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The spaceborne Electric Field Detector (EFD) is one of the payloads of the China Seismo-Electromagnetic Satellite (CSES-01), which can measure electric field data at near-Earth orbit for investigating fundamental scientific topics such as the dynamics of the top-side ionosphere, lithosphere–atmosphere–ionosphere coupling, and electromagnetic field emissions possibly associated with earthquake occurrence. The Extremely Low-Frequency (ELF) waveform shows anomalous step variations, and this work proposes an automatic detection algorithm to identify steps and analyze their characteristics using a convolutional neural network. The experimental results show that the developed detection method is effective, and the identification performance reaches over 90% in terms of both accuracy and area under the curve index. We also analyze the rate of the occurrence of steps in the three components of the electric field. Finally, we discuss the stability of the statistical results on steps and their relevance to the probe's function. The research results provide a guideline for improving the quality of EFD data, and further applications in monitoring the low-Earth electromagnetic environment. [ABSTRACT FROM AUTHOR]

We present the results of a systematic study of the ionospheric electric field in the Auroral Oval (AO) region in the southern hemisphere. We exploit one year of electric field measurements taken by the Electric Field Detector (EFD) on board the Chinese Seismo-Electromagnetic Satellite-01 (CSES-01), flying at around 500 km altitude in a sun-synchronous orbit. We exploit the high temporal resolution of the EFD to devise a new technique for the detection of CSES-01 crossing of the AO using electric field measurements only. This new technique combines a Median-Weighted Local Variance Measure with Fast Iterative Filtering to automatically isolate high levels of electromagnetic activity caused by, e.g., particle precipitation and Field Aligned Currents (FACs) at auroral latitudes. We validate this new method against other standard proxies, such as the single-FAC product from the Swarm mission and the auroral radiance emission measured by the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) units on board the Defense Meteorological Satellite Program (DMSP) constellation. Furthermore, we identify ∼3000 orbits (out of a dataset of ∼10,000) where CSES-01 crosses the AO boundary under conditions of high geomagnetic activity. This dataset represents the first step in the systematic study of the auroral electric field, with many potential applications to space weather, thanks to the large amount of continuous observations of the ionosphere by CSES-01 and the forthcoming CSES-02 mission. [ABSTRACT FROM AUTHOR]

Due to the long distance propagation characteristics of the HF spectrum, noise and interference are significant and challenging factors that have to be addressed in the context of HF system performance. Both aspects exhibit systematic diurnal, seasonal, and solar cycle variability that result in a number of corresponding measurement campaigns all over the globe, in an effort to characterise HF noise. Noise at HF consists of man-made and naturally occurring HF noise with atmospheric and galactic components. An understanding of HF noise variation in terms of time, azimuth, and filter bandwidth is crucial for a specific location, as it can provide a background knowledge based on which appropriate values of HF system parameters may be selected. This paper deals with the temporal, azimuthal, and bandwidth characteristics of HF noise based on a one-month dataset of electric field strength measurements recorded by a directional antenna in Cyprus. [ABSTRACT FROM AUTHOR]

Measuring the atmospheric electric field is of crucial importance for studying the discharge phenomena of thunderstorm clouds. If one is used to indicate the occurrence of a lightning event and zero to indicate the non-occurrence of the event, then a binary classification problem needs to be solved. Based on the established database of weather samples, we designed a lightning prediction system using deep learning techniques. First, the features of time-series data from multiple electric field measurement sites are extracted by a sparse auto encoder (SAE) to construct a visual picture, and a binary prediction of whether lightning occurs at a specific time interval is obtained based on the improved ResNet50. Then, the central location of lightning flashes is located based on the extracted features using a multilayer perceptron (MLP) model. The performance of the method yields satisfactory results with 88.2% accuracy, 92.2% precision rate, 81.5% recall rate, and 86.4% F1-score for weather samples, which is a significant improvement over traditional methods. Multiple spatial localization results for several minutes before and after can be used to know the specific area where lightning is likely to occur. All the above methods passed the reliability and robustness tests, and the experimental results demonstrate the effectiveness and superiority of the model in lightning short-time proximity warning. [ABSTRACT FROM AUTHOR]

The recent Chinese Seismo-Electromagnetic Satellite (CSES-01) provides a good opportunity to investigate some features of plasma properties and its motion in the topside ionosphere. Using simultaneous measurements from the electric field detector and the magnetometers onboard CSES-01, we investigate some properties of the plasma E × B drift velocity for a case study during a crossing of the Southern auroral region in the topside ionosphere. In detail, we analyze the spectral and scaling features of the plasma drift velocity and provide evidence of the turbulent character of the E × B drift. Our results provide an evidence of the occurrence of 2D E × B intermittent convective turbulence for the plasma motion in the topside ionospheric F2 auroral region at scales from tens of meters to tens of kilometers. The intermittent character of the observed turbulence suggests that the macro-scale intermittent structure is isomorphic with a quasi-1D fractal structure, as happens, for example, in the case of a filamentary or thin-tube-like structure. Furthermore, in the analyzed range of scales we found that both magnetohydrodynamic and kinetic processes may affect the plasma dynamics at spatial scales below 2 km. The results are discussed and compared with previous results reported in the literature. [ABSTRACT FROM AUTHOR]

Taking photographs with a commercially available digital camera is an efficient and objective method for determining the green fractional vegetation cover (FVC) for field validation of satellite products. However, classifying leaves under shadows in processing digital images remains challenging and results in classification errors. To address this problem, an automatic shadow-resistant algorithm in the Commission Internationale d'Eclairage L*a*b* color space (SHAR-LABFVC) based on a documented FVC estimation algorithm (LABFVC) is proposed in this paper. The hue saturation intensity (HSI) is introduced in SHAR-LABFVC to enhance the brightness of shaded parts of the image. The lognormal distribution is used to fit the frequency of vegetation greenness and to classify vegetation and the background. Real and synthesized images are used for evaluation, and the results are in good agreement with the visual interpretation, particularly when the FVC is high and the shadows are deep, indicating that SHAR-LABFVC is shadow resistant. Without specific improvements to reduce the shadow effect, the underestimation of FVC can be up to 0.2 in the flourishing period of vegetation at a scale of 10 m. Therefore, the proposed algorithm is expected to improve the validation accuracy of remote sensing products. [ABSTRACT FROM AUTHOR]

This study introduces a new approach to estimate surface soil moisture in vegetated areas using Synthetic Aperture Radar (SAR) and hyperspectral data. To achieve this, the Michigan Microwave Canopy Scattering (MIMICS) model was initially used to simulate backscatter from vegetated surfaces containing various canopy water contents, across three frequency bands (i.e., L, S, and C). Using this simulated dataset, the influence of the canopy water content on the backscattered signals was further analyzed. In addition, we developed a modified Water-Cloud model which adds in the crown-ground interaction term. Finally, a soil moisture retrieval model for an agricultural region was developed. Alternating polarization data with ASAR and Hyperion hyperspectral data were used to retrieve soil moisture and validate the feasibility of the retrieval model. The field measured data from the Heihe river basin was used to confirm the proposed model. Results revealed an average absolute deviation (AAD) and average absolute relative deviation (AARD) of 0.051 cm3.cm-3 and 19.7%, respectively, between the estimated soil moisture and the field measurements. [ABSTRACT FROM AUTHOR]

The recent Global Inventory Modeling and Mapping Studies (GIMMS) LAI3g product provides a 30-year global times-series of remotely sensed leaf area index (LAI), an essential variable in models of ecosystem process and productivity. In this study, we use a new dataset of field-based LAITrue to indirectly validate the GIMMS LAI3g product, LAIavhrr, in East Africa, comparing the distribution properties of LAIavhrr across biomes and environmental gradients with those properties derived for LAITrue. We show that the increase in LAI with vegetation height in natural biomes is captured by both LAIavhrr and LAITrue, but that LAIavhrr overestimates LAI for all biomes except shrubland and cropland. Non-linear responses of LAI to precipitation and moisture indices, whereby leaf area peaks at intermediate values and declines thereafter, are apparent in both LAITrue and LAIavhrr, although LAITrue reaches its maximum at lower values of the respective environmental driver. Socio-economic variables such as governance (protected areas) and population affect both LAI responses, although cause and effect are not always obvious: a positive relationship with human population pressure was detected, but shown to be an artefact of both LAI and human settlement covarying with precipitation. Despite these complexities, targeted field measurements, stratified according to both environmental and socio-economic gradients, could provide crucial data for improving satellite-derived LAI estimates, especially in the human-modified landscapes of tropical Africa. [ABSTRACT FROM AUTHOR]

Despite longstanding contributions to oceanography, similar use of fluorescence light detection and ranging (LiDAR) in lake settings is not routine. The potential for ship-mounted, multispectral Ultraviolet Fluorescence LiDAR (UFL) to provide rapid, high-resolution data in variably turbid and productive lake conditions are investigated here through a series of laboratory tank and field measurements carried out on Lake Balaton, Hungary. UFL data, calibrated empirically to a set of coinciding conventionally-analyzed samples, provide simultaneous estimates of three important parameters-chlorophyll a(chla), total suspended matter (TSM) and colored dissolved organic matter (CDOM). Successful UFL retrievals from both laboratory and field measurements were achieved for chla (0.01-378 mg·m-3; R = 0.83-0.92), TSM (0.1-130 g·m-3; R = 0.90-0.96) and CDOM (0.003-0.125 aCDOM(440); R = 0.80-0.97). Fluorescence emission at 685 nm is shown through tank measurements to display robust but distinct relationships with chla concentration for the two cultured algae species investigated (cyanobacteria, Cylindrospermopsis raciborskii, and chlorophyta, Scenedesmus armatus). The ratio between fluorescence emissions measured at 650 nm, related to the phycocyanin fluorescence maximum, to that at 685 nm is demonstrated to effectively distinguish these two species. Validation through both laboratory measurements and field measurements confirmed that site specific calibration is necessary. This study presents the first known assessment and application of ship-mounted fluorescence LiDAR in freshwater lake conditions and demonstrates the use of UFL in measuring important water quality parameters despite the more complicated hydro-optic conditions of inland waters. [ABSTRACT FROM AUTHOR]