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Publication date: 15 August 2019

Source: Advances in Space Research, Volume 64, Issue 4

Author(s): Siwoo Kim, Byeong-Un Jo, Eun-Jung Choi, Sungki Cho, Jaemyung Ahn

Abstract

This paper proposes a two-phase framework to predict the impact dispersion area of a reentering space object. A semi-analytic approach is developed that predicts the dispersion area by combining an analytic impact point sensitivity model with corrections to account for aerodynamic drag. The first phase of the framework (preparation phase) generates a database storing the coefficients used in the correction model; this applies the least-squares method to the results of numerical experiments on the space object reentry for various initial states (position and velocity) and aerodynamic characteristics (i.e., ballistic coefficient). The second phase (execution phase: during the reentry event) predicts the dispersion area of the falling object using the correction coefficients database generated in the preparation phase. The validity and computational efficiency of the proposed method are demonstrated through a case study.

Publication date: 1 August 2019

Source: Advances in Space Research, Volume 64, Issue 3

Author(s): Bo Zhang, Xiaolin Jia, Fuping Sun, Kai Xiao, Hailiang Dai

Abstract

A new generation of satellites aimed for the BeiDou-3 global positioning system (BDS-3) has recently been launched. These satellites will play a crucial role in its globalization process. The performance of the BDS-3 experimental satellites has been addressed in previous works. However, performance analysis of the orbits of BDS-3 satellites is still lacking. Using the observation data of the B1I and B3I frequency signals across different stations, this paper provides quality analysis, precise orbit determination (POD), and orbit comparison. The results presented here show that the ranging accuracy of BDS-3 is superior to that of the BeiDou-2 system (BDS-2). The satellite-induced code bias of BDS-2 satellite is not obvious on BDS-3 satellite. The orbit accuracy of BDS-3 satellite is superior to the BDS-2 satellite. The average three-dimensional root-mean-square error (RMS) of two-day overlapping arcs for BDS-3 satellite orbits is within 0.1 m, and the satellite laser ranging (SLR) validation reports that the orbit radial-track is within 6 cm.

Publication date: 15 August 2019

Source: Advances in Space Research, Volume 64, Issue 4

Author(s): Xiuying Wang, Wanli Cheng, Dehe Yang, Dapeng Liu

Abstract

A preliminary validation of the in situ electron density data obtained by CSES, a newly launched electromagnetic satellite in China on Feb. 2, 2018, using the Swarm satellites LP measurements, is carried out in this study to assess the consistency and reliability of the LAP observations onboard CSES. Three ways are implemented to achieve the goal: (1) comparison of the global distribution patterns for both the daytime and nighttime data, (2) comparison of the data between CSES and Swarm at intersecting ground tracks with similar local time, and (3) comparison of the relative relationship between nighttime and daytime data using the nighttime enhancement space climatology phenomenon. The results show that the in situ electron densities estimated by LAP onboard CSES are in good agreement with data from the Swarm satellites in terms of global distributions, local details and relationship between nighttime and daytime data. A systematic bias between them is also found: LAP density estimates are much lower than that of Swarm satellites. However, the highly consistent relative variations between the two datasets proves the electron density dataset of LAP onboard CSES for now is applicable for the relative data variation applications on ionosphere-related studies. Further calibration of the LAP dataset is recommended using electron density data obtained by different measurements.

Publication date: 1 August 2019

Source: Advances in Space Research, Volume 64, Issue 3

Author(s): M. Arslan Tariq, Munawar Shah, Mustafa Ulukavak, Talat Iqbal

Abstract

The rapid increase in the comparative studies between the Global Positioning System (GPS) measured Total Electron Content (TEC) and model-predicted TEC on Earth helps in mitigating the biases in the ionospheric delays of radio waves. In this paper, an evaluation on the performance of the latest International Reference Ionosphere (IRI-2016) modelled TEC is conducted with GPS TEC measurements in different regions of Pakistan during the descending phase of solar cycle 24 (2015–2017). We have analyzed the diurnal, monthly and seasonal variabilities in the measured TEC and compared with IRI-2016 modelled TEC. The diurnal variability of measured TEC is found to be maximum during 06:00–12:00 UT (11:00–17:00 LT) and minimum during 21:00–24:00 UT (02:00–05:00 LT). Moreover, maximal and minimal monthly measured TEC for each station and model are also observed in April and December, respectively. In the summer solstice months at Islamabad station during 2015–2017, the measured TEC are larger than the corresponding modelled TEC by about 19%, 22% and 24%, respectively for each year. On the other hand, the difference between the measured and modelled TEC in summer solstice at Multan station during 2015 is 25% of the normal distribution and at Quetta station during 2016 the difference is about 29% in the summer solstice. The results show that the TEC measurements from GPS coincide with TEC from IRI-2016 during the selected days by a correlation of more than 0.86, while a very high correlation coefficient (0.91–0.99) is shown during each month and season over all the stations for the years 2015–2017. IRI-2016 is a good climate model that can provide accurate estimates of ionospheric delays of radio signals propagated over Pakistan.

Publication date: 1 August 2019

Source: Advances in Space Research, Volume 64, Issue 3

Author(s): Sabyasachi Pal, Dusmanta Patra, Monique Hollick, Sandip K. Chakrabarti

Abstract

We have searched for transient and variable radio sources in the field of Galactic micro-quasar Cygnus X-1 near 1.4 GHz (L band) using data from the Karl G. Jansky Very Large Array. We used twenty years of data between 1983 and 2003. We found a source NVSS J1957+35 showing transient behavior. The source was also mentioned earlier in NVSS and WENSS catalog but its transient nature was not reported earlier. The source is located 23.8 arcminutes far from Cygnus X-1. It is detected many times during the span of our study and it varied between less than 1.9 mJy (3σ) to 201 mJy. NVSS J195754+353513 also showed high intra-day variability. In one occasion, the source rose from ∼15 mJy to ∼170 mJy within 700 s. We detected circularly polarized emission from the source for a limited number of cases with fractional circular polarization varies between 0.14 and 0.17. 2MASS J19575420+3535152 may be the near-infrared counterpart of the source. We compared the properties of the source with other Galactic transient sources having similar properties. The nature of the source is still unknown. We discussed the possible nature of the source.

Publication date: 1 August 2019

Source: Advances in Space Research, Volume 64, Issue 3

Author(s): Nergis Cesur, Aytap Sezer, Jelle de Plaa, Jacco Vink

Abstract

The Galactic supernova remnant (SNR) MSH 15–56 is a member of the class of composite SNRs that consists of the remnant shell and a displaced pulsar wind nebula (PWN). The earlier X-ray observations reported the comet-like morphology of the PWN and the ejecta distribution of the SNR. In this work, we present a study of MSH 15–56 using archival Suzaku data. We investigate the nature of the emission and spectral parameters of the remnant. The X-ray spectra are well fitted with a combination of a thermal and non-thermal model with temperature ∼0.6 keV and photon index ∼2.0. The slightly enhanced abundances of Ne, Mg, S and enhanced abundance of Si confirm the presence of ejected material.

Publication date: 1 August 2019

Source: Advances in Space Research, Volume 64, Issue 3

Author(s): Leyuan Sun, Wende Huang, Yifan Zhou, Jun Yang, Yueke Wang

Abstract

The BeiDou Navigation Satellite System (BDS) has equipped its new-generation satellites with inter-satellite link (ISL) payloads to improve navigation services and system operation. When the inter-satellite ranging and communication are satisfied, we analyze the exploitation of the spare ISL capability for serving atmospheric reentry users. These users can be monitored over the atmospheric reentry segment with ISL transmission, even in the absence of visibility to ground stations and escaping the blackout. We modeled the problem and proposed a link assignment method combining parallel assignment of ISLs and dynamic access of monitor links. First, ISLs were assigned for inter-satellite ranging and communication, which were quantified with the number of different links and timeslot delays respectively. Corresponding assignment algorithm operated in the stations and the computing resource was abundant. Therefore, the heuristic algorithm was used to search the shortest route and the fitness function was determined with a shortest path algorithm. Based on the ISL assignment, extended users were accessed to the ISL network dynamically without influencing performances of the constellation. Because of the uncertainty of users’ states, the monitor link assignment was implemented onboard with short-term predicted states and therefore the computing resource was scarce. Short-term predicted states conquered the deviation of satellite-user visibility. And a simple smallest delay strategy was used to determine the access nodes for users. To evaluate performances of the algorithm, link assignments were implemented for the BeiDou global constellation with 3 users. Each satellite was linked with at least 10 satellites and communicated with stations within 3 timeslots on the basis of ISL assignments. The assignment of monitor links demonstrated the user access did not influence the ranging and communication index of the ISL network and 1-, 2-, and 3-timeslot route delays of users occupy the main parts and the total ratio is larger than 95%.

Publication date: 1 August 2019

Source: Advances in Space Research, Volume 64, Issue 3

Author(s): Peter M.B. Waswa, Sangram Redkar

Abstract

This article analyzes and controls the quasi-periodic attitude motion of a gravity-gradient stabilized spacecraft in eccentric orbit by way of system states augmentation, Lyapunov-Floquet transformation and normal forms simplification. Perturbing torques in the ambient space environment can be shown to engender spacecraft attitude motion represented by nonlinear dynamics coupled in the roll-yaw axes; and, uncoupled planar dynamics in the pitch axis. The non-planar dynamics equations are homogeneous and analytically solvable. However, the pitch attitude motion is nonlinear, possesses parameter-varying coefficients and is subjected to external periodic excitations. Consequently, we transform the unwieldy attitude dynamics into relatively more amenable schemes for analysis and control law synthesis. Subsequently, we demonstrate the implementation of linear and nonlinear control laws (i.e. bifurcation and sliding mode control laws) on the relatively acquiescent transformed attitude dynamics. By employing a two-pronged approach, the quasi-periodic planar motion is independently shown to be stabilizable via the nonlinear control approaches.

Publication date: 1 August 2019

Source: Advances in Space Research, Volume 64, Issue 3

Author(s): Dheyaa Ameri, Eino Valtonen

Abstract

We have searched for solar proton events consisting of both solar energetic particles (SEPs) accelerated near the Sun and energetic storm particles (ESPs) accelerated by interplanetary shocks driven by coronal mass ejections (CMEs) and observed near the time when the shock passes the observer. The purpose of this study is to investigate the possibilities and advantages of using energetic particle observations for mid-term (warning time several hours) forecasting of geomagnetic storms or as a support for longer-term forecasting methods based on solar observations. The study period extends from May 1996 to December 2017 covering the entire solar cycle 23 and the major part of solar cycle 24. Using two particle energies, 2 and 20 MeV, we found 95 SEP–ESP events of which 65 were associated with geomagnetic storms with Dst ⩽ −50 nT caused by CMEs. We performed correlation analysis between log10|Dst (nT)| and various parameters characterising the particle events or the associated CMEs. We found the best correlations for the single independent variables ΔtESP-SEP (r=-0.47±0.08), which is the difference between the ESP peak time and SEP onset time, the CME direction parameter DP (r=0.47±0.10), and the logarithm of the maximum ESP energy log10[EESPmax (MeV)] (r=0.44±0.11). Using a linear combination of these three variables improves the correlation (r=0.68±0.07). We suggest that an empirical equation based on these three parameters and requiring only coronagraph observations of CMEs and energetic particle measurements in interplanetary space can be used for mid-term forecasting of geomagnetic storm strengths. We found that 74% of the strongest storms (Dst ⩽ -200 nT) during the study period were associated with energetic particle events. The average warning time and its standard deviation for all geomagnetic storms associated with SEP–ESP events was (15±10) hours.

Publication date: 1 August 2019

Source: Advances in Space Research, Volume 64, Issue 3

Author(s): E. Delande, J. Houssineau, J. Franco, C. Frueh, D. Clark, M. Jah

Abstract

This paper presents the filter for Hypothesised and Independent Stochastic Populations (HISP), a multi-object joint detection/tracking algorithm derived from a recent estimation framework for stochastic populations, in the context of Space Situational Awareness. Designed for multi-object estimation problems where the data association between tracks and collected observations is moderately ambiguous, the HISP filter has a linear complexity with the number of objects and the number of observations. Because of its scalable complexity, the HISP filter is a promising solution for the construction of a large-scale catalogue of Resident Space Objects. We illustrate the HISP filter on a challenging surveillance scenario built from real data for 115 satellites of PlanetLabs’ Dove constellation, and simulated observations collected from two sensors with limited coverage and measurement noise, in the presence of false positives and missed detection.

Publication date: 1 August 2019

Source: Advances in Space Research, Volume 64, Issue 3

Author(s): Ayman Soliman, Ling Han

Abstract

Remote sensing data, such as satellite images, and remote sensing derived digital elevation models (DEMs) are credited by simplifying many geological processes that require costly and laborious field work, such as lineament extraction. Furthermore, the recent increase in the availability of DEMs from many free open sources as well as their advantages over satellite imagery have promoted their wide application as remote sensing methods for lineament extraction. The quality of a DEM affects the results of its application, and this quality is controlled by its vertical accuracy and spatial resolution. The objectives of this study were to assess and verify the effects of the vertical accuracies of DEMs on lineament extraction. The area around Baoji city, Shaanxi province, China, was selected as a case study and the lineaments were automatically extracted using the LINE algorithm of PCI Geomatica from three DEMs with different vertical accuracies: tri stereo ZY3 imagery derived DEM, SRTM1V3, and ASTGDEMV2. All of these DEMs have 1″ spatial resolution (approx. 30 m). The results showed that the vertical accuracy of the applied DEM affects the number, length, and density of the extracted lineaments, where these quantities increase with increasing vertical accuracy of the DEM.

Publication date: 1 August 2019

Source: Advances in Space Research, Volume 64, Issue 3

Author(s): H. Fuqua Haviland, G.T. Delory, I. de Pater

Abstract

The global electromagnetic induction response of the Moon has been solved numerically for several electrical conductivity profiles using the finite-element method. Here we demonstrate the capability and applicability in both two and three spatial dimensions for any input magnetic field time series measured at the Moon. We discuss the applicability of a vacuum approximation to the induced magnetic field response to the lunar plasma environment and the challenges of isolating geomagnetic induced fields including the interaction with the lunar wake structure. We perform three validation analyses comparing our vacuum model response to analytic solutions: (1) the time domain response to a step impulse or tangential discontinuity within the solar wind, (2) the time domain response to a ramp driving function, and (3) the broadband frequency domain response. We fit the analytic solutions to a root-mean-square error of better than 1% for all cases. We analyze the accuracy range and demonstrate our model’s capability of resolving interior structure from Apollo magnetometer data. We present the first time domain numerical solution of the induced magnetic field response of the Moon in vacuum for any driving input signal and any interior conductivity profile, building on previous Apollo era work. Lastly, we discuss the trade-offs between model accuracy and performance, which is of particular concern for large datasets and iterative optimizations. The transfer function method developed here is applicable to other airless body two-point magnetometer measurements including Apollo, ARTEMIS, and future lunar geophysical networks.

Publication date: 1 August 2019

Source: Advances in Space Research, Volume 64, Issue 3

Author(s): Fernanda Watanabe, Enner Alcântara, Nariane Bernardo, Caroline de Andrade, Ana Carolina Gomes, Alisson do Carmo, Thanan Rodrigues, Luiz Henrique Rotta

Abstract

In this work, we investigated the trophic gradient in three reservoirs cascading in Tietê River, Southeast Brazil, based on their chlorophyll-a (chl a) concentration. The goal of this study was to identify spatial patterns in the chl a distribution, which are associated with the filtration process caused by reservoir cascade. Hence, maps of chl a content were developed considering a short time series of MSI Sentinel-2A images (2016–2018). A chl a prediction algorithm was applied to images, whose calibration was done from data collected during a severe drought (2014), which led to intense harmful algal blooms (HABs) and after the drought (2016). The outcomes showed that 20 m spatial resolution of MSI Sentinel-2A images are suitable in estimating pigment concentration in small and middle reservoirs. In addition, the Sen2cor atmospheric correction tool exhibited good performance in removing the scattering effects. Its application in retrieving the chl a content also presented good results. Besides reservoir order in the cascade, the storage system showed to be a factor that also affects the trophic state in downstream impoundments.

Publication date: 1 August 2019

Source: Advances in Space Research, Volume 64, Issue 3

Author(s): Ruchi Bala, Rajendra Prasad, Vijay Pratap Yadav

Abstract

Applications of satellite thermal images are usually impeded by the low spatial resolution, leading to the development of various downscaling techniques. The thermal sharpening model based on the relationship between LST and Normalized Difference Vegetation Index (NDVI) was developed which shows good results in agricultural areas but may not be applicable for urban areas. Therefore, the present study focuses on determining improved downscaling techniques that shows good results in different urban regions. Hence, the performance of six different indices, namely NDVI, Enhanced Vegetation Index (EVI), Normalized Difference Built-up Index (NDBI), Urban Index (UI), Normalized Difference Soil Index (NDSI) and Normalized Difference Water Index (NDWI) were compared for thermal sharpening using Disaggregation of Radiometric Temperature (Distrad) Model over four different cities in India i.e. Bikaner, Hyderabad, Vadodara and Varanasi. LST obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) sensors (930 m) were disaggregated to the spatial resolution of Landsat 8 Thermal Infrared Sensor (TIRS) (100 m) and compared with the Landsat LST. The performance of NDBI was found better as compared to other indices in the four cities having Root Mean Square Error (RMSE) = 1.54 K, 1.24 K, 1.10 K and 1.03 K, respectively. Further, NDBI was used for disaggregation using two robust regression techniques i.e. Least Median Square Regression (LMSR) and Bi-square regression which shows better results as compared to that of Distrad model in the four study sites. Bi-square regression method shows RMSE values of 1.30 K, 1.21 K, 0.98 K and 0.97 K, respectively for the four study sites. The LMSR and Bi-square regressions are less sensitive to outliers resulting in increased accuracy of downscaled LST.

Publication date: 1 August 2019

Source: Advances in Space Research, Volume 64, Issue 3

Author(s): Sk. Ziaul, Swades Pal

Abstract

The present study intended to analyze the spatio-temporal outdoor thermal condition during the winter, summer and post-monsoon seasons of 2010 and 2016 by using Discomfort Index (DI) and Physiological Equivalent Temperature (PET) in the English Bazar Municipality (India). DI value has been computed based on air temperature and relative humidity data retrieved from satellite imageries and mobile field survey, while PET value has been produced with the RayMan Model. Result of DI reveals that built up area experienced partially uncomfortable-Cold (C) in winter, extremely uncomfortable in summer and partially uncomfortable-W in post-monsoon both in 2010 and 2016. But the areal extension under these discomfort zone significantly increased in 2016 compare to 2010, for example area under extreme uncomfortable and partially uncomfortable zones-Warm (W) was 3281.4 ha and 983.07 ha respectively in 2010 but it increased 4815.83 ha and 3291.74 ha respectively in 2016. Mean monthly PET value ranges from 15 °C to 27 °C. But in extreme hours, 58.78% area of the town experienced strong cold stress with the range of PET of 9 to 11 °C in winter season. In summer seasons 82.41%, 16.91%, and 0.67% areas respectively fall under the physiologically strong, extreme and scorching type of heat stress.

Publication date: 15 August 2019

Source: Advances in Space Research, Volume 64, Issue 4

Author(s): Chunxing Wang, Nan Ma, Yanfang Ming, Quan Wang, Jinfeng Xia

Abstract

A three-dimensional convolutional neural network (3D-CNN) is proposed and applied to the identification of land types from hyperspectral images. Due to the advantages of the combined use of the spectral-spatial features of hyperspectral imagery, high accuracy identification of most objects can be realized. However, too many wavelengths increase information redundancy between adjacent bands and interfere with classification accuracy to some extent, complicating achievement of better results for the identification of ground objects with relatively small differences in spectral and spatial domains. To solve such problems, in this paper, the Jeffries-Matusita (J-M) distance is introduced to select effective bands to reduce the redundancy of spectral information for identifying objects with similar features. This method is based on a 3D-CNN considering pixel spectral and spatial information. The optimal band combination algorithm based on the J-M distance is first used to extract spectral features of hyperspectral data while reducing feature dimensions. Then, the 3D-CNN is applied to mine spectral and spatial features from the hyperspectral images. Finally, a Softmax classifier is used to classify land types based on the high-level features learned by the 3D-CNN. Experiments were carried out on data from an area of north-western Indiana and a Pavia university scene. In such images, some objects have very similar spectral and spatial features. The results were compared with the current 3D-CNN land type classification and show that both methods can achieve high-precision identification of most land types, but for objects with similar features, the method proposed in this article has obvious advantages.

Publication date: 1 August 2019

Source: Advances in Space Research, Volume 64, Issue 3

Author(s): Huan N. Do, Tat-Jun Chin, Nicholas Moretti, Moriba K. Jah, Matthew Tetlow

Abstract

With the rapid growth in space utilisation, the probability of collisions between space assets and orbital debris also increases substantially. To support the safe utilisation of space and prevent disruptions to satellite-based services, maintaining space situational awareness (SSA) is crucial. A vital first step in achieving SSA is detecting the man-made objects in orbit, such as space-crafts and debris. We focus on the surveillance of Geo-stationary (GEO) orbital band, due to the prevalence of major assets in GEO. Detecting objects in GEO is challenging, due to the objects being significantly distant (hence fainter) and slow moving relative to the observer (e.g., a ground station or an observing satellite). In this paper, we introduce a new detection technique called GP-ICP to detect GEO objects using optical sensors that is applicable for both ground and space-based observations. Our technique is based on mathematically principled methods from computer vision (robust point set registration and line fitting) and machine learning (Gaussian process regression). We demonstrate the superior performance of our technique in detecting objects in GEO.

Simulating lightning NO production in CMAQv5.2: evolution of scientific updates
Daiwen Kang, Kenneth E. Pickering, Dale J. Allen, Kristen M. Foley, David C. Wong, Rohit Mathur, and Shawn J. Roselle
Geosci. Model Dev., 12, 3071-3083, https://doi.org/10.5194/gmd-12-3071-2019, 2019
Lightning strikes produce significant amount of nitrogen oxides and the resulting atmospheric chemistry causes one of the primary air pollutants, ground-level ozone, to change. In this paper, we documented the evolution of scientific updates for lightning-induced nitrogen oxides schemes in the CMAQ model. The updated observation-based schemes are good for retrospective applications, while the parameterized scheme can estimate lightning nitrogen oxides for applications without observations.

Development of Korean Air Quality Prediction System version 1 (KAQPS v1): an operational air quality prediction system with focuses on practical issues
Kyunghwa Lee, Jinhyeok Yu, Sojin Lee, Mieun Park, Hun Hong, Soon Young Park, Myungje Choi, Jhoon Kim, Younha Kim, Jung-Hun Woo, Sang-Woo Kim, and Chul H. Song
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-169,2019
Manuscript under review for GMD (discussion: open, 0 comments)
For the purpose of providing reliable and robust air quality predictions, an operational air quality prediction system was developed for the main air quality criteria species in South Korea (PM10, PM2.5, CO, O3, and SO2) by preparing the initial conditions for model simulations via data assimilation using satellite- and ground-based observations. The performance of the developed air quality prediction system was evaluated using ground in-situ data during the KORUS-AQ campaign period.

A practical information-centered technique to remove a priori information from lidar optimal-estimation-method retrievals
Ali Jalali, Shannon Hicks-Jalali, Robert J. Sica, Alexander Haefele, and Thomas von Clarmann
Atmos. Meas. Tech., 12, 3943-3961, https://doi.org/10.5194/amt-12-3943-2019, 2019
This paper builds upon the work in von Clarmann and Grabowski (2007) concerning the a priori profile influence in the optimal estimation method applied to active remote sensing measurements, with examples given for lidar retrievals of temperature and water vapor mixing ratio. The optimal estimation method is a new technique for many active remote sensing researchers. This study gives insight into understanding the effect on retrievals of the a priori information.