2018 November - 189 articles
The characteristics of the improved Atomic Frequency Standard (AFS) operated on the latest BeiDou-3 experimental satellites are analyzed from day-of-year (DOY) 254 to 281, of the year 2017, considering the following three aspects: stability, periodic...
Accurate estimation of tree position, diameter at breast height (DBH), and tree height measurements is an important task in forest inventory. Mobile Laser Scanning (MLS) is an important solution. However, the poor global navigation satellite system (...
Numerous global-scale land-cover datasets have greatly contributed to the study of global environmental change and the sustainable management of natural resources. However, land-cover datasets inevitably experience information loss because of the nat...
Knowledge of forest productivity status is an important indicator of the amount of biomass accumulated and the role of terrestrial ecosystems in the carbon cycle. However, accurate and up-to-date information on forest biomass and forest succession re...
Forest cover and vegetation degradation was monitored across the Kavango-Zambezi Transfrontier Conservation Area (KAZA) in southern Africa and the performance of three different methods in detecting degradation was assessed using reference data. Brea...
In tree Aboveground Biomass (AGB) estimation, the traditional harvest method is accurate but unsuitable for a large-scale forest. The airborne Light Detection And Ranging (LiDAR) is superior in obtaining the point cloud data of a dense forest and ext...
Space-based Interferometric Synthetic Aperture Radar (InSAR) applications have been widely used to monitor the cryosphere over past decades. Owing to temporal decorrelation, interferometric coherence often severely degrades on fast moving glaciers. T...
Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products are widely used in ecology, hydrology, vegetation monitoring, and global circulation models. Compared to the collection-5 (C5) LST products, the newly relea...
After publication of the research paper [...]
Cloud detection, which is defined as the pixel-wise binary classification, is significant in satellite imagery processing. In current remote sensing literature, cloud detection methods are linked to the relationships of imagery bands or based on simp...
Different kinds of radiative transfer models, including a relative sunshine-based model (BBM), a physical-based model for tropical environment (PBM), an efficient physical-based model (EPP), a look-up-table-based model (LUT), and six artificial intel...
After publication of the research paper [...]
The potential of Global Navigation Satellite Systems-Reflectometry (GNSS-R) techniques to estimate land surface parameters such as soil moisture (SM) is experimentally studied using 2014–2017 global data from the UK TechDemoSat-1 (TDS-1) missio...
Characterizing 3-D structure of clouds is needed for a more complete understanding of the Earth’s radiative and latent heat fluxes. Here we develop and explore a ray casting algorithm applied to data from the Multi-angle Imaging SpectroRadiomet...
Due to the advantages of wide coverage and continuity, remotely sensed data are widely used for large-scale drought monitoring to compensate for the deficiency and discontinuity of meteorological data. However, few studies have focused on the capabil...
Accurate estimation of precipitation is critical for hydrological, meteorological, and climate models. This study evaluates the performance of satellite-based precipitation products (SPPs) including Global Precipitation Measurement (GPM)-based Integr...
The proliferation of remote sensing imagery motivates a surge of research interest in image processing such as feature extraction and scene recognition, etc. Among them, scene recognition (classification) is a typical learning task that focuses on ex...
Automatic image registration of optical-to-Synthetic aperture radar (SAR) images is difficult because of the inconsistency of radiometric and geometric properties between the optical image and the SAR image. The intensity-based methods may require ma...
The fine-mode aerosol optical depth (AODf) is an important parameter for the environment and climate change study, which mainly represents the anthropogenic aerosols component. The Polarization and Anisotropy of Reflectances for Atmospheric Science c...
Global soil moisture (SM) products are currently available thanks to microwave remote sensing techniques. Validation of these satellite-based SM products over different vegetation and climate conditions is a crucial step. INRA (National Institute of...
Rice is one of the world’s major staple foods, especially in China. Highly accurate monitoring on rice-producing land is, therefore, crucial for assessing food supplies and productivity. Recently, the deep-learning convolutional neural network...
Analyzing the trends in the spatial distribution of suspended sediment concentration (SSC) in riverine surface water enables better understanding of the hydromorphological properties of its watersheds and the associated processes. Thus, it is critica...
Long and consistent soil moisture time series at adequate spatial resolution are key to foster the application of soil moisture observations and remotely-sensed products in climate and numerical weather prediction models. The two L-band soil moisture...
Modeling the statistical distribution of synthetic aperture radar (SAR) images is essential for sea target detection, which is an important aspect of marine SAR applications. The main goal of this study is to determine the effects of sea states and s...
Stereo matching has been solved as a supervised learning task with convolutional neural network (CNN). However, CNN based approaches basically require huge memory use. In addition, it is still challenging to find correct correspondences between image...
The Horizon 2020 interim evaluation (2017) indicates a steep increase in citizen engagement in European Union Citizen Science (CS) projects, with less than 1% in budgetary terms and minimal influence. Research findings attribute weak CS influence to...
With the rapid development of Unmanned Aerial Vehicle (UAV) systems, the autonomous landing of a UAV on a moving Unmanned Ground Vehicle (UGV) has received extensive attention as a key technology. At present, this technology is confronted with such p...
We analyzed chemical composition, mineralogy, and spectral characteristics of the tailings of a hydrothermal gold mine in South Korea. We measured spectral responses of tailings to arsenic (As) and lead (Pb) concentration and developed and validated...
Despite the importance of tidal ecosystems in the global carbon budget, the relationships between environmental drivers and carbon dynamics in these wetlands remain poorly understood. This limited understanding results from the challenges associated...
Recent developments in remote sensing (RS) technology have made several sources of auxiliary data available to support forest inventories. Thus, a pertinent question is how different sources of RS data should be combined with field data to make inven...
This study introduces a technique for automatically mapping built-up areas using synthetic aperture radar (SAR) backscattering intensity and interferometric multi-temporal coherence generated from Sentinel-1 data in the framework of the Copernicus pr...
Sound water resources planning and management requires adequate data with sufficient spatial and temporal resolution. This is especially true in the context of irrigated agriculture, which is one of the main consumptive users of the world’s fre...
Superpixels, as a state-of-the-art segmentation paradigm, have recently been widely used in computer vision and pattern recognition. Despite the effectiveness of these algorithms, there are still many limitations and challenges dealing with Very High...
The prediction of forest biomass at the landscape scale can be achieved by integrating data from field plots with satellite imagery, in particular data from the Landsat archive, using k-nearest neighbour (kNN) imputation models. While studies have de...
Ice albedo feedback amplifies climate change signals and thus affects the global climate. Global long-term records on sea-ice albedo are important to characterize the regional or global energy budget. As the successor of MODIS (Moderate Resolution Im...
Among the objectives of the upcoming space missions Tandem-L and BIOMASS, is the 3-D representation of the global forest structure via synthetic aperture radar (SAR) tomography (TomoSAR). To achieve such a goal, modern approaches suggest solving the...
Hyperspectral change detection (CD) can be effectively performed using deep-learning networks. Although these approaches require qualified training samples, it is difficult to obtain ground-truth data in the real world. Preserving spatial information...
Satellite synthetic aperture radar (SAR) interferometry (InSAR) is a powerful technology to monitor slow ground surface movements. However, the extraction and interpretation of information from big sets of InSAR measurements is a complex and demandin...
We examine the mass balance of the glaciers in the Novaya Zemlya Archipelago, located in the Russian High Arctic using time series of time-variable gravity from the NASA/DLR Gravity Recovery and Climate Experiment (GRACE) mission, laser altimetry dat...
Human transformation of landscapes is pervasive and accelerating across the Earth. However, existing studies have not provided a comprehensive picture of how precipitation frequency and intensity respond to vegetation cover change. Therefore, this st...
Advanced parametric financial instruments, like weather index insurance (WII) and risk contingency credit (RCC), support disaster-risk management and reduction in the world’s most disaster-prone regions. Simultaneously, satellite data that are...
Plastic mulching on farmland has been increasing worldwide for decades due to its superior advantages for improving crop yields. Monitoring Plastic-Mulched Land-cover (PML) can provide essential information for making agricultural management decision...
To improve the detection ability of infrared small targets in complex backgrounds, a novel method based on non-convex rank approximation minimization joint l2,1 norm (NRAM) was proposed. Due to the defects of the nuclear norm and l1 norm, the state-o...
Using surface temperature as a signature of the surface energy balance is a way to quantify the spatial distribution of evapotranspiration and water stress. In this work, we used the new dual-source model named Soil Plant Atmosphere and Remote Sensin...
We analyze ten years (2008–2017) of ground-based observations of the Aerosol Optical Depth (AOD) in the atmosphere of Kuwait City, in Middle East. The measurements were conducted with a CIMEL sun-sky photometer, at various wavelengths. The dail...
This work presents calibration results for the altimeter of Sentinel-3A Surface Topography Mission as determined at the Permanent Facility for Altimetry Calibration in west Crete, Greece. The facility has been providing calibration services for more...
To improve the performance of land-cover change detection (LCCD) using remote sensing images, this study utilises spatial information in an adaptive and multi-scale manner. It proposes a novel multi-scale object histogram distance (MOHD) to measure t...
The imaging issue of a rotating maneuvering target with a large angle and a high translational speed has been a challenging problem in the area of inverse synthetic aperture radar (ISAR) autofocus imaging, in particular when the target has both radia...
Rapidly developing droughts, including flash droughts, have frequently occurred throughout East Asia in recent years, causing significant damage to agricultural ecosystems. Although many drought monitoring and warning systems have been developed in r...
Surface albedo is a critical parameter in surface energy balance, and albedo change is an important driver of changes in local climate. In this study, we developed a workflow for landscape albedo estimation using images acquired with a consumer-grade...
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