Successive re-calibrations were implemented in Landsat-8 TIRS data since launch. This paper evaluates the performances of both: (1) these re-calibrations, up to the last calibration update announced for TIRS data in the next Landsat Collection 2; and (2) single-channel (SC) corrections and split-window (SW) algorithms to retrieve land surface temperature (LST) from TIRS data. A robust and accurate

Multisensor Earth observation has significantly accelerated the development of multisensor collaborative remote sensing applications such as all-weather mapping using synthetic aperture radar (SAR) images and optical images. However, in the real-world application scenarios, not all data sources may be available, namely, the missing-modality problem, e.g., the poor imaging conditions obstruct the optical

Reconstructing the Cenozoic sedimentary history of the Bay of Bengal (BoB) is significant for understanding the evolutionary history of South Asian river systems and the links between river development, tectonic deformation and global climate change. Here, we present the first long-term clay mineral record combined with Sr-Nd isotopic compositions from a 200-m-long sediment core from Ocean Drilling

Tree-ring width chronologies are a critically important material to reconstruct past precipitation variability on the northeastern Tibetan Plateau (NTP). However, temperature signals are often encoded in these chronologies, which complicate the precipitation reconstructions and should be carefully assessed. Here, a dataset of 487 Qilian juniper (Sabina przewalskii Kom.) tree-ring width series from

ABSTRACT This paper aims to compare the performance of typical open global DEM datasets by using the indexes of elevation error, relative error and hydrologic network. Taking Fenhe River Basin of China as the study area, this research made quantitative performance comparison among four typical open global DEM datasets including SRTM data with 1” (SRTM1) and 3” (SRTM3) resolutions, ASTER Global DEM

The Middle Triassic is thought to have had a greenhouse paleoclimate with a few short humid phases. However, the timing of these humid events, and the extent to which orbital forcing influenced the evolution of climate, are unclear. Here, a cyclostratigraphic analysis has been carried out based on the integrated study of magnetic susceptibility, elemental chemistry and lithofacies from two shallow-marine

The Teočak section in Bosnia and Herzegovina (Sava-Vardar Zone) composed of the Upper Permian Bellerophon Formation and the Lower Triassic “Werfen Formation” was studied sedimentologically and micropaleontologically by using foraminifers and conodonts. The Bellerophon Formation was deposited in a shallow subtidal lagoon rich in biota characterized by typical Changsingian foraminiferal species. Deposition

Four-dimensional (4D) ultrasound reconstruction can greatly extend the spatial and temporal range of two-dimensional (2D) ultrasound in clinical practice. However, uneven breaths may yield a considerable motion artifact in the reconstructed time sequences of volume ultrasound. In this paper, a system with sparse respiratory signal matching is proposed to realize accurate 4D ultrasound reconstruction

In this work, an integrated framework comprising of pixel-based classification, road network filtering, and multi-scale Gabor filter is proposed to address the various prevailing issues in road centerline extraction from VHR images. The proposed framework is composed of three steps; generation of the initial road map, road network filtering and road centerline extraction. In the first step, pixel-based

Natural disasters like flood are causing massive damages to natural and human resources, especially in coastal areas. In respect to social, economic and environmental perspective, flood is one of the most devastating disasters in Chennai for the recent days. Flood susceptibility mapping using frequency ratio model was done for the 88 micro watersheds of Adyar, Cooum and Kosasthalaiyar watersheds of

Land use provides crucial data for earth science research and its accuracy has always been a hot topic. Various auxiliary data are used to improve the classification accuracy of land use. The digital elevation model (DEM) is one of the common auxiliary data since topography directly affects the surface landscape. However, few researches focus on the impact of the DEM on the classification accuracy

Water vapor plays an important role in Earth’s weather and climate processes and energy transfer. Plenty of techniques have developed to monitor precipitable water vapor (PWV), but joint use of different techniques has some problems, including systematic biases, different spatiotemporal coverages and resolutions among different datasets. To address the above problems and improve the data utilization

Ecosystems are defined by the community of living organisms and how they interact together and with their environment. Insects and plants are key taxa in terrestrial ecosystems and their network determines the trophic structure of the environment. However, what drives the interactions between plants and insects in modern and fossil ecosystems is not well understood. In this study, we analyzed insect

It has been argued that the beginning of significant pelagic calcification could have been linked to the Carnian Pluvial Episode (CPE), a climate change in the Late Triassic (~234–232 Ma) that was marked by C-cycle disruption and global warming. Nevertheless, abundant calcareous nannofossils have been described so far only in post-CPE rocks, and therefore no conclusive hypotheses can be drawn on possible

Remote monitoring of chlorophyll-a (chla) has been widely used to evaluate the trophic state of inland and coastal waters, however, there is still much uncertainty in the algorithms applied in different optical water types. The influence of different atmospheric correction (AC) processors, which can also provide correction for sunglint and adjacency effects, on the retrieved chla is poorly understood

This paper investigates the influence of armed and political conflicts on the urban climate, particularly the surface urban heat island (SUHI) of the Baghdad metropolitan area. This study analyzes changes in spatial patterns of land use and land cover and anthropogenic activities that have occurred as a result of wars and political conflicts. Multi-temporal Landsat data for the years 1984, 2001, and

Civil receivers of Global Navigation Satellite System (GNSS) are vulnerable to spoofing and jamming attacks due to their signal structures. The Spreading Code Authentication (SCA) technique is one of the GNSS message encryption identity authentication techniques. Its robustness and complexity are in between Navigation Message Authentication (NMA) and Navigation Message Encryption (NME)/Spreading Code

Sea surface temperatures (SSTs) in the North Pacific exert a great influence on global climate and ecosystem changes. The Pacific Decadal Oscillation (PDO) is the leading mode of decadal SST variability in the North Pacific. The PDO-like variability at a millennial timescale during the Holocene is still poorly understood. In this study, the millennial-scale PDO-like variability during the Holocene

ABSTRACT A new satellite-based algorithm for rainfall retrieval in high spatio-temporal resolution for Ecuador is presented. The algorithm relies on the precipitation information from the Integrated Multi-SatEllite Retrieval for the Global Precipitation Measurement (GPM) (IMERG) and infrared (IR) data from the Geostationary Operational Environmental Satellite-16 (GOES-16). It was developed to (i) classify

As a dynamic and essential component in the road environment of urban scenarios, vehicles are the most popular investigation targets. To monitor their behavior and extract their geometric characteristics, an accurate and instant measurement of vehicles plays a vital role in traffic and transportation fields. Point clouds acquired from the mobile laser scanning (MLS) system deliver 3D information of

With the development of photon-counting sensors, spaceborne photon-counting lidars have shown many advantages in mapping underwater topography. Although a space based lidar is normally a profiling system, the depth penetration and the vertical accuracy achieved with a bathymetric lidar is superior to imagery (that only provides relative depths). Therefore, many satellite derived bathymetry products

Identifying spatial distribution of crop planting in large-scale is one of the most significant applications of remote sensing imagery. As an active remote sensing system, synthetic aperture radar (SAR) provides high-resolution polarimetric information of land covers. Nowadays, it is possible to carry out continuous multi-temporal analysis of crops in large-scales since an increased number of spaceborne

With the development of supervised deep neural networks, classification performance on existing remote sensing scene datasets has been markedly improved. However, supervised learning methods rely heavily on large-scale tagged examples to obtain a better prediction performance. The lack of large-scale tagged remote sensing scene images has become the primary bottleneck in scene classification. To deal

The TanDEM-X mission, formed by the TanDEM-X satellite in cooperation with its almost identical twin TerraSAR-X (TSX), has mainly been designed to acquire bistatic synthetic aperture radar (SAR) images of the Earth. Initiated in 2010, the primary mission objectives were to generate a global digital elevation model (DEM) to perform scientific measurements and to explore novel SAR techniques. Up to the

Joint sparse representation (JSR) is a commonly used classifier that recognizes different objects with core features extracted from images. However, the generalization ability is weak for the traditional linear kernel, and the objects with similar feature values associated with different categories are not sufficiently distinguished especially for a hyperspectral image (HSI). In this article, an HSI

Recently, many deep learning-based methods have been developed for solving remote sensing (RS) scene classification or retrieval tasks. Most of the adopted loss functions for training these models require accurate annotations. However, the presence of noise in such annotations (also known as label noise) cannot be avoided in large-scale RS benchmark archives, resulting from geo-location/registration

Hyperspectral images (HSIs) are characterized by high spatial resolution and are rich in spectral information. In the process of HSI classification, the extraction of spectral–spatial features directly influences the classification results. In recent years, the hyperspectral classification method based on convolutional neural networks has demonstrated excellent performance. However, as the network

A soil moisture (SM) disaggregation algorithm based on thermal inertia (TI) theory was implemented to downscale the soil moisture active passive (SMAP) enhanced product (SPL2SMP $\_$ E) from 9 to 1 km over the continental United States. The algorithm applies land surface temperature and normalized difference vegetation index from moderate resolution imaging spectroradiometer (MODIS) at higher spatial

Electromagnetic (EM) scattering calculation is a very important part of most synthetic aperture radar (SAR) target image simulation methods. It affects the intensity of the radar echo signal to a great extent, thus affecting the quality of the final simulation image. EM reflection models are usually approximate formulas derived under certain assumptions. The errors between these models and the actual

Monitoring wetlands is necessary in order to understand and protect their ecohydrological balance. In Ireland, traditionally wetland-monitoring is carried out by manual field visits which can be very time-consuming. To automate the process, this study extends the ability of remote sensing-based monitoring of wetlands by combining RGB image processing, machine learning algorithms, and satellite data

Estimating evapotranspiration is an essential step towards the calculation of crops irrigation needs. One of the most widely used methods for this estimation is Surface Energy Balance Algorithm (SEBAL), a method based on remote sensing imagery. In the current study, fusion images of Landsat 8 and MODIS satellites using Gram-Schmidt algorithm were employed to calculate actual evapotranspiration of the

The Japan Sea is ideal for investigating deep water formation due to its unique topography and hydrography. However, because of the scarcity of reliable indicator and high-resolution ventilation records, the driving mechanisms behind ventilation changes in the entire Japan Sea since the Last Glacial Maximum (LGM) remain elusive. In this study, we analyze the radiolarian assemblage in three sediment

Atmospheric correction is an essential step in hyperspectral imaging and target detection from spectrometer remote sensing data. State-of-the-art atmospheric correction approaches either require extensive filed experiments or prior knowledge of atmospheric characteristics to improve the predicted accuracy, which are computational expensive and unsuitable for real time application. To take full advantages

In this article, we propose a method to reconstruct the total electromagnetic field in an arbitrary two-dimensional scattering environment without any prior knowledge of the incident field or the permittivities of the scatterers. However, we assume that the region between the scatterers is homogeneous and that the approximate geometry describing the environment is known. Our approach uses field measurements

Detecting the changes of buildings in urban environments is essential. Existing methods that use only nadir images suffer from severe problems of ambiguous features and occlusions between buildings and other regions. Furthermore, buildings in urban environments vary significantly in scale, which leads to performance issues when using single-scale features. To solve these issues, this paper proposes

Robust and effective detection of a small target in an infrared maritime image is a key technology of maritime target search and tracking applications. Infrared small target detection is a challenging task due to the factors such as dim small targets and various complex backgrounds caused by sun glitters and strong waves. In this article, the integrated target saliency measure (ITSM) based on local

The rapid development of deep learning brings effective solutions for remote sensing image interpretation. Training deep neural network models usually require a large number of manually labeled samples. However, there is a limitation to obtain sufficient labeled samples in remote sensing field to satisfy the data requirement. Therefore, it is of great significance to conduct the research on few-shot

The main objective of this article is to develop a physically constrained support vector machine (SVM) to predict C-band backscatter over snow-covered terrain as a function of geophysical inputs that reasonably represent the relevant characteristics of the snowpack. Sentinel-1 observations, in conjunction with geophysical variables from the Noah-MP land surface model, were used as training targets

In our previous work, a two-phase multiobjective sparse unmixing (Tp-MoSU) approach has been proposed, which settled the regularization parameter issues of the regularization unmixing methods. However, Tp-MoSU has limited performance in identifying the real endmembers from the highly noisy data in the first phase and cannot effectively exploit the spatial-contextual information in the second phase

This article focuses on bistatic coherence as an additional feature complementing amplitudes in classification space, permitting to monitor temporal changes in water extent on the wetland comprising surface water and inundated vegetation. The research was conducted on a herbaceous wetland. The TanDEM-X images were acquired during the science phase in bistatic mode with long perpendicular baselines

In this article, we aim to explore the potential of using onboard cameras and pre-stored geo-referenced imagery for Unmanned Aerial Vehicle (UAV) localization. Such a vision-based localization enhancing system is of vital importance, particularly in situations where the integrity of the global positioning system (GPS) is in question (i.e., in the occurrence of GPS outages, jamming, etc.). To this end

This article presents a deep residual network-based fusion framework for hyperspectral and LiDAR data. In this framework, three new fusion methods are proposed, which are the residual network-based deep feature fusion (RNDFF), the residual network-based probability reconstruction fusion (RNPRF) and the residual network-based probability multiplication fusion (RNPMF). The three methods use extinction

Hyperspectral images (HSIs) include hundreds of spectral bands, which lead to Hughes phenomenon in classification task and decrease the classification accuracy. Feature selection can remove redundant and noisy features in the HSIs to overcome this phenomenon. In real applications, we may face a HSI scene with only a few labeled samples. Meanwhile, there are adequate labeled samples in a similar HSI

This article assesses how the ground-penetrating radar RIMFAX will image the crater floor at the Mars 2020 landing site, where lithological compositions and stratigraphic relationships are under discussion prior to mission operation. A putative mafic unit (lava flow, volcanic ash, or volcaniclastic deposit) on the crater floor will be crucial in piecing together the chronology of deposition and for

Convolutional neural networks (CNNs) have improved the accuracy of hyperspectral image (HSI) classification significantly. However, CNN models usually generate a large number of feature maps, which lead to high redundancy and cannot guarantee to effectively extract discriminative features for well characterizing the complex structures of HSIs. In this article, two novel mixed link networks (MLNets)

Abstract A sand spit is a deposition of sediments built up and diverging from the coast. The spit can be beneficial or create problems. Understanding and being able to forecast its evolution is the key to maximizing its advantages and minimizing its drawbacks. Along the southern Gulf of Thailand, there are 3 major sand spits, being Laem Talumpuk spit, Laem Sui spit, and Laem Tachi spit. Each individual

ABSTRACT An ocean circulation model, Nucleus for European Modelling of the Ocean (NEMO version 3.6) is customized to run at high-resolution over a regional domain [30oE-105oE; 20oS-30oN] in the Indian Ocean. It uses horizontal resolution of 1/12° in longitude/latitude and 75 levels in the vertical direction. The model well captures the observed space-time variations of temperature and salinity at the

In 2015, the International Association of Geodesy defined the International Height Reference System (IHRS) as the conventional gravity field-related global height system. The IHRS is a geopotential reference system co-rotating with the Earth. Coordinates of points or objects close to or on the Earth’s surface are given by geopotential numbers C(P) referring to an equipotential surface defined by the

In 2017, the new generation satellite-based augmentation system (SBAS) test-bed was initiated by Australia and New Zealand, which supports the dual-frequency multi-constellation (DFMC) positioning with both GPS and Galileo signals. This new SBAS DFMC service allows the elimination of the first-order term of the ionospheric delays, and extends the service area to the entire footprint of the geostationary

Ionospheric scintillation refers to rapid and random fluctuations in radio frequency signal intensity and phase, which occurs more frequently and severely at high latitudes under strong solar and geomagnetic activity. As one of the most challenging error sources affecting Global Navigation Satellite System (GNSS), scintillation can significantly degrade the performance of GNSS receivers, thereby leading

Aside from the ionospheric total electron content (TEC) information, root-mean-square (RMS) maps are also provided as the standard deviations of the corresponding TEC errors in global ionospheric maps (GIMs). As the RMS maps are commonly used as the accuracy indicator of GIMs to optimize the stochastic model of precise point positioning algorithms, it is of crucial importance to investigate the reliability

With the development of multi-GNSS, the differential code bias (DCB) has been an increasing interest in the multi-frequency multi-GNSS community. Unlike code division multiple access (CDMA) mode used by GPS, BDS and Galileo etc., the GLONASS signals are modulated with frequency division multiple access (FDMA) mode. Up to now, the FDMA-aware GLONASS bias products are provided by two individual IGS analysis

Global pressure and temperature (GPT) models are widely available and easy-to-use in tropospheric delay estimation and GNSS water vapor retrieval, but cannot capture the diurnal and semidiurnal variations that add uncertainty to tropospheric delay determinations. This paper introduces an improved global pressure and temperature model (IGPT) established using 10 years hourly ERA5 dataset provided by

Global ionosphere maps (GIM) computed from dual-frequency GNSS measurements have been widely used for monitoring ionosphere as well as providing ionospheric corrections in Space Geodesy since 1998. This work focuses on a comprehensive study of the influence of time resolution on GIM performance. One and a half solar cycle of the IGS GIM with higher time resolution and accuracy (the UPC-IonSAT Quarter-of-an-hour

We present a new method to incorporate paleo-surface temperature effects in steady state 3D conductive temperature models. The workflow approximates the transient effects and incorporates these into steady state models, using appropriate source and sink terms for radiogenic heat production. This allows for rapid models, which can be easily used in ensemble approaches for data assimilation of high-resolution

Geographic information such as the altitude, latitude, and longitude are common but fundamental meta-records in remote sensing image products. In this paper, it is shown that such a group of records provides important priors for cloud and snow detection in remote sensing imagery. The intuition comes from some common geographical knowledge, where many of them are important but are often overlooked.

Precipitable water vapor (PWV) plays an important role in understanding the atmosphere and weather. The advancement in Global Navigation Satellite System (GNSS) technology provides the possibility of computing PWV in near real time. In this study, the PWV was computed using the Zenith Tropospheric Delay (ZTD) from Global Positioning System (GPS) data for two International GNSS Service (IGS) stations