bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on a Second-Order Adaptive Sliding-Mode Observer Control Algorithm for the Sensorless Permanent Magnet Synchronous Motor
Authors: Yao Guozhong , Cheng Yuanpeng , Wang Zhengjiang , Xiao Yuhan
Published: May 2023

The control of a permanent magnet synchronous motor (PMSM) without a position sensor based on a sliding-mode observer (SMO) algorithm has a serious jitter problem in the process of motor phase tracking. A second-order adaptive sliding-mode observer algorithm was proposed, and the ideas and principles of the second-order sliding-mode observer algorithm based on the super-twisting algorithm were elaborated. In particular, adaptive estimation with the introduction of back-electromotive force (EMF) was investigated, and the Lyapunov stability criterion was used to determine the convergence properties of the algorithm. The results showed that the second-order adaptive sliding-mode observer algorithm had better jitter suppression and a better phase tracking performance than the traditional sliding-mode observer algorithm. The experimental results showed that when the motor velocity was 800 r/min, the velocity error of the second-order adaptive sliding-mode observer algorithm was 0.57 r/min and the position error was 0.018 rad, with accuracy improvements of 93.63% and 58.34%, respectively. When the motor velocity was 1000 r/min, the velocity error of the second-order adaptive sliding-mode observer algorithm was 0.94 r/min and the position error was 0.022 rad, with accuracy improvements of 90.55% and 55.10%, respectively. The jitter of the system was suppressed well, the curve of back-EMF was smoother, and the robustness of the system was high. Therefore, the second-order adaptive sliding-mode observer algorithm is more suitable for the position-sensorless control of a PMSM.
Soil Destabilization Induced by Water Wetting Treatments Simulating Rain Infiltration Processes, Studied via Rheology and Granulometry
Authors: Carotenuto Claudia , Minale Mario
Published: May 2023

A soil depleted of its organic carbon content is typically destabilized, i.e., its capacity to maintain its microstructure intact under various stress conditions weakens, and consequently, landslides and mudflows can be triggered and propagated more easily. In a previous work, we showed with a rheological analysis that the removal of the sole water-soluble organic carbon “destabilized” the slurry very similarly to what occurs with the removal of the vast majority of soil organic carbon. In principle, the water-soluble organic carbon can be dissolved by rainfall, during which water can infiltrate the soil, eventually leaving it either by percolation or evaporation. These two processes are mimicked here with two different soil water wetting procedures. The stability of the treated (wetted) soils is studied with rheological and granulometric experiments. The former run on concentrated suspensions, while the latter run on very diluted ones. Despite this, the results agreed very well, indicating that the two wetting procedures induce the same destabilization of the soil which behaves as the one depleted by the whole water-soluble organic carbon. Our results concluded that a soil destabilized by a wetting procedure, i.e., by a rainfall event, will be more prone to trigger a landslide that will propagate more swiftly and will stop with more difficulties.
Research of an Abandoned Tailings Deposit in the Iberian Pyritic Belt: Characterization and Gross Reserves Estimation
Authors: Davoise Diego , Méndez Ana
Published: May 2023

Global situations such as economic recovery after a pandemic, geopolitical instability, and future digital and energy transition are some of the drivers for the European Union (EU) to explore new and existing sources of raw materials. The Iberian Pyrite Belt in the southwest of the Iberian Peninsula (Spain and Portugal) hosts a great number of tailing deposits from centuries of mining operations. A unique tailings deposit has been studied and characterized. The similarities with other tailing deposits deeply studied suggested the presence of critical raw materials. Furthermore, a very gross reserves estimation was made. The characterization and reserves estimations were compared with the bibliography from mining companies who operated in the area decades ago and from the bibliography available at Fundación Riotinto. The presence of critical raw materials was confirmed, some of them in high concentrations. Moreover, a singular difference was found compared with other similar tailings stored within the Iberian Pyrite Belt. The main valuable metals identified were Au (2.25 ppm), Ag (215 ppm), Co (131 ppm) and Cu (0.29%). The reserves estimation showed that this deposit potentially hosts 1.86 t of Au, 177 t of Ag, 108 t of Co or 2358 t of Cu; in other words, with a copper average price of 8366 US$/t in December 2022, the tailings deposit contains a potential value of more than 19 million USD.
Applications of Differential Effective Medium (DEM)-Driven Correlations to Estimate Elastic Properties of Jafurah Tuwaiq Mountain Formation (TMF)
Authors: Shawaf Ali , Rasouli Vamegh , Dehdouh Abdesselem
Published: May 2023

Organic-rich mud rocks are being developed on a large scale worldwide, including in the Middle East. The Jurassic Tuwaiq Mountain Formation (TMF) in the Jafurah Basin is a potential world-class unconventional play. Based on a petrophysical evaluation of the Jafurah basin, the TMF exhibits exceptional and unconventional gas characteristics, such as a high total organic content (TOC) and low clay content. Additionally, the TMF is in the appropriate maturity window, indicating that it has reached the required level of thermal maturity to generate hydrocarbons. Plans for the development of the Jafurah unconventional field use multistage hydraulic fracturing technology. The elastic properties of the shale formation, particularly its Young’s modulus and Poisson’s ratio, dictate how the rock responds to stress and deformation. These properties strongly impact the growth of hydraulic fractures in shale formations. Without a comprehensive understanding of the elastic properties, predicting the bulk mechanical response of the target zones and surrounding layers would be challenging. Therefore, this study aims to predict the elastic characteristics of the Jafurah shale play considering the variations in carbonate facies, the kerogen volume fraction, and the pore’s geometry. Petrophysical and XRD data were used to estimate the elastic properties of various tiers (geological units) of the TMF (Tiers 1, 2, and 3). Inclusion-based, differential effective medium (DEM) rock physics models were used to estimate the formation’s elastic and velocity properties as a function of the kerogen volume fraction and the pore’s geometry. The results showed that the Young’s modulus as well as the mineral and elastic brittleness indices increase as the volume fraction of calcite increases. At the same time, they decrease due to intensified clay and kerogen volumes. The effect of the TMF’s elastic parameters on the rock brittleness behavior was also investigated by considering the formation’s mineralogy, as well as clay and kerogen contents. The results led to the development of physics-based correlations of the mineral brittleness index as function of the Young’s modulus and Poisson’s ratio for various tiers of the TMF.
Studying the Antioxidant and the Antimicrobial Activities of Leaf Successive Extracts Compared to the Green-Chemically Synthesized Silver Nanoparticles and the Crude Aqueous Extract from Azadirachta indica
Authors: Ahmed Mostafa , Marrez Diaa Attia , Mohamed Abdelmoeen Nadia , Abdelmoneem Mahmoud Ebtesam , Ali Mohamed Abdel-Shakur , Decsi Kincső , Tóth Zoltán
Published: May 2023

Azadirachta indica has several medicinal uses, especially its leaves. Over 4000 years ago, Ayurvedic medicine used it for its therapeutic benefits. This study examined the biological activity of Neem crude extracts and green-chemically produced Ag-NPs. TPCs and TFCs were measured for polyphenolic burden in consecutive extracts. DPPH, ABTS, and FRAP experiments measured antioxidant and antimicrobial activity against seven strains of food-borne pathogenic bacteria and eight mycotoxigenic fungi. At 1000 μg/mL, ethanolic and aqueous extracts of Neem leaves had 80.10% and 69.41% in DPPH and 71.42% and 74.61% in ABTS assays for the antioxidant activity, compared to 93.58% for BHT. At 800 μg/mL, both extracts showed antioxidant activity with 57.52 and 57.87 μM in the FRAP assay, compared to 139.97 μM for Ascorbic acid. Both extracts demonstrated antimicrobial activity with 0.02 to 0.35 mg/mL as antibacterials, 0.03 to 2.17 mg/mL as antifungals, and 0.04 to 0.42 mg/mL as antibacterials. Compared to Neem crude extract, Neem Ag-NPs had the lowest MIC values as antibacterials and antifungals at 0.05 to 0.07 mg/mL and 0.07 to 0.20 mg/mL, respectively. Neem Ag-NPs and crude extract boost antioxidant and antibacterial properties.
Panorama of Undergraduate Research in Brazil: Profile, Scientific Production, and Perceptions
Authors: Melo Angélica Ferreira , da Costa Woska Pires , Rodrigues Rhanya Rafaella , Nunes Lorena de Almeida Cavalcante Brandão , Noll Priscilla Rayanne E Silva , Noll Matias
Published: May 2023

Undergraduate Research (UR) is an institutional program that introduces undergraduate students to scientific research. The program selects research projects proposed by advisors and students for execution. Despite the importance of knowing the stages of research activities in undergraduate research, only a few studies have evaluated data on this subject. Therefore, this study aims to outline an overview of UR in a Brazilian educational institution, considering the profiles of students and advisors, students’ scientific productions, and perceptions about the experience of both. The study was a mixed-approach case study conducted through a questionnaire and interviews. The sample consisted of 213 undergraduate students and 167 UR supervisors. The results show that the largest group of students were aged 21 and 22 (46.6%) and supervisors 33 to 38 years (38.9%). Regarding the scientific productions of students, those who participated twice or more in undergraduate research had higher indicators compared to those who were participating for the first time. Students’ perceptions of their evolution and perceptions of the advisors were mostly positive, with a greater number of responses classified as very good to good. Thus, the satisfaction of researchers in being part of this experience was perceived and the need to improve the scientific production indicators of students, mediated by the advisors stimulating the writing of articles, abstracts, and books, as well as participation in events and patent development, was shown. We conclude that undergraduate research activities promote the integral development of students’ academic, scientific, personal, and professional terms, which ultimately reflect critical and emancipatory actions in society.
Anomalous Relaxation and Three-Level System: A Fractional Schrödinger Equation Approach
Authors: Lenzi Ervin K. , Gabrick Enrique C. , Sayari Elaheh , de Castro Antonio S. M. , Trobia José , Batista Antonio M.
Published: May 2023

We investigate a three-level system in the context of the fractional Schrödinger equation by considering fractional differential operators in time and space, which promote anomalous relaxations and spreading of the wave packet. We first consider the three-level system omitting the kinetic term, i.e., taking into account only the transition among the levels, to analyze the effect of the fractional time derivative. Afterward, we incorporate a kinetic term and the fractional derivative in space to analyze simultaneous wave packet transition and spreading among the levels. For these cases, we obtain analytical and numerical solutions. Our results show a wide variety of behaviors connected to the fractional operators, such as the non-conservation of probability and the anomalous spread of the wave packet.
Attributes and Activities of Religious Communities in Italy: First Results from a City Congregations Study (CCS)
Authors: Breskaya Olga , Giordan Giuseppe , Mignardi Martina , Sbalchiero Stefano
Published: May 2023

This article explores the attributes and religious, social and political activities of local religious groups in three Italian cities across all religious traditions. This is the first application of Congregations Study methodology in Italy to analyze the social composition, structure and activities of religious communities. The research was conducted between 2020 and 2021 with a total number of 877 communities mapped in the cities of Bologna, Milan and Brescia, and their surroundings. All local religious groups in three cities and their surroundings were counted and one key informant per group was interviewed (N = 566) with a Congregations Study questionnaire. Based on the results of the interviews, we found that, during the last decade, the dynamics of growth of adults’ and children’s regular religious participation was distinct within the Muslim and Christian Orthodox communities. Social service for elderly, environmental programs and political activity were found to be promoted by the Catholic communities to a stronger degree, while activities linked to the support of migrants were endorsed stronger by Muslim and Orthodox groups. Moreover, this study assessed the theological, ethical and political orientation of religious communities, highlighting different trends across religious traditions. The article discusses various configurations of urban religious diversity by bringing similarities and contrasts between communities of dominant religious tradition and minority religions, thus questioning the applicability of City Congregations Study (CCS) methodology to the analysis of configurations of religious diversity in Italy.
AutoDRIVE: A Comprehensive, Flexible and Integrated Digital Twin Ecosystem for Autonomous Driving Research & Education
Authors: Samak Tanmay , Samak Chinmay , Kandhasamy Sivanathan , Krovi Venkat , Xie Ming
Published: May 2023

Prototyping and validating hardware–software components, sub-systems and systems within the intelligent transportation system-of-systems framework requires a modular yet flexible and open-access ecosystem. This work presents our attempt to develop such a comprehensive research and education ecosystem, called AutoDRIVE, for synergistically prototyping, simulating and deploying cyber-physical solutions pertaining to autonomous driving as well as smart city management. AutoDRIVE features both software as well as hardware-in-the-loop testing interfaces with openly accessible scaled vehicle and infrastructure components. The ecosystem is compatible with a variety of development frameworks, and supports both single- and multi-agent paradigms through local as well as distributed computing. Most critically, AutoDRIVE is intended to be modularly expandable to explore emergent technologies, and this work highlights various complementary features and capabilities of the proposed ecosystem by demonstrating four such deployment use-cases: (i) autonomous parking using probabilistic robotics approach for mapping, localization, path-planning and control; (ii) behavioral cloning using computer vision and deep imitation learning; (iii) intersection traversal using vehicle-to-vehicle communication and deep reinforcement learning; and (iv) smart city management using vehicle-to-infrastructure communication and internet-of-things.
Analysis of the 20-Year Variability of Ocean Wave Hazards in the Northwest Pacific
Authors: Li Rui , Wu Kejian , Zhang Wenqing , Dong Xianghui , Lv Lingyun , Li Shuo , Liu Jin , Babanin Alexander V.
Published: May 2023

In the Northwest Pacific (NWP), where a unique monsoon climate exists and where both typhoons and extratropical storms occur frequently, hazardous waves pose a significant risk to maritime safety. To analyze the 20-year variability of hazardous waves in this region, this study utilized hourly reanalysis data from the ECMWF ERA5 dataset covering the period from 2001–2020, alongside the wave risk assessment method. The ERA5 data exhibits better consistency, in both the temporal and spatial dimensions, than satellite data. Although hazardous wind seas occur more frequently than hazardous swells, swells make hazardous waves travel further. Notably, the extreme wave height (EWH) shows an increasing trend in high- and low-latitude areas of the NWP. The change in meridional wind speeds is the primary reason for the change in the total wind speed in the NWP. Notably, the maximum annual increase rate of 0.013 m/year for EWH exists in the region of the Japanese Archipelago. This study elucidated the distributions of wave height intensity and wave risk levels, noting that the EWHs of the 50-year and 100-year return periods can reach 20.92 m and 23.07 m, respectively.
Generation of High Temporal Resolution Full-Coverage Aerosol Optical Depth Based on Remote Sensing and Reanalysis Data
Authors: Long Zhiyong , Jin Zichun , Meng Yizhen , Ma Jin
Published: May 2023

Aerosol Optical Depth (AOD) is a crucial physical parameter used to measure the radiative and scattering properties of the atmosphere. Obtaining full-coverage AOD measurements is essential for a thorough understanding of its impact on climate and air quality. However, satellite-based AOD products can be affected by abnormal weather conditions and high reflectance surfaces, leading to gaps in spatial coverage. To address this issue, we propose a satellite-based AOD filling method based on hourly level-3 Himawari-8 AOD products. In this study, the optimal model with a mean bias error (MBE) less than 0.01 and a root-mean-square error (RMSE) less than 0.1 in most land cover types was selected to generate the full-coverage AOD. The generated full-coverage AOD was validated against in situ measurements from the AERONET sites and compared with the performance of Himawari-8 AOD and MERRA-2 AOD over the AERONET sites. The validation results indicate that the accuracy of full-coverage AOD is comparable to that of the Advanced Himawari Imager (AHI) AOD, and for other land cover types (excluding barren land), the accuracy of full-coverage AOD is superior to that of MERRA-2 AOD. To investigate the practical application of full-coverage AOD, we utilized it as an input parameter to perform radiative transfer simulations in northwestern and southern China. The validation results showed that the simulated at-sensor radiance based on full-coverage AOD was in good agreement with the at-sensor radiance observations from MODIS. These results indicate that complete and accurate measurements of AOD have considerable potential for application in the simulation of at-sensor radiance and other related topics.
Mapping Malaria Vector Habitats in West Africa: Drone Imagery and Deep Learning Analysis for Targeted Vector Surveillance
Authors: Trujillano Fedra , Jimenez Garay Gabriel , Alatrista-Salas Hugo , Byrne Isabel , Nunez-del-Prado Miguel , Chan Kallista , Manrique Edgar , Johnson Emilia , Apollinaire Nombre , Kouame Kouakou Pierre , Oumbouke Welbeck A. , Tiono Alfred B. , Guelbeogo Moussa W. , Lines Jo , Carrasco-Escobar Gabriel , Fornace Kimberly
Published: May 2023

Disease control programs are needed to identify the breeding sites of mosquitoes, which transmit malaria and other diseases, in order to target interventions and identify environmental risk factors. The increasing availability of very-high-resolution drone data provides new opportunities to find and characterize these vector breeding sites. Within this study, drone images from two malaria-endemic regions in Burkina Faso and Côte d’Ivoire were assembled and labeled using open-source tools. We developed and applied a workflow using region-of-interest-based and deep learning methods to identify land cover types associated with vector breeding sites from very-high-resolution natural color imagery. Analysis methods were assessed using cross-validation and achieved maximum Dice coefficients of 0.68 and 0.75 for vegetated and non-vegetated water bodies, respectively. This classifier consistently identified the presence of other land cover types associated with the breeding sites, obtaining Dice coefficients of 0.88 for tillage and crops, 0.87 for buildings and 0.71 for roads. This study establishes a framework for developing deep learning approaches to identify vector breeding sites and highlights the need to evaluate how results will be used by control programs.
Mapping Small Watercourses from DEMs with Deep Learning—Exploring the Causes of False Predictions
Authors: Koski Christian , Kettunen Pyry , Poutanen Justus , Zhu Lingli , Oksanen Juha
Published: May 2023

Vector datasets of small watercourses, such as rivulets, streams, and ditches, are important for many visualization and analysis use cases. Mapping small watercourses with traditional methods is laborious and costly. Convolutional neural networks (CNNs) are state-of-the-art computer vision methods that have been shown to be effective for extracting geospatial features, including small watercourses, from LiDAR point clouds, digital elevation models (DEMs), and aerial images. However, the cause of the false predictions by machine-learning models is often not thoroughly explored, and thus the impact of the results on the process of producing accurate datasets is not well understood. We digitized a highly accurate and complete dataset of small watercourses from a study area in Finland. We then developed a process based on a CNN that can be used to extract small watercourses from DEMs. We tested and validated the performance of the network with different input data layers, and their combinations to determine the best-performing layer. We analyzed the false predictions to gain an understanding of their nature. We also trained models where watercourses with high levels of uncertainty were removed from the training sets and compared the results to training models with all watercourses in the training set. The results show that the DEM was the best-performing layer and that combinations of layers provided worse results. Major causes of false predictions were shown to be boundary errors with an offset between the prediction and labeled data, as well as errors of omission by watercourses with high levels of uncertainty. Removing features with the highest level of uncertainty from the labeled dataset increased the overall f1-score but reduced the recall of the remaining features. Additional research is required to determine if the results remain similar to other CNN methods.
Describing Polyps Behavior of a Deep-Sea Gorgonian, Placogorgia sp., Using a Deep-Learning Approach
Authors: Prado Elena , Abad-Uribarren Alberto , Ramo Rubén , Sierra Sergio , González-Pola César , Cristobo Javier , Ríos Pilar , Graña Rocío , Aierbe Eneko , Rodríguez Juan Manuel , Rodríguez-Cabello Cristina , Modica Larissa , Rodríguez-Basalo Augusto , Sánchez Francisco
Published: May 2023

Gorgonians play a fundamental role in the deep sea (below 200 m depth), composing three-dimensional habitats that are characterized by a high associated biodiversity and playing an important part in biogeochemical cycles. Here we describe the use of a benthic lander to monitoring polyps activity, used as a proxy of gorgonian feeding activity of three colonies of Placogorgia sp. Images cover a period of 22 days with a temporal resolution of 30 min. In addition, this seafloor observatory is instrumented with oceanographic sensors that allows continuous monitoring of the hydrographic conditions in the site. Deep-learning is used for automatic detection of the state of the polyps registered in the images. More than 1000 images of 3 large specimens of gorgonians are analyzed, annotating polyps as extended or retracted, using the semantic segmentation algorithm ConvNeXt. The segmentation results are used to describe the feeding patterns of this species. Placogorgia sp. shows a daily pattern of feeding conduct, depending on the hours of day and night. Using a Singular Spectrum Analysis approach, feeding activity is related to currents dynamics and Acoustic Doppler Current Profile (ADCP) return signal intensity, as proxy of suspended matter, achieving a linear correlation of 0.35 and 0.11 respectively. This is the first time that the behavior of the Placogorgia polyps, directly related to their feeding process, is described.
Absorbing Aerosol Optical Properties and Radiative Effects on Near-Surface Photochemistry in East Asia
Authors: Chen Huimin , Zhuang Bingliang , Liu Jane , Zhou Yinan , Hu Yaxin , Chen Yang , Gao Yiman , Wei Wen , Lin Huijuan , Li Shu , Wang Tijian , Xie Min , Li Mengmeng
Published: May 2023

Absorbing aerosols have significant influences on tropospheric photochemistry and regional climate change. Here, the direct radiative effects of absorbing aerosols at the major AERONET sites in East Asia and corresponding impacts on near-surface photochemical processes were quantified by employing a radiation transfer model. The average annual aerosol optical depth (AOD) of sites in China, Korea, and Japan was 1.15, 1.02 and 0.94, respectively, and the corresponding proportion of absorbing aerosol optical depth (AAOD) was 8.61%, 6.69%, and 6.49%, respectively. The influence of absorbing aerosol on ultraviolet (UV) radiation mainly focused on UV-A band (315–400 nm). Under the influence of such radiative effect, the annual mean near-surface J[NO2] (J[O1D]) of sites in China, Korea, and Japan decreased by 16.95% (22.42%), 9.61% (13.55%), and 9.63% (13.79%), respectively. In Beijing–Tianjin–Hebei (BTH) and Yangtze River Delta (YRD) region, the annual average AOD was 1.48 and 1.29, and the AAOD was 0.14 and 0.13, respectively. The UV radiative forcing caused by aerosols dominated by black carbon (BC-dominated aerosols) on the surface was −3.19 and −2.98 W m−2, respectively, accounting for about 40% of the total aerosol radiative forcing, indicating that the reduction efficiency of BC-dominated aerosols on solar radiation was higher than that of other types of aerosols. The annual mean J[NO2] (J[O1D]) decreased by 14.90% (20.53%) and 13.71% (18.20%) due to the BC-dominated aerosols. The daily maximum photolysis rate usually occurred near noon due to the diurnal variation of solar zenith angle and, thus, the daily average photolysis rate decreased by 2–3% higher than that average during 10:00–14:00.
Changes in Carbon Dioxide Balance Associated with Land Use and Land Cover in Brazilian Legal Amazon Based on Remotely Sensed Imagery
Authors: Crivelari-Costa Patrícia Monique , Lima Mendelson , La Scala Jr. Newton , Rossi Fernando Saragosa , Della-Silva João Lucas , Dalagnol Ricardo , Teodoro Paulo Eduardo , Teodoro Larissa Pereira Ribeiro , Oliveira Gabriel de , Junior José Francisco de Oliveira , Silva Junior Carlos Antonio da
Published: May 2023

The Amazon region comprises the largest tropical forest on the planet and is responsible for absorbing huge amounts of CO2 from the atmosphere. However, changes in land use and cover have contributed to an increase in greenhouse gas emissions, especially CO2, and in endangered indigenous lands and protected areas in the region. The objective of this study was to detect changes in CO2 emissions and removals associated with land use and land cover changes in the Brazilian Legal Amazon (BLA) through the analysis of multispectral satellite images from 2009 to 2019. The Gross Primary Production (GPP) and CO2Flux variables were estimated by the MODIS sensor onboard Terra and Aqua satellite, representing carbon absorption by vegetation during the photosynthesis process. Atmospheric CO2 concentration was estimated from the GOSAT satellite. The variables GPP and CO2Flux showed the effective flux of carbon in the BLA to atmosphere, which were weakly correlated with precipitation (r = 0.191 and 0.133). The forest absorbed 211.05 TgC annually but, due to its partial conversion to other land uses, the loss of 135,922.34 km2 of forest area resulted in 5.82 TgC less carbon being absorbed. Pasture and agriculture, which comprise the main land conversions, increased by 100,340.39 km2 and absorbed 1.32 and 3.19 TgC less, and emitted close to twice more, than forest in these areas. Atmospheric CO2 concentrations increased from 2.2 to 2.8 ppm annually in BLA, with hotspots observed in the southeast Amazonia, and CO2 capture by GPP showed an increase over the years, mainly after 2013, in the north and west of the BLA. This study brings to light the carbon dynamics, by GPP and CO2Flux models, as related to the land use and land cover in one of the biggest world carbon reservoirs, the Amazon, which is also important to fulfillment of international agreements signed by Brazil to reduce greenhouse gas emissions and for biodiversity conservation and other ecosystem services in the region.
A GNSS Spoofing Detection and Direction-Finding Method Based on Low-Cost Commercial Board Components
Authors: Mao Pengrui , Yuan Hong , Chen Xiao , Gong Yingkui , Li Shuhui , Li Ran , Luo Ruidan , Zhao Guangyao , Fu Chengang , Xu Jiajia
Published: May 2023

The Global Navigation Satellite System (GNSS) is vulnerable to deliberate spoofing signal attacks. Once the user wrongly locks on the spoofing signal, the wrong position, velocity, and time (PVT) information will be calculated, which will harm the user. GNSS spoofing signals are difficult to carry out spoofing attacks in the direction of arrival (DOA) of the real signal, so the spoofing detection method based on DOA is very effective. On the basis of identifying spoofing signals, accurate DOA information of the signal can be further used to locate the spoofer. At present, the existing DOA monitoring methods for spoofing signals are mainly based on dedicated antenna arrays and receivers, which are costly and difficult to upgrade and are not conducive to large-scale deployment, upgrade, and maintenance. This paper proposes a spoofing detection and direction-finding method based on a low-cost commercial GNSS board component (including an antenna). Based on the traditional principle of using a multi-antenna carrier phase to solve DOA, this paper innovatively solves the following problems: the poor direction-finding accuracy caused by the unstable phase center of low-cost commercial antennas, the low success rate of spoofing detection in a multipath environment, and the inconsistent sampling time among multiple low-cost commercial GNSS boards. Moreover, the corresponding prototype equipment for spoofing detection and direction-finding is developed. The measured results show that it can effectively detect spoofing signals in open environments. Under a certain false alarm rate, the detection success rate can reach 100%, and the typical direction-finding accuracy can reach 5°.
Geometric Configuration Design and Fast Imaging for Multistatic Forward-Looking SAR Based on Wavenumber Spectrum Formation Approach
Authors: Liu Yumeng , Zhao Yijing , Ding Yi
Published: May 2023

Multistatic forward-looking synthetic aperture radar (Mu-FLSAR) has the potential of high-resolution imaging with short synthetic aperture time, which can improve the transmitter’s survivability, by coherently fusing simultaneously observed measurements of multiple receivers. However, the combined performance of the multiple measurements strictly depends on an appropriate geometric configuration among the transmitter and receivers because the forward-looking application limits the flight directions of receivers. In this paper, to design a geometric configuration for Mu-FLSAR, a wavenumber spectrum formation (WSF) approach is proposed based on the projection relationship between the wavenumber support regions (WSRs) and geometric configuration parameters. On the one hand, the projected pattern of multiple WSRs is deduced, and the relationship between multiple WSRs and the point spread function (PSF) is analyzed. Based on the geometric feature of the kernel WSR, which is formed by the transmitter and the master receiver, and the relationship between the geometric features and the geometric configuration parameters, including synthetic aperture time and azimuthal angle, a WSF method is proposed to visually and quickly deduce the geometric parameter of the salve receivers. On the other hand, based on the designed geometric configuration of Mu-FLSAR, a wavenumber-dependent fast polar format algorithm (WF-PFA) is proposed to efficiently reconstruct the targets relying on the geometric features of WSRs. Simulation results verify the proposed method.
An Automatic Method for Rice Mapping Based on Phenological Features with Sentinel-1 Time-Series Images
Authors: Tian Guixiang , Li Heping , Jiang Qi , Qiao Baojun , Li Ning , Guo Zhengwei , Zhao Jianhui , Yang Huijin
Published: May 2023

Rice is one of the most important staple foods in the world, feeding more than 50% of the global population. However, rice is also a significant emitter of greenhouse gases and plays a role in global climate change. As a result, quickly and accurately obtaining the rice mapping is crucial for ensuring global food security and mitigating global warming. In this study, we proposed an automated rice mapping method called automated rice mapping using V-shaped phenological features of rice (Auto-RMVPF) based on the time-series Sentinel-1A images, which are composed of four main steps. First, the dynamic threshold method automatically extracts abundant rice samples by flooding signals. Second, the second-order difference method automatically extracts the phenological period of rice based on the scattering feature of rice samples. Then, the key “V” feature of the VH backscatter time series, which rises before and after rice transplanting due to flooding, is used for rice mapping. Finally, the farmland mask is extracted to avoid interference from non-farmland features on the rice map, and the median filter is applied to remove noise from the rice map and obtain the final spatial distribution of rice. The results show that the Auto-RMVPF method not only can automatically obtain abundant rice samples but also can extract the accurate phenological period of rice. At the same time, the accuracy of rice mapping is also satisfactory, with an overall accuracy is more than 95% and an F1 score of over 0.91. The overall accuracy of the Auto-RMVPF method is improved by 2.8–12.2% compared with support vector machine (SVM) with an overall accuracy of 89.9% (25 training samples) and 92.2% (124 training samples), random forest (RF) with an overall accuracy of 82.8% (25 training samples) and 88.3% (124 training samples), and automated rice mapping using synthetic aperture radar flooding signals (ARM-SARFS) with an overall accuracy of 89.9%. Altogether, these experimental results suggest that the Auto-RMVPF method has broad prospects for automatic rice mapping, especially for mountainous regions where ground samples are often not easily accessible.
Surface Soil Moisture Retrieval of China Using Multi-Source Data and Ensemble Learning
Authors: Yang Zhangjian , He Qisheng , Miao Shuqi , Wei Feng , Yu Mingxiao
Published: May 2023

Large-scale surface soil moisture (SSM) distribution is very necessary for agricultural drought monitoring, water resource management, and climate change research. However, the current large-scale SSM products have relatively coarse spatial resolution, which limits their application. In this study, we estimate the 1 km daily SSM in China based on ensemble learning using a multi-source data set including in situ soil moisture measurements from 2980 meteorological stations, MODIS Surface Reflectance products, SMAP (Soil Moisture Active Passive) soil moisture products, ERA5-Land dataset, SRTM DEM and soil texture. Among them, in situ measurements are used as independent variables, and other data are used as dependent variables. In order to improve the spatio-temporal completeness of SSM, the missing value in SMAP soil moisture products were reconstructed using the Discrete Cosine Transformation-penalized Partial Least Square (DCT-PLS) method to provide spatially complete background field information for soil moisture retrieval. The results show that the reconstructed soil moisture value has high quality, and the DCT-PLS method can fully utilize the three-dimensional spatiotemporal information to fill the data gaps. Subsequently, the performance of four ensemble learning models of random forest (RF), extremely randomized trees (ERT), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM) for soil moisture retrieval was evaluated. The LightGBM outperformed the other three machine learning models, with a correlation coefficient (R2) of 0.88, a bias of 0.0004 m³/m³, and an unbiased root mean square error (ubRMSE) of 0.0366 m³/m³. The high correlation between the in situ soil moisture and the predicted values at each meteorological station further indicate that LightGBM can well capture the temporal variation of soil moisture. Finally, the model was used to map the 1 km daily SSM in China on the first day of each month from May to October 2018. This study can provide some reference and help for future long-term daily 1 km surface soil moisture mapping in China.
Line Scan Hyperspectral Imaging Framework for Open Source Low-Cost Platforms
Authors: Al-Hourani Akram , Balendhran Sivacarendran , Walia Sumeet , Hourani Tetiana
Published: May 2023

With advancements in computer processing power and deep learning techniques, hyperspectral imaging is continually being explored for improved sensing applications in various fields. However, the high cost associated with such imaging platforms impedes their widespread use in spite of the availability of the needed processing power. In this paper, we develop a novel theoretical framework required for an open source ultra-low-cost hyperspectral imaging platform based on the line scan method suitable for remote sensing applications. Then, we demonstrate the design and fabrication of an open source platform using consumer-grade commercial off-the-shelf components that are both affordable and easily accessible to researchers and users. At the heart of the optical system is a consumer-grade spectroscope along with a basic galvanometer mirror that is widely used in laser scanning devices. The utilized pushbroom scanning method provides a very high spectral resolution of 2.8 nm, as tested against commercial spectral sensors. Since the resolution is limited by the slit width of the spectroscope, we also provide a deconvolution method for the line scan in order to improve the monochromatic spatial resolution. Finally, we provide a cost-effective testing method for the hyperspectral imaging platform where the results validate both the spectral and spatial performances of the platform.
Analysis of Spatial and Temporal Variation in Water Coverage in the Sub-Lakes of Poyang Lake Based on Multi-Source Remote Sensing
Authors: Wang Chunyang , Xie Wenying , Li Tengteng , Wu Guiping , Wu Yongtuo , Wang Qifeng , Xu Zhixia , Song Hao , Yang Yingbao , Pan Xin
Published: May 2023

As the largest freshwater lake in China, Poyang Lake is an internationally important wetland and the largest migratory bird habitat in Asia. Many sub-lakes distributed in the lake basin are seasonal lakes, which have a significant impact on hydro-ecological processes and are susceptible to various changes. In this study, using multi-source remote sensing data, a continuous time-series construction method of water coverage suitable in Poyang Lake was developed. That method combined the downscaling of the MNDWI (modified normalized difference water index) with the ISODATA (iterative self-organizing data analysis technique algorithm), and its accuracy can be up to 97% in the months when Landsat 8 is available or 87% when it is unavailable. Based on that method, the increasing variation in water coverage was observed in the sub-lakes of Poyang Lake during 2013–2020 to be within a range of 200–690 km2 normally. The center of the sub-lakes always remained inundated (>80% inundation frequency), while the surrounding areas were probably kept dry for seven months (except for June to September). The dominant influencing factors of water coverage variations were different in different hydrological periods (wet season and dry–wet season: discharge; dry season: temperature and wind speed; wet–dry season: temperature and precipitation). In addition, “returning farmland to lakes” affected the increase in the water area in the sub-lakes. This study is helpful for the management of water resources and the protection of migratory birds in the Poyang Lake region.
A Calibration Method for Large-Footprint Full-Waveform Airborne Laser Altimeter without a Calibration Field
Authors: Li Shaoning , Yu Qifan , Fu Anmin , Zhang Guo
Published: May 2023

The geometrical measurement precision of laser spots is affected by the deviation between the parameters of the laser altimeter and the laboratory measurement results, and the inversion accuracy of surface object height is also limited. The measurement parameters and the load state can be obtained by calibration of the laser altimeter system. Usually, ground detectors are deployed to calibrate the measurement parameters of the laser altimeter, including the divergence angle and the energy distribution of the laser beam. A calibration method for a laser footprint spot without a calibration field was proposed in this paper, focused on the airborne large-footprint laser altimeter system. The geometric parameters of the laser spot were calibrated through the laser echo waveforms of a specific terrain. The experimental results show that geometric calibration of the large-footprint laser altimeter can be achieved in the area of the step surface. The divergence angle of the laser beams obtained from the six experimental areas is 4.604 ± 0.359 mRad, and the consistency of the energy distribution from each laser spot reaches 92.67%. A new method of on-orbit calibration and verification is provided for the satellite laser altimeter system.
Characterizing and Mapping Volcanic Flow Deposits on Mount St. Helens via Dual-Band SAR Imagery
Authors: Rogic Nikola , Charbonnier Sylvain J. , Garin Franco , Dayhoff II Guy W. , Gagliano Eric , Rodgers Mel , Connor Charles B. , Varma Sameer , Shean David
Published: May 2023

Mapping volcanic flow deposits can be achieved by considering backscattering characteristics as a metric of surface roughness. In this study, we developed an approach to extract a measure of surface roughness from dual-band airborne Synthetic Aperture Radar (ASAR) backscattering data to characterize and map various volcanic flow deposits—namely, debris avalanches, lahars, lava flows, and pyroclastic density currents. We employed ASAR and Indian Space Research Organization (ISRO) airborne SAR datasets, from a joint project (ASAR-ISRO), acquired in December 2019 at 2 m spatial resolution, to assess the role and importance of incorporating dual-band data, i.e., L-band and S-band, into surface roughness models. Additionally, we derived and analyzed surface roughness from a digital surface model (DSM) generated from unoccupied aircraft systems (UAS) acquisitions using Structure from Motion (SfM) photogrammetry techniques. These UAS-derived surface roughness outputs served as meter-scale calibration products to validate the radar roughness data over targeted areas. Herein, we applied our method to a region in the United States over the Mount St. Helens volcano in the Cascade Range of Washington state. Our results showed that dual-band systems can be utilized to characterize different types of volcanic deposits and range of terrain roughness. Importantly, we found that a combination of radar wavelengths (i.e., 9 and 24 cm), in tandem with high-spatial-resolution backscatter measurements, yields improved surface roughness maps, compared to single-band, satellite-based approaches at coarser resolution. The L-band (24 cm) can effectively differentiate small, medium, and large-scale structures, namely, blocks/boulders from fine-grained lahar deposits and hummocks from debris avalanche deposits. Additionally, variation in the roughness estimates of lahar and debris avalanche deposits can be identified and quantified individually. In contrast, the S-band (9 cm) can distinguish different soil moisture conditions across variable terrain; for example, identify wet active channels. In principle, this dual-band approach can also be employed with time series of various other SAR data of higher coherence (such as satellite SAR), using different wavelengths and polarizations, encompassing a wider range of surface roughness, and ultimately enabling additional applications at other volcanoes worldwide and even beyond volcanology.
Using CORONA Imagery to Study Land Use and Land Cover Change—A Review of Applications
Authors: Shahbandeh Mahsa , Kaim Dominik , Kozak Jacek
Published: May 2023

CORONA spy satellites offer high spatial resolution imagery acquired in the 1960s and early 1970s and declassified in 1995, and they have been used in various scientific fields, such as archaeology, geomorphology, geology, and land change research. The images are panchromatic but contain many details of objects on the land surface due to their high spatial resolution. This systematic review aims to study the use of CORONA imagery in land use and land cover change (LULC) research. Based on a set of queries conducted on the SCOPUS database, we identified and examined 54 research papers using such data in their study of LULC. Our analysis considered case-study area distributions, LULC classes and LULC changes, as well as the methods and types of geospatial data used alongside CORONA data. While the use of CORONA images has increased over time, their potential has not been fully explored due to difficulties in processing CORONA images. In most cases, study areas are small and below 5000 km2 because of the reported drawbacks related to data acquisition frequency, data quality and analysis. While CORONA imagery allows analyzing built-up areas, infrastructure and individual buildings due to its high spatial resolution and initial mission design, in LULC studies, researchers use the data mostly to study forests. In most case studies, CORONA imagery was used to extend the study period into the 1960s, with only some examples of using CORONA alongside older historical data. Our analysis proves that in order to detect LULC changes, CORONA can be compared with various contemporary geospatial data, particularly high and very high-resolution satellite imagery, as well as aerial imagery.
Drone-Based Imaging Polarimetry of Dark Lake Patches from the Viewpoint of Flying Polarotactic Insects with Ecological Implication
Authors: Száz Dénes , Takács Péter , Bernáth Balázs , Kriska György , Barta András , Pomozi István , Horváth Gábor
Published: May 2023

Aquatic insects detect water by the horizontal polarization of water-reflected light and thus are attracted to such light. Recently, in the Hungarian Lake Balaton we observed dark water patches forming between every autumn and spring because of the inflow of black suspended/dissolved organic matter into the bright lake water. Earlier, the polarization characteristics of such water surfaces were mapped by imaging polarimeters from the ground. In order to measure the reflection-polarization patterns of these dark lake patches from the higher viewpoint of flying polarotactic aquatic insects, we designed a drone-based imaging polarimeter. We found that the dark lake patches reflected light with very high (60% ≤ d ≤ 80%) degrees of horizontal polarization at the Brewster’s angle, while the bright lake water was only weakly (d < 20%) horizontally polarizing. There was a large contrast in both the radiance and degree of polarization between dark lake patches and bright lake water, while there was no such contrast in the angle of polarization. The ecological implication of these findings could be that these dark lake patches attract water-seeking polarotactic insects, which may oviposit more frequently in them than in the brighter lake water. However, it might not matter if they lay their eggs in these dark patches rather than the bright lake water, because this may simply increase the abundance of breeding flying insects in areas where dark patches are common.