bluuebunny/crossref_metadata_2025 huggingface dataset:
Ousting the Cypriot Ethnarch: President Makarios’ Struggle against the Greek Junta, Cypriot Bishops, and Terrorism
Authors: Kıralp Şevki , Güneyli Ahmet
Published: November 2021

This study examined the politics and political involvements of the Orthodox Church of Cyprus in the early postcolonial era, with a special focus on the ecclesiastical coup that aimed for the ouster of Archbishop Makarios III, who was also the President of the Republic of Cyprus from 1960 to 1977. The findings indicate that the Greek junta, Greek Cypriot terrorists, and the three bishops of the Orthodox Church of Cyprus joined forces to oust Makarios by forcing him to resign his presidency. These actors were displeased with Makarios because he tolerated Cypriot communism, refused to follow Athens’ manipulations in Cypriot politics, and promoted Cyprus’ independence by abandoning the pro-Enosis (unification of Cyprus with Greece) political line. The Greek junta tried to dictate policies to Makarios and asked him to resign as he refused to obey. Greek Cypriot terrorists engaged in violence to destabilize the island and oust Makarios. The three bishops summoned the Holy Synod and defrocked the Archbishop as he refused to resign his presidency. Importantly, this research came across with strong indicators that the Greek junta tried to utilize religion in trying to oust the Cypriot ethnarch as the three bishops, immediately after the junta’s failure to oust Makarios in 1972, asked him to resign his presidency. While his rivals failed to oust Makarios, at least until 1974, he called for an international synod and defrocked the three bishops. He managed to retain both posts until the end of his life.
The Concept of Grammatical Organon in the Star of Redemption by Rosenzweig
Authors: Dvorkin Ilya
Published: November 2021

In his book The Star of Redemption, F. Rosenzweig formulated a new philosophical system, which is based not on thinking, or being, but on language. At the same time, Rosenzweig not only postulates language but deduces it as a procedural reality that is currently unfolding in relation to perfect and closed elements—the world, God and man. Language fundamentally changes our attitude not only toward the world, God and man but in general toward all objects of knowledge and action. The world ceases to be perceived as an equal given, a person ceases to be a generic definition for subjectivity and acquires singularity and uniqueness. God is not defined as the Absolute Reality but becomes a live interlocutor. One of the central points of Rosenzweig’s system is its grammatical organon—a method that allows one to consider linguistic processes. Rosenzweig unfolds his organon in three books of the second part of The Star of Redemption. This article discusses the philosophical foundations of Rosenzweig’s grammatical organon and the features of its application to various linguistic and speech phenomena.
Sacral Architecture in Poland after 1945 with Particular Reference to the Archdiocese of Częstochowa
Authors: Repelewicz Aleksandra
Published: November 2021

The study attempts to analyze the post-war sacral architecture in Poland based on the example of churches built after 1945 in the area of the present archdiocese of Częstochowa. It presents the history of sacral architecture, with particular emphasis on the years 1945–1989. It further discusses issues concerning the style of churches and problems related to structures with very large areas and cubature. Problems related to churches erected as “catechetical centers” and smaller filial churches are also mentioned. The presented issues concerning the chosen archdiocese may constitute a representative example of sacral architecture in Poland.
Global Shinqīṭ: Mauritania’s Islamic Knowledge Tradition and the Making of Transnational Religious Authority (Nineteenth to Twenty-First Century)
Authors: Salem Zekeria Ahmed
Published: November 2021

Today, Bilād-Shinqīṭ or Mauritania is often portrayed as an unparalleled center of classical Islamic tradition supposedly untouched by modernity. While previous scholarship has concerned itself mostly with Mauritania’s local intellectual history on one hand and its recent global fame on the other, in this paper, I document instead how, in less than two centuries, Mauritania has become not only a point of scholarly reference and symbolic/representational space of excellence in Islamic knowledge, but also one with an astonishing amount of global reach. Thus, I explore the ways in which Mauritania has continued to asserts its relevance and scholarly authority on a global scale. Drawing on a variety of historical, literary, and anthropological sources, I historicize the rise and mythologization of Mauritania as a peerless center of traditional sacred scholarship. I specifically examine how a number of widely different Muslim actors under changing circumstances continue to invoke, perform and re-invent Shinqīṭ/Mauritania. In documenting what I call Global Shinqīt over the longue durée, rather than simply illustrate how the so-called Muslim peripheries shape central traits of transnational normative Islamic authority, I argue instead that mobility, historical circumstances, and scholarly performance combined are at least as instrumental in the credible articulation of authoritative Islamic knowledge as normative discourses issued by supposedly central institutions, personalities, and religious bodies located in the so-called “heartland of Islam.” In so doing, I destabilize the center/periphery framework altogether in order to explore how Islamic religious authority is actually construed and operates under shifting cultural and political conditions.
How to Identify Potentials and Barriers of Raw Materials Recovery from Tailings? Part II: A Practical UNFC-Compliant Approach to Assess Project Sustainability with On-Site Exploration Data
Authors: Suppes Rudolf , Heuss-Aßbichler Soraya
Published: November 2021

A sustainable raw materials (RMs) recovery from waste requires a comprehensive generation and communication of knowledge on project potentials and barriers. However, a standardised procedure to capture sustainability aspects in early project development phases is currently missing. Thus, studies on different RM sources are not directly comparable. In this article, an approach is presented which guides its user through a practical interpretation of on-site exploration data on tailings compliant with the United Nations Framework Classification for Resources (UNFC). The development status of the overall project and the recovery of individual RMs are differentiated. To make the assessment results quickly comparable across different studies, they are summarised in a heat-map-like categorisation matrix. In Part I of this study, it is demonstrated with the case study tailings storage facility Bollrich (Germany) how a tailings mining project can be assessed by means of remote screening. In Part II, it is shown how to develop a project from first on-site exploration to a decision whether to intensify costly on-site exploration. It is concluded that with a UNFC-compliant assessment and classification approach, local sustainability aspects can be identified, and a commonly acceptable solution for different stakeholder perspectives can be derived.
Accurate Refraction Correction—Assisted Bathymetric Inversion Using ICESat-2 and Multispectral Data
Authors: Liu Changda , Qi Jiawei , Li Jie , Tang Qiuhua , Xu Wenxue , Zhou Xinghua , Meng Wenjun
Published: November 2021

Shallow-water depth information is essential for ship navigation and fishery farming. However, the accurate acquisition of shallow-water depth has been a challenge for marine mapping. Combining Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) bathymetry data with multispectral data, satellite-derived bathymetry is a promising solution through which to obtain bathymetric information quickly and accurately. This study proposes a photon refraction correction method considering sea-surface undulations to address errors in the underwater photons obtained by the ICESat-2. First, the instantaneous sea surface and beam emission angle are integrated to determine the sea-surface incidence angle. Next, the distance of photon propagation in water is determined using sea-surface undulation and Snell’s law. Finally, position correction is performed through geometric relationships. The corrected photons were combined with the multispectral data for bathymetric inversion, and a bathymetric map of the Yongle Atoll area was obtained. A bathymetric chart was created using the corrected photons and the multispectral data in the Yongle Atoll. Comparing the results of different refraction correction methods with the data measured shows that the refraction correction method proposed in this paper can effectively correct bathymetry errors: the root mean square error is 1.48 m and the R2 is 0.86.
A ROTI-Aided Equatorial Plasma Bubbles Detection Method
Authors: Tang Long , Louis Osei-Poku , Chen Wu , Chen Mingli
Published: November 2021

In this study, we present a Rate of Total Electron Content Index (ROTI)-aided equatorial plasma bubbles (EPBs) detection method based on a Global Navigation Satellite System (GNSS) ionospheric Total Electron Content (TEC). This technique seeks the EPBs occurrence time according to the ROTI values and then extracts the detrended ionospheric TEC series, which include EPBs signals using a low-order, partial polynomial fitting strategy. The EPBs over the Hong Kong area during the year of 2014 were detected using this technique. The results show that the temporal distribution and occurrence of EPBs over the Hong Kong area are consistent with that of previous reports, and most of the TEC depletion error is smaller than 1.5 TECU (average is 0.63 TECU), suggesting that the detection method is feasible and highly accurate. Furthermore, this technique can extract the TEC depletion series more effectively, especially for those with a long duration, compared to previous method.
Application of the Comparison of Multibeam Echo-Sound Records to the Study of Stability of a Toxic Waste Stockpile Located on the Margin of a Tidal System: Tinto Estuary, Huelva, SW Spain
Authors: Carro Berta M. , Reyes Alejandro , Morales Juan A. , Borrego José
Published: November 2021

For more than 40 years, the industrial complex which developed near Huelva (in SW Spain) produced a huge amount of phosphogypsum as a waste product of manufacturing fertilizers. This waste was stockpiled in a stack 25 m high, covering 1200 ha of what was once a salt marsh. The weight of that enormous amount of waste produced active subsidence in the underlying sediment. Part of the sediment was injected into the marginal areas, where the load pressure is minor, causing significant vertical movement in the floor of the estuarine channel. This manuscript describes several surficial features using multibeam echosound. A crest formed by cones and a bulge area could be interpreted as injection structures. The evolution of the topographic position of the floor was also analyzed by comparing different records of the estuarine bed in the margins of the stockpile. The data in this work document the changes in the dynamics of the estuary in relation to these vertical movements. These changes in dynamicsled to erosion and deposition in various areas of the bed.
Accuracy Verification and Correction of D-InSAR and SBAS-InSAR in Monitoring Mining Surface Subsidence
Authors: Chen Yang , Yu Shengwen , Tao Qiuxiang , Liu Guolin , Wang Luyao , Wang Fengyun
Published: November 2021

The accuracy of InSAR in monitoring mining surface subsidence is always a matter of concern for surveyors. Taking a mining area in Shandong Province, China, as the study area, D-InSAR and SBAS-InSAR were used to obtain the cumulative subsidence of a mining area over a multi-period, which was compared with the mining progress of working faces. Then dividing the mining area into regions with different magnitudes of subsidence according to the actual mining situation, the D-InSAR-, SBAS-InSAR- and leveling-monitored results of different subsidence magnitudes were compared and the Pearson correlation coefficients between them were calculated. The results show that InSAR can accurately detect the location, range, spatial change trend, and basin edge information of the mining subsidence. However, InSAR has insufficient capability to detect the subsidence center, having high displacement rates, and its monitored results are quite different from those of leveling. To solve this problem, the distance from each leveling point to the subsidence center was calculated according to the layout of the rock movement observation line. Besides, the InSAR-monitored error at each leveling point was also calculated. Then, according to the internal relationship between these distances and corresponding InSAR-monitored errors, a correction model of InSAR-monitored results was established. Using this relationship to correct the InSAR-monitored results, results consistent with the actual situation were obtained. This method effectively makes up for the deficiency of InSAR in monitoring the subsidence center of a mining area.
A Consumer Grade UAV-Based Framework to Estimate Structural Attributes of Coppice and High Oak Forest Stands in Semi-Arid Regions
Authors: Fakhri Arvin , Latifi Hooman
Published: November 2021

Semi-arid tree covers, in both high and coppice growth forms, play an essential role in protecting water and soil resources and provides multiple ecosystem services across fragile ecosystems. Thus, they require continuous inventories. Quantification of forest structure in these tree covers provides important measures for their management and biodiversity conservation. We present a framework, based on consumer-grade UAV photogrammetry, to separately estimate primary variables of tree height (H) and crown area (A) across diverse coppice and high stands dominated by Quercus brantii Lindl. along the latitudinal gradient of Zagros mountains of western Iran. Then, multivariate linear regressions were parametrized with H and A to estimate the diameter at breast height (DBH) of high trees because of its importance to accelerate the existing practical DBH inventories across Zagros Forests. The estimated variables were finally applied to a model tree aboveground biomass (AGB) for both vegetative growth forms by local allometric equations and Random Forest models. In each step, the estimated variables were evaluated against the field reference values, indicating practically high accuracies reaching root mean square error (RMSE) of 0.68 m and 4.74 cm for H and DBH, as well as relative RMSE < 10% for AGB estimates. The results generally suggest an effective framework for single tree-based attribute estimation over mountainous, semi-arid coppice, and high stands.
Emulation of Sun-Induced Fluorescence from Radiance Data Recorded by the HyPlant Airborne Imaging Spectrometer
Authors: Morata Miguel , Siegmann Bastian , Morcillo-Pallarés Pablo , Rivera-Caicedo Juan Pablo , Verrelst Jochem
Published: November 2021

The retrieval of sun-induced fluorescence (SIF) from hyperspectral radiance data grew to maturity with research activities around the FLuorescence EXplorer satellite mission FLEX, yet full-spectrum estimation methods such as the spectral fitting method (SFM) are computationally expensive. To bypass this computational load, this work aims to approximate the SFM-based SIF retrieval by means of statistical learning, i.e., emulation. While emulators emerged as fast surrogate models of simulators, the accuracy-speedup trade-offs are still to be analyzed when the emulation concept is applied to experimental data. We evaluated the possibility of approximating the SFM-like SIF output directly based on radiance data while minimizing the loss in precision as opposed to SFM-based SIF. To do so, we implemented a double principal component analysis (PCA) dimensionality reduction, i.e., in both input and output, to achieve emulation of multispectral SIF output based on hyperspectral radiance data. We then evaluated systematically: (1) multiple machine learning regression algorithms, (2) number of principal components, (3) number of training samples, and (4) quality of training samples. The best performing SIF emulator was then applied to a HyPlant flight line containing at sensor radiance information, and the results were compared to the SFM SIF map of the same flight line. The emulated SIF map was quasi-instantaneously generated, and a good agreement against the reference SFM map was obtained with a R2 of 0.88 and NRMSE of 3.77%. The SIF emulator was subsequently applied to 7 HyPlant flight lines to evaluate its robustness and portability, leading to a R2 between 0.68 and 0.95, and a NRMSE between 6.42% and 4.13%. Emulated SIF maps proved to be consistent while processing time was in the order of 3 min. In comparison, the original SFM needed approximately 78 min to complete the SIF processing. Our results suggest that emulation can be used to efficiently reduce computational loads of SIF retrieval methods.
Relationships between the Spatio-Temporal Variation in Reflectance Data from the Sentinel-2 Satellite and Potato (Solanum Tuberosum L.) Yield and Stem Density
Authors: Mhango Joseph K. , Harris W. Edwin , Monaghan James M.
Published: November 2021

Satellite Image Time Series (SITS) have been used to build models for predicting Potato (Solanum tuberosum L.) yields at regional scales, but evidence of extension of such models to local field scale for practical use in precision agriculture is lacking. In this study, multispectral data from the Sentinel-2 satellite were used to interpolate continuous spectral signatures of potato canopies and generate vegetation indices and the red edge inflection point (REIP) to relate to marketable yield and stem density. The SITS data were collected from 94 sampling locations across five potato fields in England, United Kingdom. The sampling locations were georeferenced and the number of stems per square meter, as well as marketable yield, were determined at harvest. The first principal components of the temporal variation of each SITS wavelength were extracted and used to generate 54 vegetation indices to relate to the response variables. Marketable yield was negatively related to the overall seasonal reflectance (first principal component) at 559 nm with a beta coefficient of −0.53 (±0.18 at p = 0.05). Seasonal reflectance at 703 nm had a positive significant relationship with Marketable yield. Marketable yield was modeled with a normalized root mean square error (nRMSE) of 0.16 and R2 of 0.65. On the other hand, Stem density was significantly related to the Specific Leaf Area Vegetation Index (β = 1.66 ± 1.59) but the REIP’s farthest position during the season was reached later in dense canopies (β = 1.18 ± 0.79) with a higher reflectance (β = 3.43 ± 1.9). This suggested that denser canopies took longer to reach their maximum chlorophyll intensity and the intensity was lower than in sparse canopies. Potato stem density was modeled with an nRMSE of 0.24 and R2 of 0.51. These results reinforce the importance of SITS analysis as opposed to the use of single-instance intrinsic indices.
Ground Moving Target Imaging for Highly Squint SAR by Modified Minimum Entropy Algorithm and Spectrum Rotation
Authors: Xiong Shichao , Ni Jiacheng , Zhang Qun , Luo Ying , Yu Longqiang
Published: November 2021

Ground moving target (GMT) is displaced and defocused in conventional synthetic aperture radar (SAR) image due to the residual phase error of non-cooperative GMT motion. In this study, a GMT imaging (GMTIm) method is proposed for highly squint SAR. As the squint angle become large, the displace and defocus effect of the GMT image become severe and the geometry distortion of the GMT image cannot be ignored. The proposed method first deduced the two-dimensional (2-D) frequency domain signal of the GMT and the bulk compression function of the Range Migration Algorithm (RMA) in highly squint SAR. Then GMT ROI data are extracted and a modified minimum entropy algorithm (MMEA) is proposed to refocus the GMT image. MMEA introduces the idea of bisection into the iteration process to converge more efficiently than the previous minimum entropy method. To overcome the geometry distortion of the GMT image, an equivalent squint angle spectrum rotation method is proposed. Finally, to suppress the GMT image sidelobe, the sparse characteristic of GMT is considered and a sparse enhancement method is adopted. The proposed method can realize GMTIm in highly squint SAR where the squint angle reaches to 75 degrees. The PSNR and ISLR of point target in highly squint SAR is close to that in side-looking SAR. The simulated point target data and ship data are used to validate the effectiveness of the proposed method.
Joint Radar-Communications Exploiting Optimized OFDM Waveforms
Authors: Ahmed Ammar , Zhang Yimin D. , Hassanien Aboulnasr
Published: November 2021

We propose novel Joint Radar-communication spectrum sharing strategies exploiting orthogonal frequency-division multiplexing (OFDM) waveforms that concurrently achieve the objectives of both radar and communication systems. An OFDM transmitter is considered that transmits dual-purpose OFDM subcarriers such that all the subcarriers are exploited for the primary radar function and further exclusively allocated to the secondary communication function serving multiple users. The waveform optimization is performed by employing mutual information (MI) as the optimization criterion for both radar and communication operations. For the purpose of radar performance optimization, we consider the MI between the frequency-dependent target response and the transmit OFDM waveforms. On the other hand, communication system performance is evaluated in terms of the MI between the frequency-dependent communication channels of communication users with the transmit OFDM subcarriers. These optimization objectives not only enable the transmit power allocation of the OFDM subcarriers, but also govern the subcarrier distribution among the communication users. Two resource optimization scenarios are considered, resulting in radar-centric and cooperative resource allocation strategies that exploit convex and mixed-integer linear programming optimization problems for power allocation and subcarrier distribution, respectively. We further present a chunk subcarrier allocation approach that applies to both optimization strategies to reduce the computational complexity with a trivial performance loss. Simulation results are presented to illustrate the effectiveness of the proposed strategies.
Rotation-Invariant and Relation-Aware Cross-Domain Adaptation Object Detection Network for Optical Remote Sensing Images
Authors: Chen Ying , Liu Qi , Wang Teng , Wang Bin , Meng Xiaoliang
Published: November 2021

In recent years, object detection has shown excellent results on a large number of annotated data, but when there is a discrepancy between the annotated data and the real test data, the performance of the trained object detection model is often degraded when it is directly transferred to the real test dataset. Compared with natural images, remote sensing images have great differences in appearance and quality. Traditional methods need to re-label all image data before interpretation, which will consume a lot of manpower and time. Therefore, it is of practical significance to study the Cross-Domain Adaptation Object Detection (CDAOD) of remote sensing images. To solve the above problems, our paper proposes a Rotation-Invariant and Relation-Aware (RIRA) CDAOD network. We trained the network at the image-level and the prototype-level based on a relation aware graph to align the feature distribution and added the rotation-invariant regularizer to deal with the rotation diversity. The Faster R-CNN network was adopted as the backbone framework of the network. We conducted experiments on two typical remote sensing building detection datasets, and set three domain adaptation scenarios: WHU 2012 → WHU 2016, Inria (Chicago) → Inria (Austin), and WHU 2012 → Inria (Austin). The results show that our method can effectively improve the detection effect in the target domain, and outperform competing methods by obtaining optimal results in all three scenarios.
Boost Precision Agriculture with Unmanned Aerial Vehicle Remote Sensing and Edge Intelligence: A Survey
Authors: Liu Jia , Xiang Jianjian , Jin Yongjun , Liu Renhua , Yan Jining , Wang Lizhe
Published: November 2021

In recent years unmanned aerial vehicles (UAVs) have emerged as a popular and cost-effective technology to capture high spatial and temporal resolution remote sensing (RS) images for a wide range of precision agriculture applications, which can help reduce costs and environmental impacts by providing detailed agricultural information to optimize field practices. Furthermore, deep learning (DL) has been successfully applied in agricultural applications such as weed detection, crop pest and disease detection, etc. as an intelligent tool. However, most DL-based methods place high computation, memory and network demands on resources. Cloud computing can increase processing efficiency with high scalability and low cost, but results in high latency and great pressure on the network bandwidth. The emerging of edge intelligence, although still in the early stages, provides a promising solution for artificial intelligence (AI) applications on intelligent edge devices at the edge of the network close to data sources. These devices are with built-in processors enabling onboard analytics or AI (e.g., UAVs and Internet of Things gateways). Therefore, in this paper, a comprehensive survey on the latest developments of precision agriculture with UAV RS and edge intelligence is conducted for the first time. The major insights observed are as follows: (a) in terms of UAV systems, small or light, fixed-wing or industrial rotor-wing UAVs are widely used in precision agriculture; (b) sensors on UAVs can provide multi-source datasets, and there are only a few public UAV dataset for intelligent precision agriculture, mainly from RGB sensors and a few from multispectral and hyperspectral sensors; (c) DL-based UAV RS methods can be categorized into classification, object detection and segmentation tasks, and convolutional neural network and recurrent neural network are the mostly common used network architectures; (d) cloud computing is a common solution to UAV RS data processing, while edge computing brings the computing close to data sources; (e) edge intelligence is the convergence of artificial intelligence and edge computing, in which model compression especially parameter pruning and quantization is the most important and widely used technique at present, and typical edge resources include central processing units, graphics processing units and field programmable gate arrays.
Evaluation of Satellite-Derived Products for the Daily Average and Extreme Rainfall in the Mearim River Drainage Basin (Maranhão, Brazil)
Authors: Xavier Ana Carolina Freitas , Rudke Anderson Paulo , Serrão Edivaldo Afonso de Oliveira , Terassi Paulo Miguel de Bodas , Pontes Paulo Rógenes Monteiro
Published: November 2021

Satellite precipitation estimates are used as an alternative or as a supplement to the records of the in situ stations. Although some satellite precipitation products have reasonably consistent time series, they are often limited to specific geographic areas. The main objective of this study was to evaluate CHIRPS version 2, MSWEP version 2, and PERSIANN-CDR, compared to gridBR, as daily mean and extreme inputs represented on a monthly scale and their respective seasonal trends of rainfall in the Mearim River Drainage Basin (MDB), Maranhão state, Brazil. Estimates of errors were calculated (relative error, pbias; root mean square error, RMSE, and Willmott concordance index, d), and the chances of precipitation were estimated by remote sensing (RES). In addition, trends in precipitation were estimated by the two-sample Mann–Kendall test. Given the overall performance, the best products for estimating monthly mean daily rainfall in the MDB are CHIRPS and PERSIANN-CDR, especially for rainy months (December to May). For daily extremes on the monthly scale, the best RES is PERSIANN-CDR. There is no general agreement between gridBR and RES methods for the trend signal, even a nonsignificant one, much less a significant one. The use of MSWEP for the MDB region is discouraged by this study because it overestimates monthly averages and extremes. Finally, studies of this kind in drainage basins are essential to improve the information generated for managing territories and developing regionalized climate and hydrological models.
Mapping the Impact of COVID-19 Lockdown on Urban Surface Ecological Status (USES): A Case Study of Kolkata Metropolitan Area (KMA), India
Authors: Das Manob , Das Arijit , Pereira Paulo , Mandal Asish
Published: November 2021

An urban ecosystem’s ecological structure and functions can be assessed through Urban Surface Ecological Status (USES). USES are affected by human activities and environmental processes. The mapping of USESs are crucial for urban environmental sustainability, particularly in developing countries such as India. The COVID-19 pandemic caused unprecedented negative impacts on socio-economic domains; however, there was a reduction in human pressures on the environment. This study aims to assess the effects of lockdown on the USES in the Kolkata Metropolitan Area (KMA), India, during different lockdown phases (phases I, II and III). The land surface temperature (LST), normalized difference vegetation index (NDVI), and wetness and normalized difference soil index (NDSI) were assessed. The USES was developed by combining all of the biophysical parameters using Principal Component Analysis (PCA). The results showed that there was a substantial USES spatial variability in KMA. During lockdown phase III, the USES in fair and poor sustainability areas decreased from 29% (2019) to 24% (2020), and from 33% (2019) to 25% (2020), respectively. Overall, the areas under poor USES decreased from 30% to 25% during lockdown periods. Our results also showed that the USES mean value was 0.49 in 2019but reached 0.34 during the lockdown period (a decrease of more than 30%). The poor USES area was mainly concentrated in built-up areas (with high LST and NDSI), compared to the rural fringe areas of KMA (high NDVI and wetness). The mapping of USES are crucial in different biophysical environmental conditions, and they can be very helpful for the assessment of urban sustainability.
Retrieval of Water Cloud Optical and Microphysical Properties from Combined Multiwavelength Lidar and Radar Data
Authors: Zhang Yinchao , Chen Su , Tan Wangshu , Chen Siying , Chen He , Guo Pan , Sun Zhuoran , Hu Rui , Xu Qingyue , Zhang Mengwei , Hao Wei , Bu Zhichao
Published: November 2021

The remote sensing of water clouds is useful for studying their spatial and temporal variations and constraining physical processes in climate and weather prediction models. However, radar-only detection provides inadequate information for the cloud droplet size distribution. Here, we propose a novel lookup-table method, which combines lidar (1064, 532 nm) and radar (8.6 mm) to retrieve profiles of cloud optical (backscatter coefficient and extinction coefficient) and microphysical properties (effective diameter and liquid water content). Through the iteration of the extinction-to-backscatter ratio, more continuous cloud optical characteristics can be obtained. Sensitivity analysis shows that a 10% error of the lidar constant will lead to a retrieval error of up to 30%. The algorithm performed precise capture of the ideal cloud signal at a specific height and at full height and the maximum relative error of the backscatter coefficients at 1064 nm and 532 nm were 6% and 4%, respectively. With the application of the algorithm in the two observation cases on single or multiple cloud layers, the results indicate that the microphysical properties mostly agree with the empirical radar measurements but are slightly different when larger particles cause signal changes of different extents. Consequently, the synergetic algorithm is capable of computing the cloud droplet size distribution. It provides continuous profiles of cloud optical properties and captures cloud microphysical properties well for water cloud studies.
Remote Sensing of the Polar Ice Zones with HF Radar
Authors: Anderson Stuart
Published: November 2021

Radars operating in the HF band are widely used for over-the-horizon remote sensing of ocean surface conditions, ionospheric studies and the monitoring of ship and aircraft traffic. Several hundreds of such radars are in operation, yet only a handful of experiments have been conducted to assess the prospect of utilizing this technology for the remote sensing of sea ice. Even then, the measurements carried out have addressed only the most basic questions: is there ice present, and can we measure its drift? Recently the theory that describes HF scattering from the dynamic sea surface was extended to handle situations where an ice cover is present. With this new tool, it becomes feasible to interpret the corresponding radar echoes in terms of the structural, mechanical, and electrical properties of the ice field. In this paper we look briefly at ice sensing from space-borne sensors before showing how the persistent and synoptic wide area surveillance capabilities of HF radar offer an alternative. The dispersion relations of different forms of sea ice are examined and used in a modified implementation of the electromagnetic scattering theory employed in HF radar oceanography to compute the corresponding radar signatures. Previous and present-day HF radar deployments at high latitudes are reviewed, noting the physical and technical challenges that confront the implementation of an operational HF radar in its ice monitoring capability.
Mapping a Paddy Rice Area in a Cloudy and Rainy Region Using Spatiotemporal Data Fusion and a Phenology-Based Algorithm
Authors: Zhao Rongkun , Li Yuechen , Chen Jin , Ma Mingguo , Fan Lei , Lu Wei
Published: November 2021

The timely and accurate mapping of paddy rice is important to ensure food security and to protect the environment for sustainable development. Existing paddy rice mapping methods are often remote sensing technologies based on optical images. However, the availability of high-quality remotely sensed paddy rice growing area data is limited due to frequent cloud cover and rain over the southwest China. In order to overcome these limitations, we propose a paddy rice field mapping method by combining a spatiotemporal fusion algorithm and a phenology-based algorithm. First, a modified neighborhood similar pixel interpolator (MNSPI) time series approach was used to remove clouds on Sentinel-2 and Landsat 8 OLI images in 2020. A flexible spatiotemporal data fusion (FSDAF) model was used to fuse Sentinel-2 data and MODIS data to obtain multi-temporal Sentinel-2 images. Then, the fused remote sensing data were used to construct fusion time series data to produce time series vegetation indices (NDVI\LSWI) having a high spatiotemporal resolution (10 m and ≤16 days). On this basis, the unique physical characteristics of paddy rice during the transplanting period and other auxiliary data were combined to map paddy rice in Yongchuan District, Chongqing, China. Our results were validated by field survey data and showed a high accuracy of the proposed method indicated by an overall accuracy of 93% and the Kappa coefficient of 0.85. The paddy rice planting area map was also consistent with the official data of the third national land survey; at the town level, the correlation between official survey data and paddy rice area was 92.5%. The results show that this method can effectively map paddy rice fields in a cloudy and rainy area.
Evaluation of Muscle Function by Means of a Muscle-Specific and a Global Index
Authors: Rosati Samanta , Ghislieri Marco , Dotti Gregorio , Fortunato Daniele , Agostini Valentina , Knaflitz Marco , Balestra Gabriella
Published: November 2021

Gait analysis applications in clinics are still uncommon, for three main reasons: (1) the considerable time needed to prepare the subject for the examination; (2) the lack of user-independent tools; (3) the large variability of muscle activation patterns observed in healthy and pathological subjects. Numerical indices quantifying the muscle coordination of a subject could enable clinicians to identify patterns that deviate from those of a reference population and to follow the progress of the subject after surgery or completing a rehabilitation program. In this work, we present two user-independent indices. First, a muscle-specific index (MFI) that quantifies the similarity of the activation pattern of a muscle of a specific subject with that of a reference population. Second, a global index (GFI) that provides a score of the overall activation of a muscle set. These two indices were tested on two groups of healthy and pathological children with encouraging results. Hence, the two indices will allow clinicians to assess the muscle activation, identifying muscles showing an abnormal activation pattern, and associate a functional score to every single muscle as well as to the entire muscle set. These opportunities could contribute to facilitating the diffusion of surface EMG analysis in clinics.
LECAR: Location Estimation-Based Congestion-Aware Routing Protocol for Sparsely Deployed Energy-Efficient UAVs
Authors: Mahmud Imtiaz , Cho You-Ze
Published: November 2021

Energy-efficient routing has become a critical issue for advanced energy-hungry unmanned aerial vehicles (UAVs). Routing in a flying ad hoc network is always challenging and becomes even more critical when a small number of UAVs must cover a large area. The routing protocols based on the delay-tolerant network (DTN) are best suited for such scenarios. However, traditional DTN-based routing protocols depend on data dissemination to offer a better packet delivery ratio, leading to congestion and excess transmissions, causing heavy and unnecessary energy consumption. We propose a location estimation-based congestion-aware routing protocol (LECAR) to balance these two issues. Considering outdated location information, LECAR takes advantage of the mobility model to estimate the current location of the destination. In addition, LECAR routes a packet by considering both the distance to destination and buffer occupancy of the neighboring UAVs. Simulation results show that LECAR could ensure both a high packet delivery ratio and low energy consumption. Moreover, LECAR could provide a minimal number of transmissions, while minimizing the number of copies per packet at a time.
Theoretical, Numerical, and Experimental Study on the Identification of Subway Tunnel Structural Damage Based on the Moving Train Dynamic Response
Authors: Li Hongqiao , Xie Xiongyao , Zhang Yonglai , Wang Qiang
Published: November 2021

As an important part of urban rail transit, subway tunnels play an important role in alleviating traffic pressure in mega-cities. Identifying and locating damage to the tunnel structure as early as possible has important practical significance for maintaining the long-term safe operation of subway tunnels. Summarizing the current status and shortcomings of the structural health monitoring of subway tunnels, a very economical and effective monitoring program is proposed, which is to use the train vibration response to identify and locate the damage of the tunnel structure. Firstly, the control equation of vehicle–tunnel coupling vibration is established and its analytical solution is given as the theoretical basis of this paper. Then, a damage index based on the cumulative sum of wavelet packet energy change rate (TDISC) is proposed, and its process algorithm is given. Through the joint simulation of VI-Rail and ANSYS, a refined 3D train-tunnel coupled vibration model is established. In this model, different combined conditions of single damage and double damage verify the validity of the damage index. The effectiveness of this damage index was further verified through model tests, and the influence of vehicle speed and load on the algorithm was discussed. Numerical simulation and experimental results show that the TDISC can effectively locate the damage of the tunnel structure and has good robustness.
Influence of Topography on the Site Selection of a Moon-Based Earth Observation Station
Authors: Chen Guoqiang , Guo Huadong , Ding Yixing , Shang Haolu , Lv Mingyang , Zhang Ke
Published: November 2021

The Moon provides a long-term, stable, and unique location for Earth observation. Several space agencies, such as NASA, ESA, and CNSA, have conducted lunar explorations. To build a Moon-based observation station, site selection is the first step. The time coverage of Earth observation, e.g., the whole Earth disc observation or Earth-related plasmasphere and magnetosphere, the duration of sunlight coverage, and topography (i.e., slope) are the three major factors influencing site selection, especially in the Moon’s south pole region. In this study, we used the Chang’E digital elevation model (DEM) together with Earth, Moon, and Sun positions deduced from JPL ephemeris for site selection. Two craters, Faustini and Shoemaker, were chosen for the fuzzy evaluation of these three factors based on a multiple-input single-output (MISO) model during a 19-year period. The results show that the edge regions of craters and small hills, potholes, or uplifts inside craters are unsuitable for a Moon-based observation station. The south pole area, including these two craters, has relatively low time coverage of sunlight and some unevenly distributed, permanent shadow areas. This indicates a low thermal environment for radiation protection, whereas the relatively flat topography and the ability to cover a field of view several times the Earth’s radius enable observations of the plasmasphere and magnetosphere.
Deceptive Techniques to Hide a Compressed Video Stream for Information Security
Authors: Heo Jeonghwan , Jeong Jechang
Published: November 2021

With the recent development of video compression methods, video transmission on traditional devices and video distribution using networks has increased in various devices such as drones, IP cameras, and small IoT devices. As a result, the demand for encryption techniques such as MPEG-DASH for transmitting streams over networks is increasing. These video stream security methods guarantee stream confidentiality. However, they do not hide the fact that the encrypted stream is being transmitted over the network. Considering that sniffing attacks can analyze the entropy of the stream and scan huge amounts of traffic on the network, to solve this problem, the deception method is required, which appears unencrypted but a confidential stream. In this paper, we propose the new deception method that utilizes standard NAL unit rules of video codec, where the unpromised device shows the cover video and the promised device shows the secret video for deceptive security. This method allows a low encryption cost and the stream to dodge entropy-based sniffing scan attacks. The proposed stream shows that successful decoding using five standard decoders and processing performance was 61% faster than the conventional encryption method in the test signal conformance set. In addition, a network encrypted stream scan method the HEDGE showed classification results that our stream is similar to a compressed video.
Evaluation of the Path-Tracking Accuracy of a Three-Wheeled Omnidirectional Mobile Robot Designed as a Personal Assistant
Authors: Palacín Jordi , Rubies Elena , Clotet Eduard , Martínez David
Published: November 2021

This paper presents the empirical evaluation of the path-tracking accuracy of a three-wheeled omnidirectional mobile robot that is able to move in any direction while simultaneously changing its orientation. The mobile robot assessed in this paper includes a precise onboard LIDAR for obstacle avoidance, self-location and map creation, path-planning and path-tracking. This mobile robot has been used to develop several assistive services, but the accuracy of its path-tracking system has not been specifically evaluated until now. To this end, this paper describes the kinematics and path-planning procedure implemented in the mobile robot and empirically evaluates the accuracy of its path-tracking system that corrects the trajectory. In this paper, the information gathered by the LIDAR is registered to obtain the ground truth trajectory of the mobile robot in order to estimate the path-tracking accuracy of each experiment conducted. Circular and eight-shaped trajectories were assessed with different translational velocities. In general, the accuracy obtained in circular trajectories is within a short range, but the accuracy obtained in eight-shaped trajectories worsens as the velocity increases. In the case of the mobile robot moving at its nominal translational velocity, 0.3 m/s, the root mean square (RMS) displacement error was 0.032 m for the circular trajectory and 0.039 m for the eight-shaped trajectory; the absolute maximum displacement errors were 0.077 m and 0.088 m, with RMS errors in the angular orientation of 6.27° and 7.76°, respectively. Moreover, the external visual perception generated by these error levels is that the trajectory of the mobile robot is smooth, with a constant velocity and without perceiving trajectory corrections.
Fully Automated and Robust Cable Tension Estimation of Wireless Sensor Networks System
Authors: Zhang Min , He Huating , Li Gengying , Wang Haiyang
Published: November 2021

Accurate estimation of cable tension is crucial for the structural health monitoring of cable-supported structures. Identifying the cable’s force from its vibration data is probably the most widely adopted method of cable tension estimation. According to string theory, the accuracy of estimated cable tension is highly related to identified modal parameters including natural frequencies and frequency order. To alleviate the factors that impact the accuracy of modal parameters when using the peak-picking method in wireless sensor networks, a fully automated and robust identifying method is proposed in this paper. This novel method was implemented on the Xnode wireless sensor system and validated with the data obtained from Jindo Bridge. The experiment results indicate that, through this method, the wireless sensor is able to distinguish the cognizable power spectrum, extract the peaks, eliminate false frequencies and determine frequency orders automatically to estimate cable tension force without any manual intervention or preprocessing. Meanwhile, the results of natural frequencies, corresponding orders and cable tension force obtained from the Xnode system show excellent agreement with the results obtained using the Matlab program method. This demonstrates the effectiveness and reliability of the Xnode estimation system. Furthermore, this method is also appropriate for other high-performance wireless sensor network systems to realize self-identification of cable in long-term monitoring.
On the Energy Performance of Iridium Satellite IoT Technology
Authors: Gomez Carles , Darroudi Seyed Mahdi , Naranjo Héctor , Paradells Josep
Published: November 2021

Most Internet of Things (IoT) communication technologies rely on terrestrial network infrastructure. When such infrastructure is not available or does not provide sufficient coverage, satellite communication offers an alternative IoT connectivity solution. Satellite-enabled IoT devices are typically powered by a limited energy source. However, as of this writing, and to our best knowledge, the energy performance of satellite IoT technology has not been investigated. In this paper, we model and evaluate the energy performance of Iridium satellite technology for IoT devices. Our work is based on real hardware measurements. We provide average current consumption, device lifetime, and energy cost of data delivery results as a function of different parameters. Results show, among others, that an Iridium-enabled IoT device, running on a 2400 mAh battery and sending a 100-byte message every 100 min, may achieve a lifetime of 0.95 years. However, Iridium device energy performance decreases significantly with message rate.