bluuebunny/crossref_metadata_2025 huggingface dataset:
Ecological and Syntaxonomic Analysis of the Communities of Glebionis coronaria and G. discolor (Malvion neglectae) in the European Mediterranean Area
Authors: Cano Eusebio , Cano-Ortiz Ana , Quinto Canas Ricardo , Piñar Fuentes Jose Carlos , Rodrigues Meireles Catarina , Raposo Mauro , Pinto Gomes Carlos , Laface Valentina Lucia Astrid , Spampinato Giovanni , Musarella Carmelo Maria
Published: February 2024

Nitrophilous communities dominated by Glebionis coronaria and Glebionis discolor in the European Mediterranean area were studied. The nomenclature was corrected according to the current taxonomy, following the International Code of Phytosociological Nomenclature (ICPN). The statistical analysis revealed six new associations and one subassociation, with four in Spain, one in Greece, and one in Italy. Additionally, a subassociation of high relevance due to its endemic character was identified. These grasslands exhibit requirements for organic matter and other edaphic nutrients that are closer to those of Malva neglecta communities than to those of Hordeum murinum subsp. leporinum. We confirmed the published syntaxon with the rank of Resedo albae-Glebionenion coronariae suballiance and its subordination to the Malvion neglectae alliance, and we established the type association for this suballiance. Sisimbrietalia officinalis J. Tüxen in Lohmeyer et al. 1962 em. Rivas-Martínez, Báscones, T. E. Díaz, Fernández-González & Loidi 1991. Stellarietea mediae Tüxen, Lohmeyer & Preising ex von Rochow 1951.
Natural 2′,4-Dihydroxy-4′,6′-dimethoxy Chalcone Isolated from Chromolaena tacotana Inhibits Breast Cancer Cell Growth through Autophagy and Mitochondrial Apoptosis
Authors: Mendez-Callejas Gina , Piñeros-Avila Marco , Celis Crispin A. , Torrenegra Ruben , Espinosa-Benitez Anderson , Pestana-Nobles Roberto , Yosa-Reyes Juvenal
Published: February 2024

Breast cancer (BC) is one of the most common cancers among women. Effective treatment requires precise tailoring to the genetic makeup of the cancer for improved efficacy. Numerous research studies have concentrated on natural compounds and their anti-breast cancer properties to improve the existing treatment options. Chromolaena tacotana (Klatt) R.M. King and H. Rob (Ch. tacotana) is a notable source of bioactive hydroxy-methylated flavonoids. However, the specific anti-BC mechanisms of these flavonoids, particularly those present in the plant’s inflorescences, remain partly undefined. This study focuses on assessing a chalcone derivative extracted from Ch. tacotana inflorescences for its potential to concurrently activate regulated autophagy and intrinsic apoptosis in luminal A and triple-negative BC cells. We determined the chemical composition of the chalcone using ultraviolet (UV) and nuclear magnetic resonance (NMR) spectroscopy. Its selective cytotoxicity against BC cell lines was assessed using the MTT assay. Flow cytometry and Western blot analysis were employed to examine the modulation of proteins governing autophagy and the intrinsic apoptosis pathway. Additionally, in silico simulations were conducted to predict interactions between chalcone and various anti-apoptotic proteins, including the mTOR protein. Chalcone was identified as 2′,4-dihydroxy-4′,6′-dimethoxy-chalcone (DDC). This compound demonstrated a selective inhibition of BC cell proliferation and triggered autophagy and intrinsic apoptosis. It induced cell cycle arrest in the G0/G1 phase and altered mitochondrial outer membrane potential (∆ψm). The study detected the activation of autophagic LC3-II and mitochondrial pro-apoptotic proteins in both BC cell lines. The regulation of Bcl-XL and Bcl-2 proteins varied according to the BC subtype, yet they showed promising molecular interactions with DDC. Among the examined pro-survival proteins, mTOR and Mcl-1 exhibited the most favorable binding energies and were downregulated in BC cell lines. Further research is needed to fully understand the molecular dynamics involved in the activation and interaction of autophagy and apoptosis pathways in cancer cells in response to potential anticancer agents, like the hydroxy-methylated flavonoids from Ch. tacotana.
Interaction of Zinc Mineral Nutrition and Plant Growth-Promoting Bacteria in Tropical Agricultural Systems: A Review
Authors: Jalal Arshad , Júnior Enes Furlani , Teixeira Filho Marcelo Carvalho Minhoto
Published: February 2024

The relationship between zinc mineral nutrition and plant growth-promoting bacteria (PGPB) is pivotal in enhancing agricultural productivity, especially in tropical regions characterized by diverse climatic conditions and soil variability. This review synthesizes and critically evaluates current knowledge regarding the synergistic interaction between zinc mineral nutrition and PGPB in tropical agricultural systems. Zinc is an essential and fundamental micronutrient for various physiological and biochemical processes in plants. Its deficiency affects plant growth and development, decreasing yields and nutritional quality. In tropical regions, where soil zinc availability is often limited or imbalanced, the PGPB, through different mechanisms such as Zn solubilization; siderophore production; and phytohormone synthesis, supports Zn uptake and assimilation, thereby facilitating the adverse effects of zinc deficiency in plants. This review outlines the impacts of Zn–PGPB interactions on plant growth, root architecture, and productivity in tropical agricultural systems. The positive relationship between PGPB and plants facilitates Zn uptake and improves nutrient use efficiency, overall crop performance, and agronomic biofortification. In addition, this review highlights the importance of considering indigenous PGPB strains for specific tropical agroecosystems, acknowledging their adaptability to local conditions and their potential in sustainable agricultural practices. It is concluded that Zn fertilizer and PGPBs have synergistic interactions and can offer promising avenues for sustainable agriculture, addressing nutritional deficiencies, improving crop resilience, and ensuring food security.
Phytotoxic Ozone Dose–Response Relationships for Durum Wheat (Triticum durum, Desf.)
Authors: Marzuoli Riccardo , Faoro Franco , Picchi Valentina , Gerosa Giacomo A.
Published: February 2024

Ozone (O3) pollution poses a significant threat to global crop productivity, particularly for wheat, one of the most important staple foods. While bread wheat (Triticum aestivum) is unequivocally considered highly sensitive to O3, durum wheat (Triticum durum) was often found to be more tolerant. This study investigated the O3 dose–response relationships for durum wheat in the Mediterranean region, focusing mainly on grain yield losses, and utilizing the phytotoxic ozone dose (POD) metric to describe the intensity of the stressor. The results from two experiments with Open-Top Chambers performed in 2013 and 2014 on two relatively sensitive durum wheat cultivars confirmed that this wheat species is far more tolerant than bread wheat. The use of a local parameterization of a stomatal conductance model based on field measurements did not significantly improve the dose–response relationships obtained in comparison to the generic parameterization suggested by the Mapping Manual of the United Nations Economic Commission for Europe (UNECE). The POD6 critical level of 5 mmolO3 m−2 for 5% grain yield loss was remarkably higher than the one established for bread wheat with analogous experiments, highlighting that O3 risk assessments based on bread wheat may largely overestimate the damage in the Mediterranean region where durum wheat cultivation prevails.
A Physiological and Molecular Focus on the Resistance of “Filippo Ceo” Almond Tree to Xylella fastidiosa
Authors: De Pascali Mariarosaria , Greco Davide , Vergine Marzia , Carluccio Giambattista , De Bellis Luigi , Luvisi Andrea
Published: February 2024

The impact of Xylella fastidiosa (Xf) subsp. pauca on the environment and economy of Southern Italy has been devastating. To restore the landscape and support the local economy, introducing new crops is crucial for restoring destroyed olive groves, and the almond tree (Prunus dulcis Mill. D. A. Webb) could be a promising candidate. This work focused on the resistance of the cultivar “Filippo Ceo” to Xf and evaluated its physiological and molecular responses to individual stresses (drought or pathogen stress) and combined stress factors under field conditions over three seasons. Filippo Ceo showed a low pathogen concentration (≈103 CFU mL−1) and a lack of almond leaf scorch symptoms. Physiologically, an excellent plant water status was observed (RWC 82–89%) regardless of the stress conditions, which was associated with an increased proline content compared to that of the control plants, particularly in response to Xf stress (≈8-fold). The plant’s response did not lead to a gene modulation that was specific to different stress factors but seemed more indistinct: upregulation of the LEA and DHN gene transcripts by Xf was observed, while the PR transcript was upregulated by drought stress. In addition, the genes encoding the transcription factors (TFs) were differentially induced by stress conditions. Filippo Ceo could be an excellent cultivar for coexistence with Xf subps. pauca, confirming its resistance to both water stress and the pathogen, although this similar health status was achieved differently due to transcriptional reprogramming that results in the modulation of genes directly or indirectly involved in defence strategies.
Effect of Silica Fume Utilization on Structural Build-Up, Mechanical and Dimensional Stability Performance of Fiber-Reinforced 3D Printable Concrete
Authors: Şahin Hatice Gizem , Mardani Ali , Beytekin Hatice Elif
Published: February 2024

It is known that 3D printable concrete mixtures can be costly because they contain high dosages of binder and that the drying-shrinkage performance may be adversely affected. Mineral additives and fibers are generally used to control these negative aspects. In this study, the use of silica fume, a natural viscosity modifying admixture, was investigated to improve the rheological and thixotropic behavior of 3D printable concrete mixtures reinforced with polypropylene fiber (FR-3DPC). The effect of increasing the silica fume utilization ratio in FR-3DPC on the compressive strength (CS), flexural strength (FS), and drying-shrinkage (DS) performance of the mixtures was also examined. A total of five FR-3DPC mixtures were produced using silica fume at the rate of 3, 6, 9, and 12% of the cement weight, in addition to the control mixture without silica fume. As a result of the tests, the dynamic yield stress value decreased with the addition of 3% silica fume to the control mixture. However, it was found that the dynamic yield stress and apparent viscosity values of the mixtures increased with the addition of 6, 9, and 12% silica fume. With the increase in the use of silica fume, the CS values of the mixtures were generally affected positively, while the FS and DS behavior were affected negatively.
Effect of End Groups on the Cloud Point Temperature of Aqueous Solutions of Thermoresponsive Polymers: An Inside View by Flory–Huggins Theory
Authors: Dang Thi To Nga , Nies Erik
Published: February 2024

In an effort to gain insight into the origin of the effects of end groups on the cloud point temperature (Tcp) as a function of the polymer molar mass of thermoresponsive polymers with lower critical solution behavior in dilute aqueous solutions, we use the Flory–Huggins (FH) theory amended for end groups. The theory was applied to available experimental data sets of poly(N-isopropylacrylamide) (PNIPAM), poly(4-vinylbenzyl methoxytris(oxyethylene) ether) (PTEGSt), and poly(α-hydro-ω-(4-vinylbenzyl)tetrakis(oxyethylene) ether) (PHTrEGSt). The theory relates the variations in TcpM,ϕcp for different end groups to the effective FH χ parameter of the end groups and explains the qualitative notion that the influence of the end groups is related to the hydrophobicity/hydrophilicity of the end groups relative to that of the so called intrinsic TcpM,ϕcp response of a polymer without end groups. The limits to the applicability of the FH theory are established, and a set of possible theoretical improvements is considered. The ultimate scrutiny of the simple FH theory and suggested improved theories must await the measurement of truly thermodynamic cloud points; the available cloud points are merely estimations of the thermodynamic cloud point, for which the deviation to the true cloud point cannot be established with sufficient accuracy.
Rheological and Mechanical Characterization of 3D-Printable Solid Propellant Slurry
Authors: Zumbo Alessandra , Stumpo Leonardo , Antonaci Paola , Ferrero Andrea , Masseni Filippo , Polizzi Giovanni , Tetti Giacomo , Pastrone Dario
Published: February 2024

This study delves into the rheological and mechanical properties of a 3D-printable composite solid propellant with 80% wt solids loading. Polybutadiene is used as a binder with ammonium sulfate, which is added as an inert replacement for the ammonium perchlorate oxidizer. Further additives are introduced to allow for UV curing. An in-house illumination system made of four UV-A LEDs (385 nm) is employed to cure the resulting slurry. Rheological and mechanical tests are conducted to evaluate the viscosity, ultimate tensile strength and strain, and compression behavior. Viscosity tests are performed for both pure resin and complete propellant composition. A viscosity reduction factor is obtained for the tested formulations when pre-heating slurry. Uniaxial tensile and compression tests reveal that the mechanical properties are consistent with previous research. Results emphasize the critical role of temperature and solid loading percentage. Pre-heating resin composites may grant a proper viscosity reduction while keeping mechanical properties in the applicability range. Overall, these findings pave the way for the development of a 3D printer prototype for composite solid propellants.
Vortex of a Symmetric Jet Structure in a Natural Gas Pipeline via Proper Orthogonal Decomposition
Authors: Li Lihao , Lu Jiaxing , Zhao Haoyu , Qiu Yilong
Published: February 2024

The impact of particle addition jets on the flow field in natural gas pipelines was investigated, and the structural information of the flow field at different flow velocities in a symmetric jet flow was analyzed via numerical simulation. The results of coherent structures in the high-pressure natural gas pipeline reveal vortex structures of varying sizes both upstream and downstream of the jet flow. To determine the spatial distribution of the main vortex structures in the flow field, proper orthogonal decomposition (POD) mode analysis was performed on the unsteady numerical results. Moreover, the detailed spatial characteristics of the coherent vortex structures represented by each mode were obtained. The results indicate that the large-scale vortex structures within the pipeline are balanced and stable, with their energy increasing as the jet flow velocity increases. Additionally, higher-order modes exhibit significant shedding of small-scale vortex structures downstream of the jet flow. In this research, coherent structures present in symmetric particle addition jets are provided, offering theoretical support for future investigations on the distribution of particle image velocimetry (PIV) flowmeters.
An Integrated Risk Assessment Methodology of In-Service Hydrogen Storage Tanks Based on Connection Coefficient Algorithms and Quintuple Subtraction Set Pair Potential
Authors: Liang Xiaobin , Fei Fan , Wang Lei , Mou Daibin , Ma Weifeng , Yao Junming
Published: February 2024

At present, there have been a number of hydrogen storage tank explosions in hydrogen filling stations, causing casualties and property losses, and having a bad social impact. This has made people realize that the risk assessment and preventive maintenance of hydrogen storage tanks are crucial. Therefore, this paper innovatively proposes a comprehensive risk assessment model based on connection coefficient algorithms and quintuple subtractive set pair potential. First of all, the constructed index system contains five aspects of corrosion factors, material factors, environmental factors, institutional factors and human factors. Secondly, a combined weighting analysis method based on FAHP and CRITIC is proposed to determine the weight of each indicator. The basic indicators influencing hydrogen storage tanks are analyzed via the quintuple subtraction set pair potential and full partial connection coefficient. Finally, the risk level and development trend of hydrogen storage tanks in hydrogen filling stations are determined by a combination of the three-category connection coefficient algorithms and the risk level eigenvalue method. The results of our case analysis show that the proposed risk assessment model can identify the main weak indicators affecting the safety of hydrogen storage tanks, including installation quality, misoperation and material quality. At the same time, it is found that the risk of high-pressure hydrogen storage tanks is at the basic safety level, and the development trend of safety conditions holds a critical value. The evaluation results can help establish targeted countermeasures for the prevention and maintenance of hydrogen storage tanks.
Time of Consolidation and Humidity Influence on Properties of Food Powders
Authors: Stasiak Mateusz , Wajs Justyna , Bańda Maciej , Combrzyński Maciej , Gondek Ewa , Wiącek Joanna
Published: February 2024

The effect of short-term storage at 75% and 90% ambient humidity on the mechanical properties of selected materials was determined using a new device for measuring the strength of food powders. A series of tests were conducted on wheat flour and potato starch subjected to various consolidation loads. The high accuracy and repeatability of the measurements confirmed the suitability of the pull-based tester for assessing the degree of caking in food powders. The pull-based tester allows for the measurement of strength parameters of agglomerates under various consolidation loads while simultaneously wetting the powder, introducing a novel approach to assessing the mechanical properties of powders. The analysis of force oscillation during the withdrawal of the measuring rod from the powder facilitates the identification of the slip-stick effect in these materials and the determination of parameters characterizing that phenomenon. The outcomes of this study may be of interest to farmers, manufacturers, and companies processing raw materials.
The Treatment of Natural Calcium Materials Using the Supercritical Antisolvent Method for CO2 Capture Applications
Authors: Nobre Luís C. S. , Teixeira Paula , Pinheiro Carla I. C. , Palavra António M. F. , Calvete Mário J. F. , Nieto de Castro Carlos A. , Nobre Beatriz P.
Published: February 2024

The potential of the supercritical antisolvent micronization (SAS) technique was evaluated for the production of CaO-based particles with a size and a physical structure that could enable high performance for CO2 capture through the calcium looping process. Two sources of calcium derivative compounds were tested, waste marble powder (WMP) and dolomite. The SAS micronization of the derivate calcium acetate was carried out at 60 °C, 200 bar, a 0.5 mL min−1 flow rate of liquid solution, and 20 mg mL−1 concentration of solute, producing, with a yield of more than 70%, needle-like particles. Moreover, since dolomite presents with a mixture of calcium and magnesium carbonates, the influence of the magnesium fraction in the SAS micronization was also assessed. The micronized mixtures with lower magnesium content (higher calcium fraction) presented needle-like particles similar to WMP. On the other hand, for the higher magnesium fractions, the micronized material was similar to magnesium acetate micronization, presenting sphere-like particles. The use of the micronized material in the Ca-looping processes, considering 10 carbonation-calcination cycles under mild and realistic conditions, showed that under mild conditions, the micronized WMP improved CaO conversion. After 10 cycles the micronization, WMP presented a conversion 1.8 times greater than the unprocessed material. The micronized dolomite, under both mild and real conditions, maintained more stable conversion after 10 cycles.
Evolution of Wetland Patterns and Key Driving Forces in China’s Drylands
Authors: Wu Xiaolan , Zhao Hui , Wang Meihong , Yuan Quanzhi , Chen Zhaojie , Jiang Shizhong , Deng Wei
Published: February 2024

Wetlands within dryland regions are highly sensitive to climate change and human activities. Based on three types of land use data sources from satellite images and a spatial data analysis, the spatiotemporal characteristics of wetland evolution in China’s drylands and their relationship with human interference and climate change from 1990 to 2020 were analyzed. The results were as follows: (1) The wetlands within China’s drylands expanded, including rivers, lakes, and artificial wetlands, apart from marshes, which shrunk. Meanwhile, wetland fragmentation increased, with rivers being particularly severely fragmented. (2) Temperature and precipitation showed an increasing trend from 1990 to 2020 in China’s drylands. Lakes and rivers expanded with regional differences due to the uneven distribution of precipitation and rising temperature. (3) Human activities, more than climate change, became the key driving factor for the changes in wetland patterns in China’s drylands. The increased areas of farmland and grassland along with increased levels of drainage and irrigation activities led to the shrinkage of marshes and the fragmentation of rivers. The increase in the number of artificial reservoirs was the main reason for the expansion of artificial wetlands. This study clarifies the specific driving factors of different types of wetlands within China’s drylands, which is of great use for better protecting wetlands and the gradual restoration of degraded wetlands.
Comprehensive Evaluation of Near-Real-Time Satellite-Based Precipitation: PDIR-Now over Saudi Arabia
Authors: Alharbi Raied Saad , Dao Vu , Jimenez Arellano Claudia , Nguyen Phu
Published: February 2024

In the past decade, Saudi Arabia has witnessed a surge in flash floods, resulting in significant losses of lives and property. This raises a need for accurate near-real-time precipitation estimates. Satellite products offer precipitation data with high spatial and temporal resolutions. Among these, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Dynamic Infrared Rain Rate near-real-time (PDIR-Now) stands out as a novel, global, and long-term resource. In this study, a rigorous comparative analysis was conducted from 2017 to 2022, contrasting PDIR-Now with rain gauge data. This analysis employs six metrics to assess the accuracy of PDIR-Now across various daily rainfall rates and four yearly extreme precipitation indices. The findings reveal that PDIR-Now slightly underestimates light precipitation but significantly underestimates heavy precipitation. Challenges arise in regions characterized by orographic rainfall patterns in the southwestern area of Saudi Arabia, emphasizing the importance of spatial resolution and topographical considerations. While PDIR-Now successfully captures annual maximum 1-day and 5-day precipitation measurements across rain gauge locations, it exhibits limitations in the length of wet and dry spells. This research highlights the potential of PDIR-Now as a valuable tool for precipitation estimation, offering valuable insights for hydrological, climatological, and water resource management studies.
ATLAS: Latest Advancements and First Observations
Authors: Pandeirada João , Bergano Miguel , Marques Paulo , Coelho Bruno , Barbosa Domingos , Figueiredo Mário
Published: February 2024

The increasing amount of space debris poses a significant threat to operational satellites and space-based services. This article updates the community on the current status of the development of ATLAS, a tracking radar that is part of the EUSST network and aims to detect space objects in low Earth orbits. This article focuses on the latest activities performed: calibration of the pointing system and initial observations of space objects. The calibration procedure consisted of cross-scanning the Solar disk and yielded great results, obtaining an offset of 5.3° in azimuth and 0.10° in elevation. The first observation campaign resulted in 33 range detections of the International Space Station (ISS) with a probability of false alarm of 10−9. The observations were then used to readjust the radar equation to assess the real-world performance of the system.
Quantifying Spatio-Temporal River Morphological Change and Its Consequences in the Vietnamese Mekong River Delta Using Remote Sensing and Geographical Information System Techniques
Authors: Vu Thi Huong , Binh Doan Van , Tran Huan Ngoc , Khan Muhammad Adnan , Bui Duong Du , Stamm Jürgen
Published: February 2024

The evolution of delta and riverbank erosion within the river basin can significantly impact the environment, ecosystems, and lives of those residing along rivers. The Vietnamese Mekong Delta (VMD), counted among the world’s largest deltas, has undergone significant morphological alterations via natural processes and human activities. This research aims to examine these morphological alterations and their impacts on local economic and social conditions in the VMD. This study utilized satellite data from 1988 to 2020, coupled with population density and land use/land cover (LULC) maps from 2002, 2008, and 2015. The findings reveal that the VMD experienced widespread erosion over the past three decades, covering an area of 66.8 km2 and affecting 48% of the riverbank length (682 km). In contrast to riverbanks, islets showed an accretion trend with an additional area of 13.3 km2, resulting in a decrease in river width over the years. Riverbank and islet erosion has had a profound impact on the LULC, population, and economy of the provinces along the VMD. From 2002 to 2020, eight different land use types were affected, with agricultural land being the most severely eroded, constituting over 86% of the total lost land area (3235.47 ha). The consequences of land loss due to erosion affected 31,273 people and resulted in substantial economic damages estimated at VND 19,409.90 billion (USD 799.50 million) across nine provinces along the VMD. Notably, even though built-up land represented a relatively small portion of the affected area (6.58%), it accounted for the majority of the economic damage at 70.6% (USD 564.45 million). This study underscores the crucial role of satellite imagery and GIS in monitoring long-term morphological changes and assessing their primary impacts. Such analysis is essential for formulating effective plans and strategies for the sustainable management of river environments.
Precise Drought Threshold Monitoring in Winter Wheat Using the Unmanned Aerial Vehicle Thermal Method
Authors: Liu Hongjie , Song Wenlong , Lv Juan , Gui Rongjie , Shi Yangjun , Lu Yizhu , Li Mengyi , Chen Long , Chen Xiuhua
Published: February 2024

Accurate monitoring of crop drought thresholds at different growth periods is crucial for drought monitoring. In this study, the canopy temperature (Tc) of winter wheat (‘Weilong 169’ variety) during the three main growth periods was extracted from high-resolution thermal and multispectral images taken by a complete unmanned aerial vehicle (UAV) system. Canopy-air temperature difference (ΔT) and statistic Crop Water Stress Index (CWSIsi) indicators were constructed based on Tc. Combined experiment data from the field and drought thresholds for the ΔT and CWSIsi indicators for different drought levels at three main growth periods were monitored. The results showed a strong correlation between the Tc extracted using the NDVI-OTSU method and ground-truth temperature, with an R2 value of 0.94. The CWSIsi was more stable than the ΔT index in monitoring the drought level affecting winter wheat. The threshold ranges of the CWSIsi for different drought levels of winter wheat at three main growth periods were as follows: the jointing–heading period, where the threshold ranges for normal, mild drought, moderate drought, and severe drought are <0.30, 0.30–0.42, 0.42–0.48, and >0.48, respectively; the heading–filling period, where the threshold ranges for normal, and mild, moderate, and severe drought are <0.33, 0.33–0.47, 0.44–0.53, and >0.53, respectively; and the filling–maturation period, where the threshold ranges for normal, mild drought, moderate drought, and severe drought are <0.41, 0.41–0.54, 0.54–0.59, and >0.59, respectively. The UAV thermal threshold method system can improve the accuracy of crop drought monitoring and has considerable potential in crop drought disaster identification.
Multisource High-Resolution Remote Sensing Image Vegetation Extraction with Comprehensive Multifeature Perception
Authors: Li Yan , Min Songhan , Song Binbin , Yang Hui , Wang Biao , Wu Yongchuang
Published: February 2024

High-resolution remote sensing image-based vegetation monitoring is a hot topic in remote sensing technology and applications. However, when facing large-scale monitoring across different sensors in broad areas, the current methods suffer from fragmentation and weak generalization capabilities. To address this issue, this paper proposes a multisource high-resolution remote sensing image-based vegetation extraction method that considers the comprehensive perception of multiple features. First, this method utilizes a random forest model to perform feature selection for the vegetation index, selecting an index that enhances the otherness between vegetation and other land features. Based on this, a multifeature synthesis perception convolutional network (MSCIN) is constructed, which enhances the extraction of multiscale feature information, global information interaction, and feature cross-fusion. The MSCIN network simultaneously constructs dual-branch parallel networks for spectral features and vegetation index features, strengthening multiscale feature extraction while reducing the loss of detailed features by simplifying the dense connection module. Furthermore, to facilitate global information interaction between the original spectral information and vegetation index features, a dual-path multihead cross-attention fusion module is designed. This module enhances the differentiation of vegetation from other land features and improves the network’s generalization performance, enabling vegetation extraction from multisource high-resolution remote sensing data. To validate the effectiveness of this method, we randomly selected six test areas within Anhui Province and compared the results with three different data sources and other typical methods (NDVI, RFC, OCBDL, and HRNet). The results demonstrate that the MSCIN method proposed in this paper, under the premise of using only GF2 satellite images as samples, exhibits robust accuracy in extraction results across different sensors. It overcomes the rapid degradation of accuracy observed in other methods with various sensors and addresses issues such as internal fragmentation, false positives, and false negatives caused by sample generalization and image diversity.
Examining the Effects of Soil and Water Conservation Measures on Patterns and Magnitudes of Vegetation Cover Change in a Subtropical Region Using Time Series Landsat Imagery
Authors: Sun Xiaoyu , Li Guiying , Wu Qinquan , Li Dengqiu , Lu Dengsheng
Published: February 2024

Soil and water erosion has long been regarded as a serious environmental problem in the world. Thus, research on reducing soil erosion has received continuous attention. Different conservation measures such as restoring low-function forests, closing hillsides for afforestation, planting trees and grass, and constructing terraces on slope land have been implemented for controlling soil erosion problems and promoting vegetation cover change. One important task is to understand the effects of different conservation measures on reducing water and soil erosion problems. However, directly conducting the evaluation of soil erosion reduction is difficult. One solution is to evaluate the patterns and magnitudes of vegetation cover change due to implementing these measures. Therefore, this research selected Changting County, Fujian Province as a case study to examine the effects of implementing conservation measures on vegetation cover change based on time series Landsat images and field survey data. Landsat images between 1986 and 2021 were used to produce time series vegetation cover data using the Google Earth Engine. Sentinel-2 images acquired in 2021 and Landsat images in 2010 were separately used to develop land cover maps using the random forest method. The spatial distribution of different conservation measures was linked to annual vegetation cover and land cover change data to examine the effects on the change in vegetation cover. The results showed a significant reduction in bare lands and increase in pine forests. The vegetation coverage increased from 42% in 1986 to 79% in 2021 in the conservation region compared with an increase from 73% to 87% in the non-conservation region during the same period. Of the different conservation measures, the change magnitude was 0.44 for restoring low-function forests and closing hillsides for afforestation and 0.65 for multiple control measures. This research provides new insights in terms of understanding the effects of taking proper measures for reducing soil and water erosion problems and provides scientific results for decisionmaking for soil erosion controls. The strategy and method used in this research are valuable for other regions in understanding the roles of different conservation measures on vegetation cover change and soil erosion reduction through employing remote sensing technologies.
Lightweight Multilevel Feature-Fusion Network for Built-Up Area Mapping from Gaofen-2 Satellite Images
Authors: Chen Yixiang , Peng Feifei , Yao Shuai , Xie Yuxin
Published: February 2024

The timely, accurate acquisition of geographic spatial information such as the location, scope, and distribution of built-up areas is of great importance for urban planning, management, and decision-making. Due to the diversity of target features and the complexity of spatial layouts, the large-scale mapping of urban built-up areas using high-resolution (HR) satellite imagery still faces considerable challenges. To address this issue, this study adopted a block-based processing strategy and constructed a lightweight multilevel feature-fusion (FF) convolutional neural network for the feature representation and discrimination of built-up areas in HR images. The proposed network consists of three feature extraction modules composed of lightweight convolutions to extract features at different levels, which are further fused sequentially through two attention-based FF modules. Furthermore, to improve the problem of incorrect discrimination and severe jagged boundaries caused by block-based processing, a majority voting method based on a grid offset is adopted to achieve a refined extraction of built-up areas. The effectiveness of this method is evaluated using Gaofen-2 satellite image data covering Shenzhen, China. Compared with several state-of-the-art algorithms for detecting built-up areas, the proposed method achieves a higher detection accuracy and preserves better shape integrity and boundary smoothness in the extracted results.
The Retrieval Relationship between Lightning and Maximum Proxy Reflectivity Based on Random Forest
Authors: Yin Junhong , Tian Liqing , Zhou Kuo , Zhang Weiguang , Ran Lingkun
Published: February 2024

Using the SWAN (Severe Weather Automatic Nowcasting) maximum reflectivity mosaic product and the lightning positioning observations (LPOs) from the ADTD (Advanced Direction and Time of Arrival Detection) system obtained during the 2018–2020 warm season (May to September), adding multi-characteristic LPO parameters in addition to lightning density, the retrieval relationship between lightning and maximum proxy reflectivity, deemed FRST, is constructed by using random forest. The FRST is compared with two empirical relationships from the GSI (Gridpoint Statistical Interpolation) assimilation system, and the results show that the FRST retrieved result better reflects the frequency distribution structure and peak interval of maximum reflectivity. The correlation coefficient between the FRST retrieved result and the observed maximum reflectivity is 0.7037, which is 3.38 (3.12) times greater than that of empirical GSI relationships. The root mean square error and the mean absolute error are 50.85% (28.05%) and 57.15% (35.19%) lower than those for the empirical GSI relationships, respectively. The equitable threat score (ETS) and bias score (BIAS) for FRST are better than those of the empirical GSI relationships in all three maximum reflectivity intervals.
Enhanced Graph Structure Representation for Unsupervised Heterogeneous Change Detection
Authors: Tang Yuqi , Yang Xin , Han Te , Zhang Fangyan , Zou Bin , Feng Huihui
Published: February 2024

Heterogeneous change detection (CD) is widely applied in various fields such as urban planning, environmental monitoring, and disaster management. It enhances the accuracy and comprehensiveness of surface change monitoring by integrating multi-sensor remote sensing data. Scholars have proposed many graph-based methods to address the issue of incomparable heterogeneous images caused by imaging differences. However, these methods often overlook the influence of changes in vertex status on the graph structure, which limits their ability to represent image structural features. To tackle this problem, this paper presents an unsupervised heterogeneous CD method based on enhanced graph structure representation (EGSR). This method enhances the representation capacity of the graph structure for image structural features by measuring the unchanged probabilities of vertices, thereby making it easier to detect changes in heterogeneous images. Firstly, we construct the graph structure using image superpixels and measure the structural graph differences of heterogeneous images in the same image domain. Then, we calculate the unchanged probability of each vertex in the structural graph and reconstruct the graph structure using this probability. To accurately represent the graph structure, we adopt an iterative framework for enhancing the representation of the graph structure. Finally, at the end of the iteration, the final change map (CM) is obtained by binary segmentation of the graph vertices based on their unchanged probabilities. The effectiveness of this method is validated through experiments on four sets of heterogeneous image datasets and two sets of homogeneous image datasets.
Research on Methods to Improve Length of Day Precision by Combining with Effective Angular Momentum
Authors: Li Xishun , Yang Xuhai , Ye Renyin , Cheng Xuan , Zhang Shougang
Published: February 2024

Due to the high correlation between Effective Angular Momentum (EAM) and Length of Day (LOD) data, and the wide application of LOD prediction, this study proposes to combine EAM data with Global Navigation Satellite System (GNSS) LOD data to obtain a more accurate LOD series and attempt to provide a reasonable formal error for the EAM dataset. Firstly, tidal corrections are applied to the LOD data. A first-order difference method is proposed to identify outliers in GNSS LODR (tidal corrected LOD) data, and the EAM data are converted into LODR data using the Liouville equation. Then, the residual term and the fitted term are obtained by least squares fitting. Finally, the fitted residual terms of GNSS LODR and EAM LODR are combined by using the Kalman combination method. In this study, EAM data from the German Research Centre for Geosciences (GFZ) (2019–2022), as well as LOD data from Wuhan University (WHU) and Jet Propulsion Laboratory (JPL), are used for the Kalman combination algorithm experiment. In the Kalman combination, we consider weighted combination based on formal error. However, none of the computing centers provide an uncertainty estimation for the EAM dataset. Therefore, we simulate the combination experiment of LOD and EAM with formal error ranging from 0 to 100 us. The experiment shows that using reasonable formal error for the EAM dataset can improve the accuracy of LOD. Finally, when the formal error of EAM is 2–5 times that of the GNSS LOD formal error, i.e., the EAM formal error is between 10 and 30 us, the accuracy of the combined LOD can be improved by 10–20%.
A Bidirectional Scoring Strategy-Based Transformation Matrix Estimation of Dynamic Factors in Environmental Sensing
Authors: Wang Bo , Cheng Xina , Wang Jialiang , Jiao Licheng
Published: February 2024

Simultaneous localization and mapping (SLAM) is the technological basis of environmental sensing, and it has been widely applied to autonomous navigation. In combination with deep learning methods, dynamic SLAM algorithms have emerged to provide a certain stability and accuracy in dynamic scenes. However, the robustness and accuracy of existing dynamic SLAM algorithms are relatively low in dynamic scenes, and their performance is affected by potential dynamic objects and fast-moving dynamic objects. To solve the positioning interference caused by these dynamic objects, this study proposes a geometric constraint algorithm that utilizes a bidirectional scoring strategy for the estimation of a transformation matrix. First, a geometric constraint function is defined according to the Euclidean distance between corresponding feature points and the average distance of the corresponding edges. This function serves as the basis for determining abnormal scores for feature points. By utilizing these abnormal score values, the system can identify and eliminate highly dynamic feature points. Then, a transformation matrix estimation based on the filtered feature points is adopted to remove more outliers, and a function for evaluating the similarity of key points in two images is optimized during this process. Experiments were performed based on the TUM dynamic target dataset and Bonn RGB-D dynamic dataset, and the results showed that the added dynamic detection method effectively improved the performance compared to state of the art in highly dynamic scenarios.
Glacial Lake Changes and Risk Assessment in Rongxer Watershed of China–Nepal Economic Corridor
Authors: Zhang Sihui , Nie Yong , Zhang Huayu
Published: February 2024

Glacial lake outburst floods (GLOFs) are one of the most severe disasters in alpine regions, releasing a large amount of water and sediment that can cause fatalities and economic loss as well as substantial damage to downstream infrastructures. The risk of GLOFs in the Himalayas is exacerbated by glacier retreat caused by global warming. Critical economic corridors, such as the Rongxer Watershed, are threatened by GLOFs, but the lack of risk assessment specific to the watershed hinders hazard prevention. In this study, we propose a novel model to evaluate the risk of GLOF using a combination of remote sensing observations, GIS, and hydrological models and apply this model to the GLOF risk assessment in the Rongxer Watershed. The results show that (1) the area of glacial lakes in the Rongxer Watershed increased by 31.19% from 11.35 km2 in 1990 to 14.89 km2 in 2020, and (2) 18 lakes were identified as potentially dangerous glacial lakes (PDGLs) that need to be assessed for the GLOF risk, and two of them were categorized as very high risk (Niangzongmajue and Tsho Rolpa). The proposed model was robust in a GLOF risk evaluation by historical GLOFs in the Himalayas. The glacial lake data and GLOF risk assessment model of this study have the potential to be widely used in research on the relationships between glacial lakes and climate change, as well as in disaster mitigation of GLOFs.
Detection Method and Application of Nuclear-Shaped Anomaly Areas in Spatial Electric Field Power Spectrum Images
Authors: Li Xingsu , Li Zhong , Huang Jianping , Yang Xuming , Li Wenjing , Huo Yumeng , Song Junjie , Yang Ruiqi
Published: February 2024

It is found that there are some anomalous high-energy nuclear-shaped regions in the VLF frequency band of the space electric field. To detect and statistically analyze these nuclear-shaped anomaly areas, this paper proposes a nuclear-shaped anomaly area detection method based on the electric field power spectrum image data of the China Seismo Electromagnetic Satellite (CSES-01). First, the logarithm of VLF frequency band data was calculated and rotated counterclockwise to create power spectrum images and label them to form a sample image dataset; then, images were enhanced (which involved resizing, scaling, rotation, gaussian denoising, etc.) to solve the problems of the model overfitting and sample imbalance. Finally, the U-net network model based on the ResNet50 encoder was trained to obtain the optimal kernel anomaly detection model ResNet50_Unet. Comparative experiments with various semantic segmentation algorithms show that the ResNet50_Unet model has the best performance. Applying this model to detect the electric field power spectrum images from November 2021 to February 2022, a total of 101 nuclear-shaped anomaly areas were found, distributed between 45° and 70° of the north–south latitude. This model can quickly detect nuclear-shaped anomaly regions from massive data, providing reference significance for the detection of other types of ionospheric spatial disturbances. At the same time, it has important scientific significance and practical value for understanding the ionosphere and space communication.
Use of Images Obtained by Remotely Piloted Aircraft and Random Forest for the Detection of Leaf Miner (Leucoptera coffeella) in Newly Planted Coffee Trees
Authors: dos Santos Luana Mendes , Ferraz Gabriel Araújo e Silva , Bento Nicole Lopes , Marin Diego Bedin , Rossi Giuseppe , Bambi Gianluca , Conti Leonardo
Published: February 2024

Brazil is the largest producer and exporter of coffee beans in the world. Given this relevance, it is important to monitor the crop to prevent attacks by pests. This study aimed to detect leaf miner (Leucoptera coffeella) infestation in a newly planted crop based on vegetation indices (VI) derived from aerial images obtained by a multispectral camera embedded in a remotely piloted aircraft (RPA) using random forest (RF). The study was conducted on the Cafua farm in the municipality of Lavras in southern Minas Gerais. The images were collected using a multispectral camera attached to a remotely piloted aircraft (RPA). Collections were carried out on 30 July 2019 (infested crop) and 16 December 2019 (post chemical control). The RF package in R software was used to classify the infested and healthy plants. The t test revealed significant differences in band means between healthy and infested plants, favouring higher means in healthy plants. VI also exhibited significant differences, with EXR being higher in infested plants and GNDVI, GOSAVI, GRRI, MPRI, NDI, NDRE, NDVI and SAVI showing higher averages in healthy plants, indicating distinct spectral responses and light absorption patterns between the two states of the plant. Due to the spectral differences between the classes, it was possible to classify the infested and healthy plants, and the RF algorithm performed very well.