigaura, which showed good agreements with in situ and OLCI-derived TSS time-series.

Sentinel-2↗
DOE OSTI2016

U.S. domestic cats as sentinels for perfluoroalkyl substances: Possible linkages with housing, obesity, and disease

Perfluoroalkyl substances (PFAS), such as perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are persistent, globally distributed, anthropogenic compounds. The primary source(s) for human exposure are not well understood although within home exposure is likely important since many consumer products have been treated with different PFAS, and people spend much of their lives indoors. Herein, domestic cats were used as sentinels to investigate potential exposure and health linkages. PFAS in serum samples of 72 pet and feral cats, including 11 healthy and 61 with one or more primary disease diagnoses, were quantitated using high-resolution time-of-flight mass spectroscopy. All but one sample had detectable PFAS, with PFOS and perfluorohexane sulfonate (PFHxS) ranging from <LOQ to 121 and <LOQ to 235 ng/mL, respectively. PFAS prevalence and geometric means in cats were very similar to contemporary NHANES reports of human sera in the U. S. population. The highest PFAS serum concentrations detected were in indoor cats due to disproportionately elevated PFHxS levels. Ranked by quartile, contingency testing indicated that total PFAS levels were positively associated with living indoors and with higher body weight and body condition scores. Individual PFAS quartile rankings suggested positive associations with respiratory effusion, thyroid, liver, and possibly chronic kidney disease. Domestic cats appear to be useful sentinels for assessing primary PFAS exposure routes, especially indoor sources of relevance to children. Additional case-control studies in pet cats are warranted to better define the potential health associations observed herein. A “One Health” approach assessing humans, pets, and their common environment may improve our understanding of chronic low-level, largely indoor, PFAS exposure and effects in humans and animals alike. - Highlights: • PFAS serum concentrations were measured in healthy and diseased U. S. domestic cats. • Most abundant were PFOS (range < LOQ to 121) and PFHxS (< LOQ to 235 ng/mL). • PFAS geometric means were very similar to that reported in U.S. human sera by NHANES. • Higher ΣPFAS levels were positively associated with living indoors and with obesity. • Associations with lung, liver, thyroid, or kidney disease may guide future studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Performance of Landsat-8 and Sentinel-2 surface reflectance products for river remote sensing retrievals of chlorophyll-a and turbidity

Rivers and other freshwater systems play a crucial role in ecosystems, industry, transportation and agriculture. Despite the > 40 years of inland water observations made possible by optical remote sensing, a standardized reflectance product for inland waters is yet forthcoming. The aim of this work is to compare the standard USGS land surface reflectance product to two Landsat-8 and Sentinel-2 aquatic remote sensing reflectance products over the Amazon, Columbia and Mississippi rivers. Landsat-8 reflectance products from all three routines are then evaluated for their comparative performance in retrieving chlorophyll-a and turbidity in reference to ship- borne, underway in situ validation measurements. The land surface product shows the best agreement (4% Mean Absolute Percent Difference) with field measurements of radiometry collected on the Amazon River and gen- erates 36% higher reflectance values in the visible bands compared to aquatic methods (ACOLITE and SeaDAS) with larger differences between land and aquatic products observed in Sentinel-2 (0.01sr-1) compared to Landsat-8 (0.001 sr-1). Choice of atmospheric correction routine can bias Landsat-8 retrievals of chlorophyll-a and turbidity by as much as 59% and 35% respectively. Using a more restrictive time window for matching in situ and satellite imagery can reduce differences by 5–31% depending on correction technique. This work highlights the challenges of satellite retrievals over rivers and underscores the need for future optical and biogeochemical research aimed at improving our understanding of the absorbing and scattering properties of river water and their relationships to remote sensing reflectance.

Amazon↗
DOE OSTI2016

Experimental study of {sup 99m}Tc-aluminum oxide use for sentinel lymph nodes detection

The purpose of the study was a comparative research in the possibility of using the radiopharmaceuticals {sup 99m}Tc-Al{sub 2}O{sub 3} and {sup 99m}Tc-Nanocis for visualizing sentinel lymph nodes. The measurement of the sizes of {sup 99m}Tc-Al{sub 2}O{sub 3} and {sup 99m}Tc-Nanocis colloidal particles was performed in seven series of radiopharmaceuticals. The pharmacokinetics of {sup 99m}Tc-Al{sub 2}O{sub 3} and {sup 99m}Tc-Nanocis was researched on 50 white male rats. The possibility of the use of {sup 99m}Tc-Al{sub 2}O{sub 3} and {sup 99m}Tc-Nanocis for lymphoscintigraphy was studied in the experiments on 12 white male rats. The average dynamic diameter of the sol particle was 52–77 nm for {sup 99m}Tc-Al{sub 2}O{sub 3} and 16.7–24.5 nm for {sup 99m}Tc-Nanocis. Radiopharmaceuticals accumulated in the inguinal lymph node in 1 hour after administration; the average uptake of {sup 99}mTc-Al{sub 2}O{sub 3} was 8.6% in it, and the accumulation of {sup 99m}Tc-Nanocis was significantly lower—1.8% (p < 0.05). In all study points the average uptake of {sup 99m}Tc-Al{sub 2}O{sub 3} in the lymph node was significantly higher than {sup 99m}Tc-Nanocis accumulation. The results of dynamic scintigraphic studies in rats showed that {sup 99m}Tc-Al{sub 2}O{sub 3} and {sup 99m}Tc-Nanocis actively accumulated into the lymphatic system. By using {sup 99m}Tc-Al{sub 2}O{sub 3} inguinal lymph node was determined in 5 minutes after injection and clearly visualized in all the animals in the 15th minute, when the accumulation became more than 1% of the administered dose. Further observation indicated that the {sup 99m}Tc-Al{sub 2}O{sub 3} accumulation reached a plateau in a lymph node (average 10.5%) during 2-hour study and then its accumulation remained practically at the same level, slightly increasing to 12% in 24 hours. In case of {sup 99m}Tc-Nanocis inguinal lymph node was visualized in all animals for 15 min when it was accumulated on the average 1.03% of the administered dose. Plateau of {sup 99m}Tc-Nanocis accumulation in the lymph node (average 2.05%) occurred after 2 hours of the study and remained almost on the same level (in average 2.3%) for 24 hours. Thus, the experimental study of a new domestic radiopharmaceutical showed that the {sup 99m}Tc-Al{sub 2}O{sub 3} accumulates actively in the lymph nodes several times as compared to the imported analogue and its practical application will facilitate intraoperative identification of sentinel lymph nodes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

The use of {sup 99m}Tc-Al{sub 2}O{sub 3} for detection of sentinel lymph nodes in breast cancer

Purpose: to study the feasibility of using the new radiopharmaceutical based on the technetium-99m-labeled gamma-alumina for identification of sentinel lymph nodes (SLNs) in breast cancer patients. The study included two groups of breast cancer patients who underwent single photon emission computed tomography (SPECT) and intraoperaive gamma probe identification of sentinel lymph nodes (SLNs). To identify SLNs, the day before surgery Group I patients (n = 34) were injected with radioactive {sup 99m}Tc-Al{sub 2}O{sub 3}, and Group II patients (n = 30) received {sup 99m}Tc-labeled phytate colloid. A total of 37 SLNs were detected in Group I patients. The number of identified SLNs per patient ranged from 1 to 2 (the average number of identified SLNs was 1.08). Axillary lymph nodes were the most common site of SLN localization. 18 hours after {sup 99m}Tc-Al{sub 2}O{sub 3} injection, the percentage of its accumulation in the SLN was 7–11% (of the counts in the injection site) by SPECT and 17–31% by gamma probe detection. In Group II SLNs were detected in 27 patients. 18 hours after injection of the phytate colloid the percentage of its accumulation in the SLN was 1.5–2% out of the counts in the injection site by SPECT and 4–7% by gamma probe. The new radiopharmaceutical based on the {sup 99m}Tc-Al{sub 2}O{sub 3} demonstrates high accumulation in SLNs without redistribution through the entire lymphatic basin. The sensitivity and specificity of {sup 99m}Tc-Al{sub 2}O{sub 3} were 100% for both SPECT and intraoperative gamma probe identification.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Sentinel

Network intrusion detection systems (NIDS) are commonplace in network security but they frequently employ algorithms that are computational demanding requiring hardware and software with significant power requirements. Two examples of such resource-intensive algorithms used for network security are regular expression matching and broader signature pattern matching which are commonly used in deep packet inspection (DPI). Network security algorithms that have large power requirements may be a challenge for low-power internet-of-things (IoT) environments, which generally lack the power resources to implement complex security measures like computationally expensive DPI at the edge. Furthermore, IoT environments incorporating 5G standalone networks have network latency constraints beyond just power that make DPI at the edge even more difficult. Programmable logic is ideally suited for machine learning inference for DPI because of its deep instruction level parallelism and single-cycle memory access. Machine learning approaches for DPI have been explored before using the programmable logic of field programmable gate arrays (FPGA) as a potential solution for NIDS approaches that would be power-suitable for IoT. However, those previous programmable logic NIDS approaches utilize either a supervised or unsupervised learning model. Sentinel utilizes the ensemble of these two machine learning approaches known as a semi-supervised approach which has shown promise in NIDS implementations. Sentinel provides a programmable logic implementation of a semi-supervised approach for DPI which operates at much lower power and latency than a GPU implementation with negligible loss of accuracy due to quantization through a logistic regressor.

Anderson, MatthewW [Idaho National Laboratory (INL↗
DOE OSTI2019

Internal Mammary Chain Sentinel Nodes in Early-Stage Breast Cancer Patients: Toward Selective Removal

Background: Removal of internal mammary chain sentinel nodes (IMCSNs) affects prognosis and treatment of breast cancer, and internal mammary chain radiotherapy (IMCRT) can improve survival for selected patients. This study aimed to determine the effect of IMCSN biopsy on recurrence-free survival (RFS) and overall survival (OS) and to identify predictive factors for IMCSN and distant metastasis. Methods: Patients with IMCSNs were selected from a prospective database for the period 1999–2007. Lymphoscintigraphy was performed after intratumoral technetium-99 m injection, and all sentinel nodes were removed. Both RFS and OS were calculated for subgroups with tumor-positive, tumor-negative, or non-removed IMCSNs. Predictive factors were identified for tumor-positive IMCSNs and distant metastasis by regression analysis. Results: For 287 (85%) of 336 patients, IMCSN biopsy was performed, and metastasis was detected in 38 patients (13%). The patients with tumor-positive IMCSNs had poorer OS than the patients with no IMCSN metastasis or non-removed IMCSNs (p = 0.002). These patients also had worse RFS due to distant metastasis (p = 0.002). Axillary metastasis was predictive for tumor-positive IMCSNs (positive predictive value, 38.5%). The predictive factors for distant metastasis were tumor-positive IMCSNs (hazard ratio [HR], 2.5), non-removed IMCSNs (HR, 2.3), tumor diameter greater than 1.5 cm (HR, 3.5), and age older than 65 years (HR, 3.1; reference, < 50 years). Conclusions: Patients with IMCSNs have worse survival due to distant metastasis. The clinically relevant predictive factor for distant metastasis is tumor larger than 1.5 cm. According to the authors’ current protocol, IMCSN biopsy is performed for patients younger than 70 years who have a tumor larger than 1.5 cm, with the cardiotoxicity of the adjuvant IMCRT weighed against the survival benefit.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Validation of the Sentinel-5 Precursor TROPOMI cloud data with Cloudnet, Aura OMI O 2 –O 2 , MODIS, and Suomi-NPP VIIRS

Accurate knowledge of cloud properties is essential to the measurement of atmospheric composition from space. In this work we assess the quality of the cloud data from three Copernicus Sentinel-5 Precursor (S5P) TROPOMI cloud products: (i) S5P OCRA/ROCINN_CAL (Optical Cloud Recognition Algorithm/Retrieval of Cloud Information using Neural Networks;Clouds-As-Layers), (ii) S5P OCRA/ROCINN_CRB (Clouds-as-Reflecting Boundaries), and (iii) S5P FRESCO-S (Fast Retrieval Scheme for Clouds from Oxygen absorption bands – Sentinel). Target properties of this work are cloud-top height and cloud optical thickness (OCRA/ROCINN_CAL), cloud height (OCRA/ROCINN_CRB and FRESCO-S), and radiometric cloud fraction (all three algorithms). The analysis combines (i) the examination of cloud maps for artificial geographical patterns, (ii) the comparison to other satellite cloud data (MODIS, NPP-VIIRS, and OMI O2–O2), and (iii) ground-based validation with respect to correlative observations (30 April 2018 to 27 February 2020) from the Cloudnet network of ceilometers, lidars, and radars. Zonal mean latitudinal variation of S5P cloud properties is similar to that of other satellite data. S5P OCRA/ROCINN_CAL agrees well with NPP VIIRS cloud-top height and cloud optical thickness and with Cloudnet cloud-top height, especially for the low (mostly liquid) clouds. For the high clouds, S5P OCRA/ROCINN_CAL cloud-top height is below the cloud-top height of VIIRS and of Cloudnet, while its cloud optical thickness is higher than that of VIIRS. S5P OCRA/ROCINN_CRB and S5P FRESCO cloud height are well below the Cloudnet cloud mean height for the low clouds but match on average better with the Cloudnet cloud mean height for the higher clouds. As opposed to S5P OCRA/ROCINN_CRB and S5P FRESCO, S5P OCRA/ROCINN_CAL is well able to match the lowest CTH mode of the Cloudnet observations. Peculiar geographical patterns are identified in the cloud products and will be mitigated in future releases of the cloud data products.

54 ENVIRONMENTAL SCIENCES↗