The counting of 28 Si atoms plays a fundamental role in the realisation of the unit of mass in terms of stipulated values of fundamental physical constants. In this realisation, the measurement of the volume of a 28 Si sphere is a fundamental step. This paper reports a finite element analysis of the self-weight effect on the volume determination, taking the crystal anisotropy into account. The sphere

When measuring the Bidirectional Reflectance Distribution Function (BRDF) to characterize typical materials, the effect of the polarization of the light source or the dependence of the detector on the polarization is not usually considered, even though many studies have proven their impact in the uncertainty of the BRDF of most materials, including diffuse reflectance standards. A methodology to assess

After several years of development and continuous improvement of the BIPM Kibble balance, mass measurement of a 1 kg Pt/Ir artefact in terms of the Planck constant has been carried out. The paper describes the apparatus and its alignment, and explains the measurement and data processing. The balance operates in a one-mode and two measurement phase scheme using a bifilar coil. The mass value of the

This work reports on the upgrades made to the direct emissivity measurement facility of the University of the Basque Country (UPV/EHU). The instrumental improvements consist of, among others, a high-vacuum system and a wider temperature range (300 K to 1273 K). Methodological developments include a refined measurement equation with updated parameters and a reworked ISO-compliant uncertainty budget

The joule balance is one of the mass traceability devices in the revised International System of Units, and its smooth operation relies on a compensation coil to reduce the effect of the external magnetic field. In this paper, the interaction between the magnetized coil-suspension system and the compensation coil is theoretically analyzed and experimentally verified. First, an additional induced voltage

Vehicle detection in remote sensing images has attracted increasing interest in recent years. However, its detection ability is limited due to lack of well-annotated samples, especially in densely crowded scenes. Furthermore, since a list of remotely sensed data sources is available, efficient exploitation of useful information from multi-source data for better vehicle detection is challenging. To

Since the early 1980s, large-scale revegetation has been implemented in Northwest China and has been found to be useful in desertification prevention. However, it remains unclear, how land cover changes affect local meteorological conditions, such as land surface temperature. In this study, the land surface temperature response to land-use changes was comparatively evaluated using micrometeorological

This paper addresses the problem of semi-supervised transfer learning with limited cross-modality data in remote sensing. A large amount of multi-modal earth observation images, such as multispectral imagery (MSI) or synthetic aperture radar (SAR) data, are openly available on a global scale, enabling parsing global urban scenes through remote sensing imagery. However, their ability in identifying

Over the past few decades, mean summer temperatures within the Carpathian Mountains have increased by as much as 2 °C leading to a projected increased forest fire risk. Currently, there are no paleofire records from the Western Carpathians that provide the long-term range of natural variability to contextualise the response of upper-montane forests to future environmental change and disturbance regimes

The most pronounced climate anomaly of the Holocene was the 8.2 ka cooling event. We present new 230Th/U-ages as well as high-resolution stable isotope and trace element data from three stalagmites from two different cave systems in Germany, which provide important information about the structure and climate variability of the 8.2 ka event in central Europe. In all three speleothems, the 8.2 ka event

Late Miocene and Pliocene climate changes provide an analogue for understanding linkages between variations in precipitation, the intensity of the Asian Monsoon (AM) and vegetation in a warm world with high atmospheric CO2. This study presents a reconstruction of vegetation and paleoclimate based on a pollen sequence between ~10.8 and 7.2 Ma, in addition to an analysis of pollen assemblages of Pliocene

Recently, single gray/RGB image super-resolution reconstruction task has been extensively studied and made significant progress by leveraging the advanced machine learning techniques based on deep convolutional neural networks (DCNNs). However, there has been limited technical development focusing on single hyperspectral image super-resolution due to the high-dimensional and complex spectral patterns

Feature points that are obtained from the combined speeded-up robust feature (SURF) detector and binary robust independent elementary features (BRIEF) descriptor have a highly robust performance. These points are previously considered the ground control points (GCPs) for building a connection between the image coordinates and the corresponding geodetic coordinates. This article proposes a novel architecture

Brazil, with more than 8 million km 2 , presents six different biomes, ranging from natural grasslands (Pampa biome) to tropical rainfall forests (Amazônia biome), with different land-use types (mostly pasturelands and croplands) and pressures (mainly in the Cerrado biome). The objective of this article is to present a new method to discriminate the most representative land use and land cover (LULC)

In this article, we propose a variational approach for fusion of two coregistered high-resolution panchromatic (HRP) and low-resolution multispectral (LRM) images to reach the high-resolution multispectral (HRM) one, i.e., pan-sharpening. In this fusion technique, there is a tradeoff between structural information of an HRP image and spectral information of LRM one. To reconstruct the HRM image, which

Mesoscale oceanic eddies have a visible signature on sea surface temperature (SST) satellite images, portraying diverse patterns of coherent vortices, temperature gradients, and swirling filaments. However, learning the regularities of such signatures defines a challenging pattern recognition task, due to their complex structure but also to the cloud coverage which can corrupt a large fraction of the

To avoid using a large 4D-Hough counting space (HCS) and complex invariant features of generalized Hough transform (GHT) or its extensions when detecting objects in remote sensing image (RSI), a tensored GHT (TGHT) is proposed to extract object contour by simple gradient angle feature in a 2D-HCS using a single training sample. Considering that tensor can record the structure relationship of object

Arctic coastal erosion due to decreasing ice protection and increasing temperatures is a threat to coastal communities and infrastructure as well as a driver of long-term habitat changes. In order to respond to this threat, decadal predictive models are required that incorporate the effects of climate change under current emission trajectories. This work presents an Arctic erosion one-line model capable

High spatial resolution imaging in synthetic-aperture radar (SAR) can provide accurate monitoring capacity and has been gaining great attention recently in the fields of military and civilian. Apparently, the slant range resolution of the SAR system depends on the radar operating bandwidth. Currently, the large bandwidth signal synthesizing technology of the stepped frequency chirp signal waveform

Air quality degradations caused by fine particulate matter (PM 2.5 ) can lead to various health problems, and accurate PM 2.5 data are critical for managing the environment and ensuring public health. Radiation signals collected by nighttime light (NTL) remote sensing satellites are influenced by PM 2.5 concentrations, and thus, incorporating NTL imagery in statistical models has been widely used to

In this article, we establish the nonlinear signal model of the surface-based frequency-modulated continuous wave ice-sounding radar, and propose a novel range processing strategy that aims at removing the frequency ramp nonlinearity effectively. The proposed algorithm takes full consideration of the dependence of nonlinearity on the round-trip delay time while providing certain robustness of noise

Multidate images provide additional spectral information valuable for mapping plant species. However, correlated or redundant variables created from multiple image data and a large set of variables impede accurate and efficient landscape classification. Nevertheless, with the implementation of an appropriate feature selection method, the full potential of multidate images and subsequent increased classification

Recently, the oblique earth-space links (OELs) between satellite and earth station have been used for rainfall monitoring as a supplement to existing observation methods. Most recent studies achieved the rainfall measurement by OELs based on the empirical method such as power-law (PL) model. In practice, two crucial issues need to be addressed: 1) identification of rain and no-rain periods; and 2)

Optical properties of light reflected from leaves can be described by both intensity and polarization, however, most studies focused on the intensity in the estimation of plant leaf biochemical parameters. In this study, multiangular photometric and polarimetric measurements of leaves from three different plant species are first performed in laboratory to estimate leaf chlorophyll content (LCC) using

Recently, convolutional neural networks (CNNs) have attracted enormous attention in pattern recognition and demonstrated excellent performance in hyperspectral image (HSI) classification. However, high-dimensional HSI dataset versus limited training samples is easy to cause the overfitting phenomenon in deep neural networks. Additionally, the intraclass distance of the embedding features extracted

Advances in hyperspectral sensors have led to a significantly increased capability for high-quality data. This trend calls for the development of new techniques to enhance the way that such unprecedented volumes of data are stored, processed, and transmitted to the ground station. An important approach to deal with massive volumes of information is an emerging technique, called compressive sensing

With the amount of remote sensing data increasing at an extremely fast pace, machine learning-based technique has been shown to perform superiorly in many applications. However, most of the existing methods in the real-time application are based on single modal image data. Although a few approaches use the different source images to represent the object via a fusion scheme, it may not be appropriate

Remote sensing image scene classification, which aims at labeling remote sensing images with a set of semantic categories based on their contents, has broad applications in a range of fields. Propelled by the powerful feature learning capabilities of deep neural networks, remote sensing image scene classification driven by deep learning has drawn remarkable attention and achieved significant breakthroughs

Bistatic synthetic aperture radar (BiSAR) imaging is faced with two major challenges: large scene imaging and adaptability to unideal platform motion in practice. In order to deal with these two problems, a generalized wavefront-curvature-corrected polar format algorithm (PFA) is proposed in this article. The traditional PFA is little restricted on geometry configuration and platform motion, but its

The coastal crustal deformation caused by ocean tidal loading (OTL) varies spatially and temporally, and this spatiotemporal variation in satellite-based interferometric synthetic aperture radar (InSAR) measurements needs to be determined. In this article, we propose a spatiotemporal modeling method to estimate the OTL displacements in InSAR measurements using the kinematic precise point positioning

Good knowledge of inland water dynamics is of great significance for water management, preserving ecological balance and supporting industrial and agricultural development. However, the existing water cover products and water extraction methods cannot meet the present needs of monitoring water distribution and dynamic changes accurately and timely, particularly in the areas frequently disturbed by

Land cover (LC) is an essential variable for environmental monitoring in many application domains. The detection of changes in LC can support the understanding of environmental dynamics. However, LC legends present a high degree of inconsistencies that significantly reduce their usability. This study investigates the effectiveness of ISO standard 19144-2, better known as Land Cover Meta-Language (LCML)

Herein, a semiempirical model is proposed to remove the atmospheric phase screen (APS) that occurs during ground-based synthetic aperture radar (GB-SAR) monitoring in steep mountainous areas with extreme weather conditions. The proposed method is based on a model-based statistical technique, which combines the topographical information and the estimated phase of interferograms. A 3-D geographical model

The Compact Ocean Wind Vector Radiometer (COWVR) was developed at the Jet Propulsion Laboratory as a proof of concept technology demonstration mission for the Air Force. COWVR is a fully polarimetric imaging radiometer system operating at 18.7, 23.8, and 33.9 GHz . Its receiver subsystem is based on the Jason-3 advanced microwave radiometer, which was launched in early 2016 and is currently in operation

Due to the fact that the traditional high dynamic range (HDR) imaging methods cannot be used for satellites, finding a way to generate HDR remote sensing images from the satellites has long been explored in the field of remote sensing imaging. In this article, a systematic method of synthesizing the HDR remote sensing images based on a new registration algorithm and virtual digital delay integration

The Middle Eocene Climatic Optimum (MECO; 40.5–40.0 Ma) was a pronounced climatic reversal during a long-term global cooling period. Despite conspicuous signals of warming and ocean acidification in global marine sedimentary records, changes in upper ocean thermal stratification and productivity have been less comprehensively understood across the MECO. Here we examined stratigraphic records of the

ABSTRACT This study validated SNAP-derived LAI from Sentinel-2 and its consistency with existing global LAI products. The validation and inter-comparison experiments were performed on two processing levels, i.e., Top-of-Atmosphere and Bottom-of-Atmosphere reflectances and two spatial resolutions, i.e., 10 m, and 20 m. These were chosen to determine their effect on retrieved LAI accuracy and consistency

GPS has been used to estimate ocean tide loading (OTL) height displacement amplitudes to accuracies of within 0.5 mm at the M2 frequency, but such estimation has been problematic at luni-solar K2 and K1 frequencies because they coincide with the GPS orbital period and revisit period, leading to repeating multipath and satellite orbit errors. We therefore investigate the potential of using the GLONASS

China is currently focusing on the establishment of its BDS-3 system, and a BDS-3 constellation with 18 satellites in medium Earth orbit (MEO) and one satellite in geostationary Earth orbit (GEO) has been able to provide preliminary global services since the end of 2018. These BDS-3 satellites feature the inter-satellite link (ISL) and new high-quality onboard clocks. In this study, we present the

The occurrence of endorheic basins on the Tibetan Plateau, both in its Pleistocene history and (fewer in number) at the present day, has been attributed to the ‘basin-and-range’ character of the orogen; the understanding of their conversion to exorheic drainage is key to interpreting the evolution of the Yellow River and other river systems of the plateau. However, such basins also occur in areas of

Understanding temporal variability of sea surface temperature (SST) patterns plays a crucial role in providing insights into the mechanisms causing extreme weather and climate events as well as oceanic and atmospheric teleconnections. This study presents an in-depth analysis of the SST patterns of the Arctic Ocean and its marginal seas on interannual and seasonal timescales from 1982 to 2018. The results

Sun glint in hyperspectral images (HSIs) leads to undesirable spectral interference, which severely affects subsequent image interpretation, such as environmental monitoring of coastal areas. Sun glint removal methods aim to recover a high quality image without sun glint from the original image. Most methods depend on an assumption that the near infrared band is strongly absorbed by water. However

In geophysical and geodetic studies, gravity inversion is typically performed such that observed gravity values are first continued downward onto a regular (planar, spherical or spheroidal) surface by solving an inverse integral transform, which originates from a classical solution to the first boundary-value problem in potential theory. A typical example is continuing gravity observed at the topographic

This article derives a new change detector for multivariate synthetic aperture radar (SAR) image time series (ITS). Classical statistical change detection methodologies based on covariance matrix analysis are usually built upon the Gaussian assumption, as well as an unstructured signal model. Both of these hypotheses may be inaccurate for high-dimension/resolution images, where the noise can be heterogeneous

Global Navigation Satellite System precise positioning using carrier phase measurements requires reliable ambiguity resolution. It is challenging to obtain continuous precise positions with a high ambiguity fixing rate under a wide range of dynamic scenes with a single base station, thus the positioning accuracy will be degraded seriously. The Forward–Backward Combination (FBC), a common post-processing

The measurement of trace amounts of water in process gases is of paramount importance to a number of manufacturing processes. Water is considered to be one of the most difficult impurities to remove from gas supply systems and there is strong evidence that the presence of water contamination in semiconductor gases has a measurable impact on the quality and performance of devices. Consequently, semiconductor

Under the auspices of the Protein Analysis Working Group (PAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) a key comparison, CCQM-K115.b, was coordinated by the Bureau International des Poids et Mesures (BIPM) and the Chinese National Institute of Metrology (NIM). Seven Metrology Institutes or Designated Institutes and the BIPM participated. Participants were required to assign the

The article of the freeze/thaw dynamic of high-latitude Earth surfaces is extremely important and informative for monitoring the carbon cycle, the climate change, and the security of infrastructures. Current methodologies mainly rely on the use of active and passive microwave sensors, while very few efforts have been devoted to the assessment of the potential of observations based on signals of opportunity

ConGalSAR is a novel SAR constellation that has an outstanding performance of revisit and economy. In the system, with the MirrorSAR technology, one geostationary illuminator and several economical low earth orbit transponders work together to achieve a short revisiting interval. Because of the huge difference in the distances of transmitting and receiving, the spatial weighting of the antenna patterns

Dimension reduction (DR) addresses the problem known as the curse of dimensionality in myriad hyperspectral imagery applications. Although the spatial pattern may assist in the distinction between different land covers that have close spectral signatures, it is often neglected by the current DR methods. In order to overcome this defect, two solutions: patch-based and tensor-patch-based, are studied

Because of their scientific and social significance, large-scale geoscientific phenomena are attracting more and more attention. However, many existing Earth observation systems lack the ability to conduct long-term continuous observations on regional to global scales because of limitations on spatial and temporal coverage and the existence of systematic bias. The geometrical relationship between the

Fast and stable detection of dim and small infrared (IR) targets in complex backgrounds has important practical significance for IR search and tracking system. The existing small IR target detection methods usually fail or cause a high probability of false alarm in the highly heterogeneous and complex backgrounds. Continuous motion of a target relative to the background is important information regarding

New quantitative and semiautomated methods for analyzing oil slick evolution using a time series of $L$ -band synthetic aperture radar (SAR) images with short repeat time are developed and explored. In this study, two methods that are complementary in terms of identifying temporal changes within an oil slick are presented. The two methods reflect two ways of evaluating the oil slicks. The first method

Recently, the deep learning models have achieved great success in hyperspectral images (HSI) classification. However, most of the deep learning models fail to obtain satisfactory results under the condition of small samples due to the contradiction between the large parameter space of the deep learning models and the insufficient labeled samples in HSI. To address the problem, a deep model based on

Colored dissolved organic matter (CDOM) is an important biochemical state indicator of aquatic ecosystems. However, its retrieval from remote sensing datasets remains a challenging task due to its high spatiotemporal variability and interference from other water constituents. In this article, we aim to develop new CDOM inversion algorithms by taking advantage of a representative sparse learning algorithm

Understanding and exploiting topographical data via standard machine learning techniques is challenging, mainly due to the large dynamic range of values present in elevation data and the lack of direct relationships between anthropogenic phenomena and topography, when considering topographic–geology couplings, for instance. Here we consider the first hurdle, dynamic range, in an effort to apply Convolutional

Existing sparsity-based hyperspectral image (HSI) target detection methods have two key problems. 1) The background dictionary is locally constructed by the pixels between the inner and outer windows, surrounding and enclosing the central test pixel. The dual-window strategy is intricate and might result in impure background dictionary deteriorating the detection performance. 2) For an unbalanced binary

The classification of hyperspectral imagery (HSI) is an important part of HSI applications. The nearest-regularized subspace (NRS) is an effective method to classify HSI as one of the sparse representation methods. However, its high computational complexity confines usage in a time-critical scene. In order to enhance the computation efficiency of the NRS classifier, this article proposed a new parallel