Showing papers in "Advances in Space Research in 2021"
TL;DR: Wang et al. as discussed by the authors described the scientific objectives and payloads of Tianwen-1, China's first exploration mission to Mars, which lifted off in July 2020 for a journey to Mars where it should arrive in February 2021.
Abstract: This paper describes the scientific objectives and payloads of Tianwen-1, China’s first exploration mission to Mars. An orbiter, carrying a lander and a rover, lifted-off in July 2020 for a journey to Mars where it should arrive in February 2021. A suite of 13 scientific payloads, for in-situ and remote sensing, autonomously commanded by integrated payload controllers and mounted on the orbiter and the rover will study the magnetosphere and ionosphere of Mars and the relation with the solar wind, the atmosphere, surface and subsurface of the planet, looking at the topography, composition and structure and in particular for subsurface ice. The mission will also investigate Mars climate history. It is expected that Tianwen-1 will contribute significantly to advance our scientific knowledge of Mars.
107 citations
Saleh Abdalla1, Abdolnabi Abdeh Kolahchi, Michael Ablain, Susheel Adusumilli2 +357 more•Institutions (88)
TL;DR: In 2018, the 25th year of development of radar altimetry was celebrated and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences as discussed by the authors.
Abstract: In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology.
The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the “Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other Earth observation measurements to in situ data. Section 6 identifies the data and methods and provides some accuracy and resolution requirements for the wet tropospheric correction, the orbit and other geodetic requirements, the Mean Sea Surface, Geoid and Mean Dynamic Topography, Calibration and Validation, data accuracy, data access and handling (including the DUACS system). Section 7 brings a transversal view on scales, integration, artificial intelligence, and capacity building (education and training). Section 8 reviews the programmatic issues followed by a conclusion.
105 citations
TL;DR: In this article, the authors investigate the contribution of six altimeter missions that have been placed into geodetic mapping phases for more than one year and compare the composite (all six altimeters) grids of east and north vertical deflection to matching grids where one altimeter has been omitted evaluate their contribution versus latitude.
Abstract: Satellite radar altimetry collected during a number of geodetic missions has provided a new understanding of the topography and tectonics of the deep oceans. As altimeter performance and coverage improves, smaller structures are revealed. Here we investigate the contribution of six altimeter missions that have been placed into geodetic mapping phases for more than one year. Two types of evaluations are performed. We first compare the composite (all six altimeters) grids of east and north vertical deflection to matching grids where one altimeter has been omitted evaluate their contribution versus latitude. We then estimate the noise in each altimeter by computing the median absolute deviation of the profiles with the best composite grid. Both analyses show that SARAL/AltiKa provides the greatest contribution and ERS-1 no longer provides any significant improvement. The major limitation for recovering small scale gravity features is the sea surface roughness from ocean waves. There have been steady improvements in instrumentation and processing methods that will continue into the future with higher frequency radars and interferometric swath altimeters planned for future missions.
76 citations
TL;DR: In this article, a landslide susceptibility map (LSM) was generated considering the hybrid ensemble of machine learning approaches using different sample ratios Random Forest (RF) as the base classifier an ensemble with bagging, Rotation Forest (RTF), and Random Subspace (RS) Meta classifiers were used for spatial landslide modeling.
Abstract: Landslide is a big problem in the mountainous region all over the world Sikkim Himalayan region is also suffering from landslide problem This study's main objective was to generate landslide susceptibility map (LSM) considering the hybrid ensemble of machine learning approaches using different sample ratios Random Forest (RF) as the base classifier an ensemble with bagging, Rotation Forest (RTF), and Random Subspace (RS) Meta classifiers were used for spatial landslide modeling First, collected 86 landslides locations through field investigation and from Sikkim district disaster office were mapped as a landslide inventory Collected landslide locations were categorized into training and testing datasets randomly using four sample ratios (50:50, 60:40, 70:30 and 80:20) Based on the four sampling ratios and fifteen conditioning factors, a total of sixteen LSMs were prepared using RF, Bagging-RF (B-RF), RTF-RF and RS-RF in GIS platform For assessing the modeling accuracy and comparison among these, the area under the receiver operating characteristics (AUROC) and other statistical methods such as root-mean-square-error (RMSE), mean-absolute-error (MAE) and R-index methods were used The overall proficiency of RS-RF (AUC = 0871, 0847 of 50%:50%, AUC = 0925, 0931 of 60%:40%, AUC = 0933, 0939 of 70%:30%; AUC = 0927, 0933 of 80%:20%) was found to be substantially greater than the results of RF, B-RF, and RTF-RF The RS-RF model and 70:30 sample ratio had the highest goodness-of-fit and accuracy as per the RMSE, MAE, and R-index methods Furthermore, the model based on RS-RF is a promising and acceptable way of mapping regional landslides
43 citations
TL;DR: A novel adaptive fuzzy neural network (FNN) control scheme is proposed for the trajectory tracking control of an attitude-controlled free-flying space manipulator in the presence of output constraints and input nonlinearities.
Abstract: Space manipulator is considered as one of the most promising technologies for future space activities owing to its important role in various on-orbit serving missions. In this paper, a novel adaptive fuzzy neural network (FNN) control scheme is proposed for the trajectory tracking control of an attitude-controlled free-flying space manipulator in the presence of output constraints and input nonlinearities. The parametric uncertainties and external disturbances are also taken into the consideration. First, a model-based controller is designed by using the barrier Lyapunov function (BLF) to prevent the position tracking errors from violating the predefined output constraints. Then, an adaptive FNN controller is designed by using two FNNs to compensate for the lumped uncertainties and input nonlinearities, respectively. Rigorous theoretical analysis for the semiglobal uniform ultimate boundedness of the whole closed-loop system is provided. The proposed adaptive FNN controller can guarantee the position and velocity tracking errors converge to the small neighborhoods about zero, while ensuring the position tracking errors within the output constraints even in the presence of input nonlinearities. To the best of the authors’ knowledge, there are relatively few existing controllers can achieve such excellent control performance in the same conditions. Numerical simulations illustrate the effectiveness and superiority of the proposed control scheme.
42 citations
TL;DR: The LightSail 2 mission as discussed by the authors is the culmination of a decade-long program sponsored by The Planetary Society to advance solar sailing technology, which demonstrated controlled solar sailing in Earth orbit using a CubeSat platform.
Abstract: The LightSail 2 mission is the culmination of a decade-long program sponsored by The Planetary Society to advance solar sailing technology. The objective of LightSail 2 is to demonstrate controlled solar sailing in Earth orbit using a CubeSat platform. The LightSail 2 attitude is controlled using a single-axis momentum wheel and magnetic torque rods. During solar sailing operations, two 90 degree slews are performed each orbit to harness momentum from solar photons. Flight data show that LightSail 2 is successfully controlling its orientation relative to the Sun, and the controlled thrust from solar radiation pressure is measurably reducing the rate of orbital decay. The Planetary Society declared LightSail 2 mission success on July 31, 2019. This paper provides an overview of the LightSail 2 mission implementation, including the design of the flight system and flight software, and the pre-launch testing program. A summary of LightSail 2 mission operations is provided, including a description of the ground system. Solar sailing performance is presented, and anomalies encountered during the mission are discussed. The flight team continues to refine solar sailing performance and conduct on-orbit imaging for engineering purposes and to engage public interest. The LightSail program is entirely donor-funded, with over 50,000 contributors around the globe.
39 citations
TL;DR: In this paper, the 3D inversion of aeromagnetic data was employed to imagine the depth and geometry of the magnetized ore bodies in the zones that identified by processing ASTER data.
Abstract: Due to high metal values and raised difficulties in finding superficial deposits, the exploration for mineral resources needs to reach greater depths. To achieve this objective, integrating ASTER and 3D inversion of aeromagnetic can be a useful tool in imaging deep magnetic mineralization hosting-structures. In this study, we present such integrated approach for deep mineral exploration in some promising zones of Gabal (G) Semna region, Eastern Desert (ED) of Egypt. Aeromagnetic data was used to delineate the structures and their relation to ore deposits and ASTER data was utilized for mapping lithological units and the hydrothermal zones. The 3D inversion was employed to imagine the depth and geometry of the magnetized ore bodies in the zones that identified by processing ASTER data. The 3D magnetic inversion revealed that mafic rocks and metavolcanics exhibit high-amplitude magnetic anomalies. High amplitude (positive) magnetic anomalies are joined with the large susceptibilities metavolcanics. Alteration zones in the mafic to basic bedrock and alongside major fault systems are high potential zones that revealed by ASTER image analysis. Aster and aeromagnetic data were used to map and alteration zones surface geology that can host mineralization and the 3D inversion was applied to outline the subsurface extent of these promising areas. This approach can be broadly used for deep mineral exploration in the Egyptian ED and identical areas around the world.
35 citations
TL;DR: A DME service volume model based on path loss between a pair of transmitting and receiving antennas has been proposed and results indicate about the necessity of actions for further development of global navigational aids network in order to guarantee safe airlines connections around the globe.
Abstract: Safety of air transportation strongly depends on the performance of on-board positioning sensors. Positioning by data from navigational aids is considered by international aviation community as one of the main stand-by positioning approaches onboard of civil airplanes. However, only positioning by pair of distance measuring equipment (DME) meets requirements of Performance-Based Navigation. A DME service volume model based on path loss between a pair of transmitting and receiving antennas has been proposed in the paper. The model takes into account the influence of relief on radio waves propagation and diffraction from high-altitude elements of relief. The proposed model has been used in the analysis of DME global network performance. In particular, performance of a global network is analyzed based on availability area of DME service, area of positioning by pairs of DME/DME support, availability of particular positioning accuracy, and areas of meeting various RNAV requirements. Obtained results indicate that only in 27.76% of global airspace a DME service can be provided. However, only within 15.9% of airspace, a DME/DME positioning can be used. Results of the analysis indicate about the necessity of actions for further development of global navigational aids network in order to guarantee safe airlines connections around the globe.
35 citations
TL;DR: The feasibility of the Milani CubeSat mission is assessed and a preliminary solution to cover the operational mission profile of Milani in the close-proximity of Didymos system is provided.
Abstract: CubeSats offer a flexible and low-cost option to increase the scientific and technological return of small-body exploration missions. ESA’s Hera mission, the European component of the Asteroid Impact and Deflection Assessment (AIDA) international collaboration, plans on deploying two CubeSats in the proximity of binary system 65803 Didymos, after arrival in 2027. In this work, we discuss the feasibility and preliminary mission profile of Hera’s Milani CubeSat. The CubeSat mission is designed to achieve both scientific and technological objectives. We identify the design challenges and discuss design criteria to find suitable solutions in terms of mission analysis, operational trajectories, and Guidance, Navigation, & Control (GNC) design. We present initial trajectories and GNC baseline, as a result of trade-off analyses. We assess the feasibility of the Milani CubeSat mission and provide a preliminary solution to cover the operational mission profile of Milani in the close-proximity of Didymos system.
34 citations
TL;DR: In this article, the authors present results of contemporary coastal sea level changes along the coasts of Western Africa, obtained from a dedicated reprocessing of satellite altimetry data done in the context of the ESA ‘Climate Change Initiative’ sea level project.
Abstract: We present results of contemporary coastal sea level changes along the coasts of Western Africa, obtained from a dedicated reprocessing of satellite altimetry data done in the context of the ESA ‘Climate Change Initiative’ sea level project. High sampling rate (20 Hz) sea level data from the Jason-1 and Jason-2 missions over a 14-year-long time span (July 2002 to June 2016) are considered. The data were first retracked using the ALES adaptative leading edge subwaveform retracker. The X-TRACK processing system developed to optimize the completeness and accuracy of the corrected sea level time series in coastal ocean areas was then applied. From the 14-year long sea level time series finally obtained, we estimate sea level trends along the Jason-1 & 2 tracks covering the study region. We analyze regional variations in sea level trends, with a focus on the changes observed between the open ocean to the coastal zone. Compared to the conventional 1 Hz sea level products dedicated to open ocean applications, the retracked 20 Hz measurements used in this study allow us to retrieve valid sea level information much closer to the coast (less than 3–4 km to the coast, depending on the satellite track location). The main objective of this study is twofold: (1) provide sea level products in the coastal areas from reprocessed altimetry data and (2) check whether sea level changes at the coast differ from that reported in the open ocean with conventional altimetry products. In the selected region, results show that over the study period, sea level trends observed near the coast of Western Africa are significantly different than offshore trends. In order to assess the robustness of the results, detailed analyses are performed at several locations to discriminate between possible drifts in the geophysical corrections and physical processes potentially able to explain the sea level changes observed close to the coast.
34 citations
TL;DR: In this article, the authors analyzed the scientific exploration tasks of CE-5 mission conducted on the lunar surface, and carried out the scientific payload system architecture design and individual scientific payload design with the scientific task requirements as the target, and proposed the working mode and main technical index requirements of the payloads.
Abstract: In the early morning on December 17, 2020 Beijing time, China's chang'E-5 probe successfully returned to the Earth with 1731 g of lunar samples after completing drilling, shoveling, packaging of lunar soil and scientific exploration on lunar surface. It is the successful completion of the third phase of China's lunar exploration project, namely “circling, landing and returning to the moon”. The scientific objectives of CE-5 mission are to carry out in situ investigation and analysis of the lunar landing region, laboratory research and analysis of lunar return samples. This paper analyzes scientific exploration tasks of CE-5 mission conducted on the lunar surface, and carries out the scientific payload system architecture design and individual scientific payload design with the scientific exploration task requirements as the target, and proposes the working mode and main technical index requirements of the scientific payloads. Based on the preliminary geological background study of the Mons Ruemker region which is the landing region of CE-5, the lunar scientific exploration and the laboratory physicochemical characterization of the return samples are of great scientific significance for our in-depth understanding of the formation and evolution of the Earth-Moon system and the chemical evolution history of the lunar surface.
TL;DR: In this paper, the authors used the multilayer perceptron neural network (MLP) as the base classifier and the hybrid ensemble machine learning methods i.e. Bagging and Dagging were used as the functional classifiers.
Abstract: The main aim of this study is to evaluate the gully erosion susceptibility coupling the artificial intelligence and machine learning ensemble approaches. In the present study, the multilayer perceptron neural network (MLP) was used as the base classifier and the hybrid ensemble machine learning methods i.e. Bagging and Dagging were used as the functional classifiers. The Hinglo river basin, an important tributary of the Ajay River was selected as the study area, consists with the parts of Chhotonagpur plateau and Rarh lateritic region. The study area is facing the gully erosion problems which are interrupted the growth of the agriculture. The gully erosion susceptibility maps (GESMs), prepared by MLP, MLP-Bagging and MLP-Dagging were classified into four classes such as low, moderate, high and very high susceptibility classes with the help of natural break method (NBM) in GIS environment. The very high susceptibility class covered 19.41% (MLP), 13.52% (MLP-Bagging) and 15.30% (MLP-Dagging) areas of the basin. For the evaluation and comparison of the models, receiver operating characteristics (ROC), accuracy, mean absolute error (MAE) and root mean square error (RMSE) were applied. Overall, all the gully erosion susceptibility models were performed as excellent. Integration of hybrid ensemble models with MLP has increase the accuracy of the MLP models. Among these models MLP-Dagging has achieved the highest accuracy in compare to the other models. The importance of the selected factors in the present study was assessed by the Relief-F method. The results show that the soil type factor has the highest predictive performance. Sensitivity analysis also showed soil type as most important factor. The gully erosion susceptibility maps (GESMs) are considered as the efficient tool which could be used to take the necessary steps for mitigating and controlling the soil erosion problem and sustainable environmental management and development.
TL;DR: Based on Sentinel-1A SAR data, combined with the urban geological background, the ground deformation in Lanzhou New District (LZND) from 2017 to 2019 was analyzed as discussed by the authors.
Abstract: Large-scale land creation projects involving the cutting of mountains to infill gullies for construction have been carried out in Lanzhou New District (LZND). However, there is an urgent need for comprehensive and detailed research on the spatiotemporal evolution of ground deformation in LZND. Based on Sentinel-1A SAR data, combined with the urban geological background, the ground deformation in LZND from 2017 to 2019 was analysed. Two independent, multi-temporal techniques, persistent scatterers interferometry (PS-InSAR) and the small baseline subset (SBAS-InSAR), were used to calculate the deformation time series, and the results were cross-verified. The time series-monitoring results of the SBAS and PS calculations exhibited strong consistency in LZND and verified the high reliability of the experimental results. The results showed the whole surface of the LZND from March 2017 to October 2019 maintained stability, and the deformation rate was primarily in the range of −10 to 10 mm/year. However, ground deformation in the Xicha area was evident. The maximum annual deformation rates monitored by SBAS-InSAR and PS-InSAR were −52.48 mm/year and −56.35 mm/year, respectively. The most typical deformation areas include the built-up area and the land creation area. The surface subsidence area was concentrated in the filling area. The ground deformation range of LZND kept expanding and accelerating from 2017 to 2019. Land creation, urban construction, geology and precipitation were the primary factors contributing to local severe ground deformation. The results of this study provide reference for the regional urban planning in LZND.
TL;DR: An extensive review of gossamer space structure considering different categories of large deployable antennas, understanding the behaviour of thin membrane, their static and dynamic characteristics, wrinkling control, shape control, and recent advances in deployment techniques of large Deployable antenna structures are covered.
Abstract: The gossamer space structures are very large and ultra-lightweight structures. A large aperture-based space structure is highly efficient in capturing signals from a wide coverage area. However, their deployment in space has been a critical challenge to date. Extensive research has been carried out on various types of gossamer structures used for earth exploration and deep space applications. Space antenna, in general, should have a large electrical aperture, be light in weight with small stowage volume, be easily deployable in space, and thermally stable. The antenna consists mainly of a reflector as a major part and a torus for supporting the reflector, electronic control unit, and struts. This paper covers an extensive review of gossamer space structure considering different categories of large deployable antennas. More attention has been given to a large membrane-based antenna having a parabolic reflector. This work includes the study of designs, analyses, and development of prototypes and successful deployment of space structures in orbit. We emphasize understanding the behaviour of thin membrane, their static and dynamic characteristics, wrinkling control, shape control of thin membrane reflector, and recent advances in deployment techniques of large deployable antenna structures.
TL;DR: In this paper, a new coastal sea level product called X-TRACK/ALES is developed in order to support advances in coastal sea-level variability studies, which can extend the spatial coverage of sea level altimetry data up to 3.5 km in the land direction.
Abstract: In the context of the ESA Climate Change Initiative project, a new coastal sea level altimetry product has been developed in order to support advances in coastal sea level variability studies. Measurements from Jason-1,2&3 missions have been retracked with the Adaptive Leading Edge Subwaveform (ALES) Retracker and then ingested in the X-TRACK software with the best possible set of altimetry corrections. These two coastal altimetry processing approaches, previously successfully validated and applied to coastal sea level research, are combined here for the first time in order to derive a 16-year-long (June 2002 to May 2018), high-resolution (20-Hz), along-track sea level dataset in six regions: Northeast Atlantic, Mediterranean Sea, West Africa, North Indian Ocean, Southeast Asia and Australia. The study demonstrates that this new coastal sea level product called X-TRACK/ALES is able to extend the spatial coverage of sea level altimetry data ~3.5 km in the land direction, when compared to the X-TRACK 1-Hz dataset. We also observe a large improvement in coastal sea level data availability from Jason-1 to Jason-3, with data at 3.6 km, 1.9 km and 0.9 km to the coast on average, for Jason-1, Jason-2 and Jason-3, respectively. When combining measurements from Jason-1 to Jason-3, we reach a distance of 1.2–4 km to the coast. When compared to tide gauge data, the accuracy of the new altimetry near-shore sea level estimations also improves. In terms of correlations with a large set of independent tide gauge observations selected in the six regions, we obtain an average value of 0.77. We also show that it is now possible to derive from the X-TRACK/ALES product an estimation of the ocean current variability up to 5 km to the coast. This new altimetry dataset, freely available, will provide a valuable contribution of altimetry in coastal marine research community.
TL;DR: In this paper, the authors used three machine learning (ML) models including Self-Organization Map (SOM), Radial Basis Function Neural Network (RBFNN), and Multi-layers Perceptron (MLP) to produce flood susceptibility maps.
Abstract: The main objective of this study was to produce flood susceptibility maps for Tajan watershed, Sari, Iran using three machine learning (ML) models including Self-Organization Map (SOM), Radial Basis Function Neural Network (RBFNN), and Multi-layers Perceptron (MLP). To reach such a goal, different physical-geographical factors (criteria) were integrated and mapped. 212 flood inventory map was randomly divided into training and testing datasets, where 148 flood locations (70%) were used for training and the remaining 64 locations (30%) were employed for testing. Model validation was performed using several statistical indices and the area under the curve (AUC). The results of the correlation matrix showed, three factors slope (0.277), distance from river (0.263), and altitude (0.223) were the most important factors affecting flood. The accuracy evaluation of the flood susceptibility maps through the AUC method and K-index shows that in the validation phase RBFNN (AUC = 0.90) outperform the MLP (AUC = 0.839) and SOM (AUC = 0.882) models. The highest percentage flood susceptibility of the area in MLP, SOM and RBFNN models is related to moderate (28.7%), very low (40%) and low (37%), respectively. Also, the validation results of the models using the Relative Flood Density (RFD) approach showed that very high class had the highest RFD value.
TL;DR: Experimental and analyses results show that the proposed algorithm has good performance in terms of high level of security, large enough key-space, tolerance to Single Event Upsets (SEU) as well as low time complexity.
Abstract: With the rapid growth of the number of Earth observation satellite (EOS) supporting critical applications, it is required to improve the security techniques to protect the sensitive data and images during the transmission between the satellites and the ground stations. This paper introduces a new satellite image encryption algorithm based on the Linear Feedback Shift Register (LFSR) generator, SHA 512 hash function, hyperchaotic systems, and Josephus problem. LFSR generates a matrix that is used to construct the 512-bits value of the hash function. These bits are used to set the initial values and parameters of the proposed encryption algorithm. Firstly, the six dimensions (6-D) hyperchaotic system is divided into three parts, where every two equations are considered as one part. Secondly, the 1-D hyperchaotic logistic-tent system is considered as the controller to select one part. The selected part is used to generate a matrix that is XORed with the original image. Thirdly, the scrambling operation by Josephus sequences is applied to the output of the previous step by scrambling the rows and the columns according to the selected part to produce the pre-encrypted image. Finally, if the number of iterations is less than the required number which is considered as a parameter of the secret key, the previous operations will be repeated in the pre-encrypted image; otherwise, the pre-encrypted image is considered as the final cipher image. Experimental and analyses results show that the proposed algorithm has good performance in terms of high level of security, large enough key-space, tolerance to Single Event Upsets (SEU) as well as low time complexity.
TL;DR: In this paper, the authors present a review of the limitations and potentials of each sensor onboard the Sentinel-3 satellite and investigate the added value of using these three sensors co-located on the same platform for river discharge monitoring.
Abstract: The monitoring of rivers is not the primary objective of the Sentinel-3 mission. The first satellite of the constellation was launched in February 2016 and so far no study has investigated the joint use of altimeter, near-infrared and thermal sensors for discharge estimation. Nevertheless, similar sensors onboard other platforms have showed their ability to estimate river discharge also in scarcely gauged areas. The advantage of altimetry lies in the observation of water surface elevation, which can be proficiently used in approaches based on rating curve, empirical formulae or hydraulic modeling. Even though their use is limited, near-infrared sensors are successfully used to detect the variability of river discharge thanks to their high capacity to discriminate water from land. Thermal sensors are nearly completely unused, but the unique study that uses the difference in temperature of the river water between day and night for the estimation of water level, encourages its use for river discharge assessment as well. To improve the estimation of river discharge and foster studies that are aimed at monitoring ungauged rivers, the combination of the sensors is considered a viable path. The aim of this manuscript is to review these studies to show the limitations and the potentials of each sensor onboard the Sentinel-3 satellite and to investigate the added value of using these three sensors co-located on the same platform for river discharge monitoring.
TL;DR: In this article, an integrated drought monitoring index (IDMI) was proposed as a tool to assess and monitor the spatio-temporal dynamics of agricultural drought during the northeast monsoon season for the period from 2000 to 2016 in Tamil Nadu state, south-eastern part of Indian peninsula.
Abstract: In this study, integrated drought monitoring index (IDMI) was proposed as a tool to assess and monitor the spatio-temporal dynamics of agricultural drought during the northeast monsoon season for the period from 2000 to 2016 in Tamil Nadu state, south-eastern part of Indian peninsula. The IDMI is characterized as the principal component of precipitation condition index (PCI), soil moisture condition index (SMCI), temperature condition index (TCI), and vegetation condition index (VCI) derived from time-series satellite observations of climate hazards group infra-red precipitation with stations (CHIRPS), European space agency climate change initiative (ESA-CCI) and moderate resolution imaging spectroradiometer (MODIS). The study shows that in the year 2016, about 44.4 and 17.8% of Tamil Nadu state was under extreme and severe drought conditions, respectively. Sensitivity analysis of the study shows that PCI is the most influential parameter to IDMI, followed by VCI and TCI. The validation of IDMI with 3-month standardized precipitation index (SPI) by using Pearson correlation test shows a strong positive correlation between IDMI and 3-month SPI with correlation coefficient (r) value of 0.73 and 0.77 for the wet (2005) and dry year (2016), respectively. The study clearly demonstrates the potential of IDMI derived from time-series datasets of earth observation satellites as a tool in assessment and monitoring of spatio-temporal dynamics of agricultural drought. The proposed IDMI could be effectively used as a reliable tool to monitor agricultural drought and develop its mitigation strategies to minimise the adverse effects of drought on agriculture, water resources, and livelihoods of the people.
TL;DR: The study identified the RF, SBC and ANFIS as the top three best performing models with comparable and promising SM estimation and SBC can be recommended as the best among all for SM estimation.
Abstract: The present study provided the first-time comprehensive evaluation of 12 advanced statistical and machine learning (ML) algorithms for the Soil Moisture (SM) estimation from dual polarimetric Sentinel-1 radar backscatter. The ML algorithms namely support vector machine (SVM) with linear, polynomial, radial and sigmoid kernel, random forest (RF), multi-layer perceptron (MLP), radial basis function (RBF), Wang and Mendel’s (WM), subtractive clustering (SBC), adaptive neuro fuzzy inference system (ANFIS), hybrid fuzzy interference system (HyFIS), and dynamic evolving neural fuzzy inference system (DENFIS) were used. Extensive field samplings were performed for collection of in-situ SM data and other parameters from the selected sites for seven different dates and at two different locations (Varanasi and Guntur District, India), concurrent to Sentinel-1 overpasses. The backscattering coefficients were considered as input variables and SM as output variable for the training, validation and testing of the ML algorithms. The site at Varanasi was used for the training, validation and testing of the models. On the other hand, the Guntur site was used as an independent site for checking the model performance, before finalizing the algorithms. The performances of different trained algorithms were evaluated in terms of correlation coefficient (r), root mean square error (RMSE) (in m3/m3) and bias (in m3/m3). The study identified the RF, SBC and ANFIS as the top three best performing models with comparable and promising SM estimation. In order to test the robustness of these best models (RF, SBC and ANFIS), further performance analysis was performed to the independent datasets of the Varanasi and Guntur test sites, which indicates that the performance of these three models were consistent and SBC can be recommended as the best among all for SM estimation.
TL;DR: An adaptive neural network controller is developed by combining the trained network and a proportional-integral controller, and the long-standing challenge of model-based methods for control determination of unknown dynamics is resolved.
Abstract: In this study, an adaptive neural network control approach is proposed to achieve accurate and robust control of nonlinear systems with unknown dynamics, wherein the neural network is innovatively used to learn the inverse problem of system dynamics with guaranteed convergence. This study focuses on the following three contributions. First, the considered system is transformed into a multi-integrator system using an input–output linearization technique, and an extended state observation technique is used to identify the transformed states. Second, an iterative control learning algorithm is proposed to achieve the neural network training, and stability analysis is given to prove that the network’s predictions converge to ideal control inputs with guaranteed convergence. Third, an adaptive neural network controller is developed by combining the trained network and a proportional-integral controller, and the long-standing challenge of model-based methods for control determination of unknown dynamics is resolved. Simulation results of a virtual control mission and an aerospace altitude tracking mission are provided to substantiate the effectiveness of the proposed techniques and illustrate the adaptability and robustness of the proposed controller.
TL;DR: In this paper, active surface deformation, displacement pattern, and erosional variability are estimated using the geomorphologically sensitive morphometry along with the Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique using the Sentinel-1Adata (119 images) acquired between 07- 02-2017 and 10-02-2021.
Abstract: Active surface deformation, displacement pattern, and erosional variability is estimated using the geomorphologically sensitive morphometry along with the Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique using the Sentinel-1Adata (119 images) acquired between 07- 02-2017 and 10-02-2021. The average velocities for this dataset are estimated to be between ±11 mm/y. The Raunthi River catchment from where the flood was triggered is undergoing ~8 mm/y subsidence and ~10 mm/y uplift. Compared to this the basin wide deformation (Rishi Ganga basin) is estimated to be around ±10 mm/y with commulative ground displacement of around ±45 mm. The times series analysis suggests an increase in the ground displacement by around 5 mm/y and seems to be responsible for the expansion of pre-existing cracks in the vicinity of the Vaikrita Thrust (VT) and subsequent failure of the northern face of Nandi Peak on 7th February 2021. The Global Positioning System (GPS) derived strain distribution pattern indicate a relatively higher accumulation of strain (>0.35µ strain/y). The normalized steepness index (ksn) variation along the longitudinal section of Rishi Ganga and Raunthi River sub-basin in Central Himalayan region shows anomalous increase at the glacio-fluvial transitional processes. Moreover, the χ profiles as well as planform plots shows anomalously lower values within the Raunthi River sub-basin when compared with the Rishi Ganga basin. Based on the lower values of χ it is observed that Raunthi River sub-basin is undergoing high erosion which can be caused by the presence of sheared lithology and incision of the relict glacial and paraglacial sediments. We negate the suggestion that abrupt rise in the temperature was the major triggering mechanism for the recent disaster, instead it is the sheared lithology and pre-existing fissure developed because of differential uplift and subsidence in Raunthi River that led to the wedge failure and subsequent flash flood. Had the climate was the major driver of the recent tragedy ?, it should have impacted multiple hanging glaciers in the Rishi Ganga valley. Therefore, the study calls for detailed geomorphological, structural and glaciological investigation in regions dominated by glacial and paraglacial processes in the strategic regions of the Himalaya. Towards this, the state of art PSInSAR technique seems to provide fast and reliable detection of terrain instability/stability along with identification of potential areas of slope failures in near future in the glacial and preglacial zones.
TL;DR: In this paper, the authors used Fast Fourier Transform (FFT) spectrum analysis and Nonlinear Least Square Fitting (NLSF) to calculate the vertical height from the antenna phase center to the reflection surface.
Abstract: In recent years, with the continuous development of Global Navigation Satellite System (GNSS), it has been applied not only to navigation and positioning, but also to Earth surface environment monitoring. At present, when performing GNSS-IR (GNSS Interferometric Reflectometry) snow depth inversion, Lomb-Scargle Periodogram (LSP) spectrum analysis is mainly used to calculate the vertical height from the antenna phase center to the reflection surface. However, it has the problem of low identification of power spectrum analysis, which may lead to frequency leakage. Therefore, Fast Fourier Transform (FFT) spectrum analysis and Nonlinear Least Square Fitting (NLSF) are introduced to calculate the vertical height in this paper. The GNSS-IR snow depth inversion experiment is carried out by using the observation data of P351 station in PBO (Plate Boundary Observatory) network of the United States from 2013 to 2016. Three algorithms are used to invert the snow depth and compared with the actual snow depth provided by the station 490 in the SNOTEL network. The observations data of L1 and L2 bands are respectively used to find the optimal combination between different algorithms further to improve the accuracy of GNSS-IR snow depth inversion. For L1 band, different snow depths correspond to different optimal algorithms. When the snow depth is less than 0.8 m, the inversion accuracy of NLSF algorithm is the highest. When the snow depth is greater than 0.8 m, the inversion accuracy of FFT algorithm is higher. Therefore, according to the different snow depth, a combined algorithm of NLSF + FFT is proposed for GNSS-IR snow depth inversion. Compared with the traditional LSP algorithm, the inversion accuracy of the combined algorithm is improved by 10%. For L2 band data, the results show that the accuracy of snow depth inversion of various algorithms do not change with the variations of snow depth. Among the three single algorithms, the inversion accuracy of FFT algorithm is better than that of LSP and NLSF algorithms.
TL;DR: In this paper, real-time precise point positioning (PPP) is assessed and studied based on 8 days of PPP-B2b and GPS/GPS broadcast messages.
Abstract: China’s BeiDou Navigation Satellite System (BDS) can provide real-time precise point positioning (PPP) service for users in China and surrounding areas with PPP-B2b signal. In this paper, real-time PPP is assessed and studied based on 8 days of PPP-B2b and BDS/GPS broadcast messages. Real-time precise ephemerides are compared against Multi-GNSS Experiment (MGEX) final products and the positioning performance of real-time PPP is evaluated with MGEX/iGMAS stations. Results show that the real-time orbit accuracy is about 0.0725, 0.2479 and 0.2587 m in directions of radial (R), along (A) and cross (C) for BDS-3 satellites, and 0.0729, 0.3098 and 0.2193 m for GPS satellites. The standard deviation values of the clock offset errors are about 0.05–0.18 ns for BDS-3 satellites, and 0.05–0.15 ns for GPS satellites. In addition, the differential code bias (DCB) parameters of PPP-B2b agree well with parameters of MGEX DCB and time group delay (TGD), with the differences less than 2 and 0.15 ns, respectively. Furthermore, for the positioning experiments, the average positioning accuracies of BDS and GPS integrated real-time PPP are about 1.07, 2.69 and 2.25 cm in north (N), east (E), and up (U) directions for static mode; and about 3.6, 5.9 and 9.4 cm for kinematic mode. Moreover, the convergence times for an accuracy level of 20 cm in N, E and U components are about 8–22 min, and 10–8 min, for static mode and kinematic mode, respectively.
TL;DR: The architecture of the Global Short Message Communication system is proposed based on the medium earth orbit (MEO) constellation and the crosslinks of the global BeiDou navigation system (BDS-3) and preliminary results show that the requirements of Global Maritime Distress and Safety System (GMDSS) can be fulfilled.
Abstract: Short Message Communication (SMC) is a featured service of BeiDou Navigation Satellite System (BDS). After its successful deployment in 2003, Regional Short Message Communication (RSMC) service has been continuously serving China and its neighboring countries and regions, especially in life safety scenarios. In this paper, the architecture of the Global Short Message Communication (GSMC) system is proposed based on the medium earth orbit (MEO) constellation and the crosslinks of the global BeiDou navigation system (BDS-3). Three subtypes of GSMC service, i.e. positioning report, emergency search and rescue (SAR) and regular SMC are designed in accordance with the technical characteristic of integration of navigation and communication in BDS-3, which supports future wide applications of GSMC. The performance of the designed GSMC system is analyzed by numerical calculations. As BDS-3 was officially announced completion on July 31, 2020, GSMC has been providing initial service. First test results of the in orbit GSMC payloads are also presented in the paper to verify the designed capabilities. Preliminary results also show that the requirements of Global Maritime Distress and Safety System (GMDSS) can also be fulfilled.
TL;DR: A refined satellite non-gravitational force modeling strategy is constructed to reduce the amount of empirical parameters used to compensate for force modeling deficiencies, and suggests potential benefits to the space geodesy community that always pursues best-possible satellite orbits.
Abstract: The Astronomical Institute of the University of Bern (AIUB) has been performing GPS-based Precise Orbit Determination (POD) for a large variety of Low Earth Orbit (LEO) satellites since two decades. Traditionally, LEO orbits have been generated by a reduced-dynamic POD strategy using the Bernese GNSS Software, replacing an explicit modeling of non-gravitational forces by dedicated empirical orbit parametrizations. This LEO POD strategy can be advanced by two main developments: on the one hand, use is made of the GNSS Observation-Specific Bias (OSB) and clock products provided by the Center for Orbit Determination in Europe (CODE), allowing for the resolution of single-receiver GNSS carrier-phase ambiguities. On the other hand, the main focus of this article, a refined satellite non-gravitational force modeling strategy is constructed to reduce the amount of empirical parameters used to compensate for force modeling deficiencies. LEO POD is first performed for Sentinel-3, a satellite formation currently consists of two identical satellites −3A and −3B, which experience a similar in-flight environment and allow for direct POD performance comparisons. A third satellite Swarm-C, which flies at a lower altitude and has a more sophisticated surface geometry, is selected to validate the robustness of the new POD strategy. As a result, both the internal consistency checks and external orbit validations suggest superior orbit quality obtained for the three satellites for a time span of 1.5 years (7 June, 2018 to 31 December, 2019). The ambiguity resolution adds strong constraints to the orbits and the satellite non-gravitational force modeling leads to more tightly constrained (towards zero) pseudo-stochastic empirical parameters. The final orbit solutions agree with external orbit solutions and independent satellite laser ranging measurements at levels of sub-cm, indicating approximately 20 % improvement w.r.t. the nominal reduced-dynamic orbit solutions. This suggests potential benefits to the space geodesy community that always pursues best-possible satellite orbits.
TL;DR: In this paper, the authors extend the high precision satellite altimetry record in both time and space by including independent data from the ERS1, ERS-2, Envisat and CryoSat-2 missions (ESA data).
Abstract: More than 27 years of high precision satellite altimetry enables analysis of recent changes in global mean sea level (GMSL). Several previous studies present estimates of the trend and acceleration in GMSL; however, all are exclusively performed with data from the TOPEX/Poseidon, Jason-1, Jason-2 and Jason-3 missions (TPJ data). In this study we extend the altimetry record in both time and space by including independent data from the ERS-1, ERS-2, Envisat and CryoSat-2 missions (ESA data). This increases the time-series to span more than 27 years (1991.7–2019.0) and the spatial coverage is extended from ± 66° to ± 82° latitude. Another advantage of the ESA data is that it is independent of the issues associated with the TOPEX altimeter which introduce a significant uncertainty to the first part of the record. GMSL based on ESA data on the 1991–2019 period within ± 82° latitude exhibit an acceleration of 0.095 ± 0.009 mm/yr2. The corresponding value for the TPJ data is 0.080 ± 0.008 mm/yr2 for the 1993–2019 period and within ± 66° latitude. The ERS-1 satellite was launched shortly after the large Pinatubo eruption in 1991. The satellite observes a decrease of 6 mm in GMSL during the first 1.7 years until the launch of TOPEX/Poseidon. The distribution of sea level acceleration across the global ocean is highly similar between the ESA and TPJ dataset. In the Pacific Ocean regional sea level acceleration patterns seem related to the El-Nino Southern Oscillation (ENSO) whereas around Greenland a clear negative acceleration is seen.
TL;DR: The recently discovered first hyperbolic objects passing through the Solar System, 1I/Oumuamua and 2I/Borisov, have raised the question about near term missions to Interstellar Objects.
Abstract: The recently discovered first hyperbolic objects passing through the Solar System, 1I/’Oumuamua and 2I/Borisov, have raised the question about near term missions to Interstellar Objects In situ spacecraft exploration of these objects will allow the direct determination of both their structure and their chemical and isotopic composition, enabling an entirely new way of studying small bodies from outside our solar system In this paper, we map various Interstellar Object classes to mission types, demonstrating that missions to a range of Interstellar Object classes are feasible, using existing or near-term technology We describe flyby, rendezvous and sample return missions to interstellar objects, showing various ways to explore these bodies characterizing their surface, dynamics, structure and composition Their direct exploration will constrain their formation and history, situating them within the dynamical and chemical evolution of the Galaxy These mission types also provide the opportunity to explore solar system bodies and perform measurements in the far outer solar system
TL;DR: In this paper, Sea Level Anomaly (SLA) data from satellite altimetry is utilized to investigate the role of eddies on tropical cyclones intensification in the North Indian Ocean (NIO) basin.
Abstract: Eddies are known to play a crucial role in the sudden intensification of tropical cyclones. In this study, Sea Level Anomaly (SLA) data from satellite altimetry is utilized to investigate the role of eddies on tropical cyclones intensification in the North Indian Ocean (NIO) basin. SLA data obtained from Archiving Validation and Interpretation of Satellite Data in Oceanography (AVISO), Tropical Cyclone Heat Potential (TCHP) from National Remote Sensing Centre (NRSC) and cyclone intensity data from Indian Meteorological Department (IMD) have been utilized to analyse and understand the impact of TCHP and eddies on 60 tropical cyclones in the NIO spanning the years 2001–2018. Out of these 60 cyclones, 38 were formed in the Bay of Bengal (BoB) and 22 in the Arabian Sea (AS). From the analysis, it is found that nearly 40% cyclones are affected by Warm Core Eddy (WCE) generally intensifying them, 30% are influenced by Cold Core Eddy (CCE) that generally reduce cyclone intensities and the rest 30% are affected by TCHP variations (in the absence of eddies) in the NIO region during the study period. Cyclones which do not follow the established trend of intensifying due to WCEs or increasing TCHP; and diminishing owing to CCEs or TCHP decrease were found to be governed primarily by the Translational Speed of the cyclones. WCE are mostly present during the pre-monsoon season in the NIO (both BoB and AS). This analysis confirms that consideration of the underlying eddies in the cyclone track represented by SLA, TCHP variations, Translational Speed of cyclones and the ocean barrier layer are key factors that must be considered in forecasting cyclone intensity and track.
TL;DR: In this paper, a total of 25 morphometric parameters were computed and several statistical analyses performed in establishing inter-correlation and classification of Indian rivers in Peninsular India were found 7th to 9th order catchments.
Abstract: In terms of hydro-geomorphic characteristics, catchments in Peninsular India remained mostly unexplored except a few regional and local works that deal with tectonic, structural and paleo-climatic control on geomorphology. Catchment scale morphometric analyses deliver insights into dynamics, erosion capacity, probability of flood occurrence, lithological and structural control, and genetic response to the tectonics. The present study aimed to comprehend hydro-geomorphic characteristics of 12 major catchments in Peninsular India through GIS-based morphometric analysis. A total of 25 morphometric parameters were computed and several statistical analyses performed in establishing inter-correlation and classification of Indian rivers. Most of the rivers in Peninsular India were found 7th to 9th order catchments. Almost all basins showed a moderate relief ratio, hypsometric integral, ruggedness etc. Cauvery, Baitarni, and Brahmani showed exceptionally steeper gradient, high relief ratio, LS factor, and ruggedness index, which indicated higher erosion potential. Correlation among landscape variables revealed moderate scale dependency of few relief factors. Baitarni, Brahmani and Narmada showed higher hypsometric integral. A strong positive association between hypsometric integral and sediment yield suggested critically high erosion potential in catchments with high integral values. The present study provides some generic insights into the hydro-geomorphic characteristics with dissimilarity in lithology in Peninsular Indian catchments as a whole.