Miracle-dz/UniFAR-FTUs huggingface dataset:
Long-Term Snow Height Variations in Antarctica from GNSS Interferometric Reflectometry

Acquiring reliable estimates of the Antarctic Ice Sheet surface mass balance is essential for trustworthy predictions of its evolution and future contribution to sea level rise. Snow height variations, i.e., the net change of the surface elevation resulting from a combination of surface processes such as snowfall, ablation, and wind redistribution, can provide a unique tool to constrain the uncertainty on mass budget estimations. In this study, GNSS Interferometric Reflectometry (GNSS-IR) is exploited to assess the long-term variations of snow accumulation and ablation processes. Eight antennas belonging to the Polar Earth Observing Network (POLENET) network are considered, together with the ROB1 antenna, deployed in the east part of Antarctica by the Royal Observatory of Belgium. For ROB1, which is located on an ice rise, we highlight an annual variation of snow accumulation in April–May (~30–50 cm) and ablation during spring/summer period. A snow surface elevation velocity of +0.08 ± 0.01 ma−1 is observed in the 2013–2016 period, statistically rejecting the “no trend” null hypothesis. As the POLENET stations are all located on moving glaciers, their associated downhill motion must be corrected for using an elevation model. This induces an increased uncertainty on the snow surface elevation change determined from GNSS-IR. Among the eight stations analyzed, only three of them show a long-term snow height variation larger than the uncertainties. One is located on the Flask Galcier in the Antarctic Peninsula, with a decrease of more than 4 m between 2012 and 2014, with an uncertainty of 2.5 m. The second one is located on the Lower Thwaites Glacier where we observe, between 2010 and 2020, a snow surface drop of 10 m, with a conservative uncertainty of 1 m. The third station, located on the West Antarctic Ice Sheet (WAIS) divide, shows on the opposite an upward motion from 2005 to 2019, of 1.2 m with an uncertainty of 0.4 m. The snow surface change of the other POLENET stations analyzed is smaller than the uncertainty associated with the glacier slope.
Building Extraction and Number Statistics in WUI Areas Based on UNet Structure and Ensemble Learning

Following the advancement and progression of urbanization, management problems of the wildland–urban interface (WUI) have become increasingly serious. WUI regional governance issues involve many factors including climate, humanities, etc., and have attracted attention and research from all walks of life. Building research plays a vital part in the WUI area. Building location is closely related with the planning and management of the WUI area, and the number of buildings is related to the rescue arrangement. There are two major methods to obtain this building information: one is to obtain them from relevant agencies, which is slow and lacks timeliness, while the other approach is to extract them from high-resolution remote sensing images, which is relatively inexpensive and offers improved timeliness. Inspired by the recent successful application of deep learning, in this paper, we propose a method for extracting building information from high-resolution remote sensing images based on deep learning, which is combined with ensemble learning to extract the building location. Further, we use the idea of image anomaly detection to estimate the number of buildings. After verification on two datasets, we obtain superior semantic segmentation results and achieve better building contour extraction and number estimation.
Retracking Cryosat-2 Data in SARIn and LRM Modes for Plateau Lakes: A Case Study for Tibetan and Dianchi Lakes

This paper estimates lake level variations over two small and adjacent lakes in the Tibetan plateau (TP), namely Gemang Co and Zhangnai Co, as well as the inland Dianchi Lake in China using CryoSat-2 SARIn-mode and LRM 20-Hz waveforms over the period of 2011–2018. Different retrackers and a dedicated data editing procedure have been used to process CryoSat-2 data for determining the lake level time series. The lake level estimations are indirectly validated against those from Jason-2 in TP and from in situ data in Dianchi Lake, both showing good agreement with strong correlation coefficients >0.74. The results of this paper suggest that the official ICE retracker for LRM data and APD-PPT retracker for SARIn-mode waveforms are the most appropriate retrackers over Dianchi Lake and TP lakes, respectively. The trend estimates of the time series derived by both retrackers are 61.0 ± 10.8 mm/yr for Gemang Co and Zhangnai Co in TP, and 30.9 ± 64.9 mm/yr for Dianchi Lake, indicating that the lake levels over three lakes were continuously rising over the study period. The results of this study show that CryoSat-2 SARIn-mode data can be used for monitoring many small lakes that have not been measured by other altimetry missions in TP.
Google Earth Engine Sentinel-3 OLCI Level-1 Dataset Deviates from the Original Data: Causes and Consequences

In this study, we demonstrate that the Google Earth Engine (GEE) dataset of Sentinel-3 Ocean and Land Color Instrument (OLCI) level-1 deviates from the original Copernicus Open Access Data Hub Service (DHUS) data by 10–20 W m−2 sr−1μμm−1 per pixel per band. We compared GEE and DHUS single pixel time series for the period from April 2016 to September 2020 and identified two sources of this discrepancy: the ground pixel position and reprojection. The ground pixel position of OLCI product can be determined in two ways: from geo-coordinates (DHUS) or from tie-point coordinates (GEE). We recommend using geo-coordinates for pixel extraction from the original data. When the Sentinel Application Platform (SNAP) Pixel Extraction Tool is used, an additional distance check has to be conducted to exclude pixels that lay further than 212 m from the point of interest. Even geo-coordinates-based pixel extraction requires the homogeneity of the target area at a 700 m diameter (49 ha) footprint (double of the pixel resolution). The GEE OLCI dataset can be safely used if the homogeneity assumption holds at 2700 m diameter (9-by-9 OLCI pixels) or if the uncertainty in the radiance of 10% is not critical for the application. Further analysis showed that the scaling factors reported in the GEE dataset description must not be used. Finally, observation geometry and meteorological data are not present in the GEE OLCI dataset, but they are crucial for most applications. Therefore, we propose to calculate angles and extraterrestrial solar fluxes and to use an alternative data source—the Copernicus Atmosphere Monitoring Service (CAMS) dataset—for meteodata.
An Oil Well Dataset Derived from Satellite-Based Remote Sensing

Estimation of the number and geo‐location of oil wells is important for policy holders considering their impact on energy resource planning. With the recent development in optical re‐ mote sensing, it is possible to identify oil wells from satellite images. Moreover, the recent advance‐ ment in deep learning frameworks for object detection in remote sensing makes it possible to auto‐ matically detect oil wells from remote sensing images. In this paper, we collected a dataset named Northeast Petroleum University–Oil Well Object Detection Version 1.0 (NEPU–OWOD V1.0) based on high‐resolution remote sensing images from Google Earth Imagery. Our database includes 1192 oil wells in 432 images from Daqing City, which has the largest oilfield in China. In this study, we compared nine different state‐of‐the‐art deep learning models based on algorithms for object detec‐ tion from optical remote sensing images. Experimental results show that the state‐of‐the‐art deep learning models achieve high precision on our collected dataset, which demonstrate the great po‐ tential for oil well detection in remote sensing.
We're Lost, But We are Making Good Time: Navigating Complex Pathways in a Patient-Order Management Task

Patient order management (POM) is a mission-critical task for perioperative workflow. Interface complexity within different EHR systems result in poor usability, increasing documentation burden. POM interfaces were compared across two systems prior to (Cerner SurgiNet) and subsequent to an EHR conversion (Epic). Here we employ a navigational complexity framework useful for examining differences in EHR interface systems. The methodological approach includes 1) expert-based methods-specifically, functional analysis, keystroke level model (KLM) and cognitive walkthrough, and 2) quantitative analysis of observed interactive user behaviors. We found differences in relation to navigational complexity with the SurgiNet interface displaying a higher number of unused POM functions, with 12 in total whereas Epic displayed 7 total functions. As reflected in all measures, Epic facilitated a more streamlined task-focused user experience. The approach enabled us to scrutinize the impact of different EHR interfaces on task performance and usability barriers subsequent to system implementation.
Profiling Dust Mass Concentration in Northwest China Using a Joint Lidar and Sun-Photometer Setting

The satellite-based estimation of the dust mass concentration (DMC) is essential for accurately evaluating the global biogeochemical cycle of the dust aerosols. As for the uncertainties in estimating DMC caused by mixing dust and pollutants and assuming a fixed value for the mass extinction efficiency (MEE), a classic lidar-photometer method is employed to identify and separate the dust from pollutants, obtain the dust MEE, and evaluate the effect of the above uncertainties, during five dust field experiments in Northwest China. Our results show that this method is effective for continental aerosol mixtures consisting of dust and pollutants. It is also seen that the dust loading mainly occurred in the free troposphere (<6 km), with the average mass loading of 905 ± 635 µg m−2 trapped in the planetary boundary layer. The dust MEE ranges from 0.30 to 0.60 m2 g−1 and has a significantly negative relationship with the size of dust particles. With the assumption of the dust MEE of 0.37 (0.60) m2 g−1, the DMC is shown to be overestimated (underestimated) by 20–40% (15–30%). In other words, our results suggest that the change of MEE with the size of dust particles should be considered in the estimation of DMC.
Assessing Vegetation Response to Multi-Scalar Drought across the Mojave, Sonoran, Chihuahuan Deserts and Apache Highlands in the Southwest United States

Understanding the patterns and relationships between vegetation productivity and climatic conditions is essential for predicting the future impacts of climate change. Climate change is altering precipitation patterns and increasing temperatures in the Southwest United States. The large-scale and long-term effects of these changes on vegetation productivity are not well understood. This study investigates the patterns and relationships between seasonal vegetation productivity, represented by Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI), and the Standardized Precipitation Evapotranspiration Index (SPEI) across the Mojave, Sonoran, and Chihuahuan Deserts and the Apache Highlands of the Southwest United States over 16 years from 2000 to 2015. To examine the spatiotemporal gradient and response of vegetation productivity to dry and wet conditions, we evaluated the linear trend of different SPEI timescales and correlations between NDVI and SPEI. We found that all four ecoregions are experiencing more frequent and severe drought conditions in recent years as measured by negative SPEI trends and severe negative SPEI values. We found that changes in NDVI were more strongly correlated with winter rather than summer water availability. Investigating correlations by vegetation type across all four ecoregions, we found that grassland and shrubland productivity were more dependent on summer water availability whereas sparse vegetation and forest productivity were more dependent on winter water availability. Our results can inform resource management and enhance our understanding of vegetation vulnerability to climate change.
Facile usage of a MYTHEN 1K with a Huber 5021 diffractometer and angular calibration inoperandoexperiments

A facile usage of a MYTHEN 1K detector with a Huber 5021 six-circle diffractometer is described in detail. A mechanical support has been custom designed for the first time to combine the MYTHEN 1K detector with a point detector, which can be used as a reference point for each individual pixel of the MYTHEN 1K during measurements. The MYTHEN 1K is mounted on the arm of the 2θ circle of the Huber diffractometer with an intrinsic angular resolution of ∼0.0038°, and its pitch angle can be automatically adjusted with an accuracy of 0.0072°. Standard procedures are discussed for its calibration. Programs have been written in the SPEC environment for simultaneous data conversion, integration and acquisition. The X-ray powder diffraction patterns of standard samples were measured in the Debye–Scherrer geometry and matched well with those of references. The angular shift due to sample-to-center displacement in the `flat-plate transmission' geometry, which is frequently employed in operando experiments, has been successfully investigated and can be efficiently corrected. One operando experiment using the MYTHEN 1K is presented. This work provides a straightforward procedure to use the MYTHEN 1K detector properly in Debye–Scherrer geometry, and could facilitate its application at other synchrotron facilities.
Composite Aerosol Optical Depth Mapping over Northeast Asia from GEO-LEO Satellite Observations

This study aimed to generate a near real time composite of aerosol optical depth (AOD) to improve predictive model ability and provide current conditions of aerosol spatial distribution and transportation across Northeast Asia. AOD, a proxy for aerosol loading, is estimated remotely by various spaceborne imaging sensors capturing visible and infrared spectra. Nevertheless, differences in satellite-based retrieval algorithms, spatiotemporal resolution, sampling, radiometric calibration, and cloud-screening procedures create significant variability among AOD products. Satellite products, however, can be complementary in terms of their accuracy and spatiotemporal comprehensiveness. Thus, composite AOD products were derived for Northeast Asia based on data from four sensors: Advanced Himawari Imager (AHI), Geostationary Ocean Color Imager (GOCI), Moderate Infrared Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS). Cumulative distribution functions were employed to estimate error statistics using measurements from the Aerosol Robotic Network (AERONET). In order to apply the AERONET point-specific error, coefficients of each satellite were calculated using inverse distance weighting. Finally, the root mean square error (RMSE) for each satellite AOD product was calculated based on the inverse composite weighting (ICW). Hourly AOD composites were generated (00:00–09:00 UTC, 2017) using the regression equation derived from the comparison of the composite AOD error statistics to AERONET measurements, and the results showed that the correlation coefficient and RMSE values of composite were close to those of the low earth orbit satellite products (MODIS and VIIRS). The methodology and the resulting dataset derived here are relevant for the demonstrated successful merging of multi-sensor retrievals to produce long-term satellite-based climate data records.
Large-Scale Analysis of the Spatiotemporal Changes of Net Ecosystem Production in Hindu Kush Himalayan Region

The Hindu Kush Himalayan (HKH) region is one of the most ecologically vulnerable regions in the world. Several studies have been conducted on the dynamic changes of grassland in the HKH region, but few have considered grassland net ecosystem productivity (NEP). In this study, we quantitatively analyzed the temporal and spatial changes of NEP magnitude and the influence of climate factors on the HKH region from 2001 to 2018. The NEP magnitude was obtained by calculating the difference between the net primary production (NPP) estimated by the Carnegie–Ames Stanford Approach (CASA) model and the heterotrophic respiration (Rh) estimated by the geostatistical model. The results showed that the grassland ecosystem in the HKH region exhibited weak net carbon uptake with NEP values of 42.03 gC∙m−2∙yr−1, and the total net carbon sequestration was 0.077 Pg C. The distribution of NEP gradually increased from west to east, and in the Qinghai–Tibet Plateau, it gradually increased from northwest to southeast. The grassland carbon sources and sinks differed at different altitudes. The grassland was a carbon sink at 3000–5000 m, while grasslands below 3000 m and above 5000 m were carbon sources. Grassland NEP exhibited the strongest correlation with precipitation, and it had a lagging effect on precipitation. The correlation between NEP and the precipitation of the previous year was stronger than that of the current year. NEP was negatively correlated with temperature but not with solar radiation. The study of the temporal and spatial dynamics of NEP in the HKH region can provide a theoretical basis to help herders balance grazing and forage.
Historical Changes in Land Use and Suitability for Future Agriculture Expansion in Western Bahia, Brazil

Western Bahia is a critical region in Brazil’s recent expansion of agricultural output. Its outstanding increase in production is associated with strong growth in cropland area and irrigation. Here we present analyses of Western Bahian historical changes in land use, including irrigated area, and suitability for future agricultural expansion that respects permanent protection areas and the limits established by the Brazilian Forest Code in the Cerrado biome. For this purpose, we developed a land use and land cover classification database using a random forest classifier and Landsat images. A spatial multicriteria decision analysis to evaluate land suitability was performed by combining this database with precipitation and slope data. We demonstrate that between 1990 and 2020, the region’s total agricultural area increased by 3.17 Mha and the irrigated area increased by 193,480 ha. Throughout the region, the transition between the different classes of land use and land cover followed different pathways and was strongly influenced by land suitability and also appears to be influenced by Brazil’s new Forest Code of 2012. We conclude that even if conservation restrictions are considered, agricultural area could nearly double in the region, with expansion possible mostly in areas we classify as moderately suitable for agriculture, which are subject to climate hazards when used for rainfed crops but are otherwise fine for pastures and irrigated croplands.
Anisotropic thermal conductivity and mechanical properties of phagraphene: a molecular dynamics study

Phagraphene is a novel 2D carbon allotrope with interesting electronic properties which has been recently theoretically proposed. Phagraphene is similar to a defective graphene structure with an arrangement of pentagonal, heptagonal and hexagonal rings. In this study we investigate the thermal conductivity and mechanical properties of phagraphene using molecular dynamics simulations. Using the non-equilibrium molecular dynamics method, we found the thermal conductivity of phagraphene to be anisotropic, with room temperature values of 218 ± 20 W m−1 K−1 along the armchair direction and 285 ± 29 W m−1 K−1 along the zigzag direction. Both values are one order of magnitude smaller than for pristine graphene. The analysis of the phonon group velocities also shows a significant reduction in this quantity for phagraphene in comparison to graphene. By performing uniaxial tensile simulations, we studied the deformation process and mechanical response of phagraphene. We found that phagraphene exhibits a remarkable high tensile strength around 85 ± 2 GPa, whereas its elastic modulus is also anisotropic along the in-plane directions, with values of 870 ± 15 GPa and 800 ± 14 GPa for the armchair and zigzag directions, respectively. The lower thermal conductivity of phagraphene along with its predicted electronic properties suggests that it could be a better candidate than graphene in future carbon-based thermoelectric devices.
Numerical study of optical properties of single and periodic nanostructures : from nanoantennas to enhanced transmission metamaterials

L ’interet des nano-particules pour le domaine de l ’optique visible a ete suscite lors du premier rapport redige par Faraday en 1857 et qui a initie les bases de la production de nanoparticules metalliques en vue de leur propriete optiques inattendues (coloration des solutions). Plus recemment, le controle et le guidage de la lumiere bases sur l’excitation de resonance plasmon dans les nanostructures a permis beaucoup d’applications liees a la vie quotidienne et impliquant la lumiere. La resonance plasmonique de structures metalliques estun phenomene essentiel qui conduit a des proprietes optiques uniques a travers l’interaction de la lumiere avecles electrons libres du metal. L’excitation de la resonance plasmon localise (LSPR) permet d’exalter localement l’energie electromagnetique comme dans le cas des nano-antennes mais aussi d’acheminer la lumiere a travers des canaux de dimensions sub-l sur de grandes distances distances grâce a l’excitation du Plasmonde Surface Propagatif (PSP). Au cours de cette these, nous avons etendu un algorithme existant afin de calculer la reponse optique (sections efficaces de diffusion et d’absorption) de NPs ayant une forme geometrie quelconque. Ce type de NP anisotrope (vis-a-vis de la polarisation incidente) peut presenter a la resonance plasmonique une section efficace de diffusion 25 fois superieure a celle geometrique. De plus, une etude systematique importante a ete effectuee afin d’optimiser la geometrie de tels Nps.En ce qui concerne la PSP qui est implique dans la transmission exaltee a travers les matrices d’ouvertures annulaires AAA, nous avons entrepris une etude systematique des proprietes de l’excitation du mode particul particulier sans coupure de ces nano - guides. Il s’agit du mode Transverse Electrique et Magnetique (TEM). Une etude numerique complete est alors effectuee pour correctement concevoir la structure avant qu’elle ne soit experimentalement fabriquee et caracterisee. Pour palier certaines contraintes experimentale, une structure inclinee est proposee et etudiee dans le cas d’un metal parfaitement conducteur. Nous avons demontree numeriquement et analytiquement certaines proprietes intrinseques de la structure montrant un coefficient de d’au moins 50% d’un faisceau incident non polarise independamment des conditions d’eclairage (polarisation,angle et plan d’incidence). Lorsque le mode TEM est excite, le flux laminaire de l’energie a travers la structure presente une deviation geante sur de tres petites distances inferieures a la longueur d’onde. Les resultats presentes dans cette these pourraient etre consideres comme une contribution importante a la comprehension du phenomene de transmission exaltee base sur l’excitation de ce type de mode guide.