bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Prediction Method Based on Bi-Channel Hierarchical Vision Transformer for Rolling Bearings’ Remaining Useful Life
Authors: Hao Wei , Li Zhixuan , Qin Guohao , Ding Kun , Lai Xuwei , Zhang Kai
Published: April 2023

Accurate prediction of the remaining useful life (RUL) of rolling bearings can effectively ensure the safety of complicated machinery and equipment in service. However, the diversity of rolling bearing degradation processes makes it difficult for deep learning-based RUL prediction methods to improve prediction accuracy further and provide generalizability for engineering applications. This study proposed a novelty RUL prediction model for rolling bearings based on a bi-channel hierarchical vision transformer to reduce the impact of the above problems on prediction accuracy improvement. Firstly, hierarchical vision transformer network structures based on different-sized patches were employed to extract depth features containing more degradation processes information from input samples. Second, the dual channel fusion method is implemented into classic RUL prediction networks based on a multi-layer fully connected network to improve prediction accuracy. With two distinct validation experimental arrangements utilizing the datasets from PHM 2012, the prediction accuracy of the proposed approach can be increased by up to 9.43% and 43.10%, respectively, compared with the current standard method. The results demonstrate that the proposed method is more suitable for rolling bearing RUL prediction.
Investigation of the Factors That Contribute to Fresh Fruit and Vegetable Losses in the Australian Fresh Food Supply Chain
Authors: Sanad Alsbu Reham Abdullah , Yarlagadda Prasad , Karim Azharul
Published: April 2023

Fruit and vegetables (FV) are the major source of bioactive compounds for human beings. FV supply chains are complex and sensitive due to various features, including the seasonality of products, variations in demand, and short shelf-lives. The amount of waste in FV supply chains is significant compared with other supply chains as 44% of fresh FV produced globally are wasted in the food chain. This large amount of waste has a significant impact on the economy, food security, available natural resources, and the environment. To reduce food losses in the fresh food supply chain (FFSC), the root causes of waste must be first identified. While a number of researchers have investigated food losses in Australia, most only consider a specific stage in the supply chain and multiple stages in the FFSC are often overlooked. Additionally, the impact of advanced storage technologies, packing, handling, and transport on food losses should be investigated. Furthermore, supply chain practices are changing in response to uncertainties, such as the pandemic and climate changes, which also need to be captured. This research aims to identify the key factors contributing to fresh fruit and vegetable losses through a comprehensive empirical study. Primary data were collected through a well-designed questionnaire-based survey targeting major stakeholders in the FFSC, including farmers, distributors, and retailers in Australia. The survey investigates current postharvest practices and the effects of these practices on food losses. The main factors influencing food losses were identified and the options to reduce these losses were outlined. The results showed that losses mostly occurred at the farm level, and picking practices and preharvest conditions largely contributed to FV losses. The results highlight the need for proper training and education for workers involved in harvesting and handling fresh produce.
Improvement of Relative DEM Time Step Range in Fast Fluidization Simulation of Type-A FCC Particles
Authors: Wu Guorong , Li Yanggui , Israr Muhammad
Published: April 2023

In many process engineering fields, gas-particle fluidized beds are widely used. In fluidized bed research, the discrete element method, or DEM, has been a powerful tool for design and operation purposes. However, with the use of Type-A powders, fluid catalytic cracking or FCC particles being classical cases, they have hardly been reported in DEM simulations of fast fluidization. This study paid close attention to the suitable selection of a stiffness constant and a DEM time step. To reflect their respective effects and complicated interactions, a so-called relative DEM time step was defined. The drag coefficient was correlated using the energy-minimization multi-scale (EMMS) approach to reasonably calculate the gas–solid interaction. Six representative cases with different relative time step values were chosen to simulate a micro-fluidized bed of Type-A FCC powders. The results showed that DEM employing EMMS-based drag force was able to greatly enlarge the suitable range of relative time steps in a fast fluidization simulation of Type-A powders. In addition, the typical macro flow structures of fast fluidization was successfully captured: axially dilute in the top and dense in the bottom, and radially dilute in the core and dense near the wall. Moreover, the distinct gas–solid backmixing, which is considered one of the most important pieces of evidence for the determination of fast fluidization regimes, was modeled. It was indicated that the EMMS-based drag model attenuated the overestimated drag force so that the soft-sphere contact model would be able to more appropriately deal with particle collision, and thus improve the suitable relative DEM time step range.
Power and Energy Management Strategies for a Microgrid with the Presence of Electric Vehicles and CAES Considering the Uncertainty of Resources
Authors: Doosti Reza , Rezazadeh Alireza , Sedighizadeh Mostafa
Published: April 2023

We are witnessing the growth of microgrid technology and the development of electric vehicles (EVs) in the world. These microgrids seek demand response (DR) and energy storage for better management of their resources. In this research, microgrids, including wind turbines, photovoltaics, battery charging/discharging, and compressed air energy storage (CAES), are considered. We will consider two scenarios under uncertainty: (a) planning a microgrid and DR without considering CAES, and (b) planning a microgrid and DR considering CAES. The cost of charging the battery in the second study decreased by $0.66 compared to the first study. The battery is charged with a difference of $0.7 compared to the case of the first study. We will also pay for unsupplied energy and excess energy in this microgrid. Then, we test the scheduling of vehicles to the grid (V2G) in the IEEE 33-bus network. The first framework for increasing network flexibility is the use of EVs as active loads. The scheduling of vehicles in the IEEE 33-bus network is simulated. Every hour, plug-in hybrid electric vehicle (PHEV) charging and discharging, active power loss, and cost will be compared with IHS and PSO algorithms. The difference obtained using the IHS algorithm compared to the PSO algorithm is 1.002 MW and the voltage difference is 9.14 pu.
Ecospirituality in French-Speaking Europe: Linking Ecological Thought with Alternative Spirituality
Authors: Itel Julia
Published: April 2023

Contemporary ecospirituality is built on a double articulation between ecology (science) and spirituality (religion) and can be intertwined with practices and beliefs stemming from neopaganism and, more broadly, an animist vision. The study presented here is anchored in social anthropology, which adds an important empirical dimension that is often underrepresented within the contemporary debates of ecospirituality and the philosophical approaches to science and religion. I therefore propose to begin by describing the methodology I am using. Then, I will outline the sociological (and historical) roots of ecospirituality. Thirdly, I will present the main different currents that make up ecospirituality. Finally, I will end this article by exposing the different types of knowledge produced by ecospiritual actors, reconciling intuitive knowledge and rational knowledge.
Where the Spirit Meets the Bone: Embodied Religiospiritual Cognition from an Attachment Viewpoint
Authors: Winter Anja L. , Granqvist Pehr
Published: April 2023

In this conceptual paper, we suggest that attachment theory is a viable framework for understanding key aspects of embodied religious and spiritual cognition, as seen in religious and spiritual metaphors, rituals, anthropomorphisms, and more. We also discuss embodied cognition as part of mystical experiences and other altered states of consciousness that may occur both within and outside of religious contexts. Therefore, religiospiritual cognition is introduced as an alternative term to religious cognition. We review the basic tenets of attachment theory and conceptually link embodied religiospiritual cognition to attachment-related processes. Finally, we conclude with directions for future research on embodied religiospiritual cognition from an attachment viewpoint. The field of psychedelic science may be especially promising for examining links between attachment and embodied religiospiritual cognition.
Category Mistake 101: The Idea of the Desocialising University and the Last Intellectual
Authors: McDowell John C.
Published: April 2023

A considerable and growing body of literature has engaged in a critical reading of the nature and substance of shifts in not only the business practices, but the conditions for the very raison d’ėtre or telic identifiability of universities under current strategic political arrangements. Moving beyond the practices of academic economy in the business of higher education that reduce the intellectual worker to academic labourer enduring multiple forms of alienation, the paper considers what kind of critical setting there may be for reimagining the university in non-nostalgic ways. While the paper takes its cues pre-eminently from the Australian Higher Education Provider sector, it draws on the overlapping political theorising particularly from the N. American critics Wendy Brown and Henry Giroux. From their critiques of neoliberalism, the paper argues that asking what universities are for does not fare well when higher education institutions are subjected to neoliberal rationality.
The Reactions of Orthodox Churches to Russia’s Aggression towards Ukraine in the Light of the Postsecular Approach to IR Studies
Authors: Solarz Anna M. , Korniichuk Iuliia
Published: April 2023

Russia’s war against Ukraine, in which the aggressor has been making use of religion, including theological rhetoric, to achieve its aims, has sparked reactions from Orthodox Churches all over the world. This has led to a revitalisation of social teaching, including discussions on war and peace within the Orthodox tradition. This may well become a further impetus for more in-depth research on religion and international relations, and possibly for more reappraisals of the secular identity of IR studies. An analysis of the attitudes of Orthodox Churches towards this war indicated that the authority of the Russian Orthodox Church, which considers itself the most important centre of Orthodox culture and civilisation, is waning. The reaction of other local churches showed that it is difficult to recognise the Russian Orthodox Church as such an authority. These revaluations may have a significant impact on Russia’s place in the new international order, although much depends on the final outcome of the war it has started. We explain the different reactions of the churches, and we refer to the social teaching(s) on war of the Russian Church and the Ecumenical Patriarchate according to their official synodal documents. In this teaching, we can see two different approaches—Russian and Constantinopolitan. In the world of the Orthodox tradition, the former, whose practical expression was the atrocities committed during the ongoing war, seems to be rejected in favour of the latter, Constantinople. Finally, there is the question of how the reaction of the Orthodox Churches (analysed below), which have clashed with secularism in a different manner than the Western Churches, might contribute to the development of a postsecular awareness and, consequently, a postsecular identity for IR studies.
The Formation of Biaoquan and Zhequan as a Pair of Philosophical Concepts in Chinese Buddhism
Authors: Wang Junqi
Published: April 2023

The general consensus in the field of Buddhist studies is that the terms “biaoquan” and “zhequan” are a pair of Buddhist philosophical concepts often used to designate two diametrically opposed forms of rhetoric. The former term constitutes its affirmative statement, while the latter defines a fact in negative terms—known in Christian theology as cataphatic and apophatic uses of language, respectively. Looking at the terms for which biaoquan and zhequan initially served as translations, especially in Xuanzang’s works, it would seem that these two concepts have not always appeared as a related pair representing the above-mentioned affirmative–negative dichotomy. The former could designate both affirmation (*vidhi) as well as the general activity of speech, syllables, and words (nāma). In the case of zhequan, it corresponds, in different texts, to the three Indian Buddhist concepts of negation (*pratiṣedha, *vyāvṛtti, *nivṛtti), implicative negation (paryudāsa), and exclusion of others (anyāpoha), with each use of the term “zhequan” carrying a different set of meanings and associated doctrines. Indeed, in various texts, the concept of zhequan might be opposed to the concept of biaoquan (*vidhi *sadhana) or opposed to pure negation (prasajya), or it might be applied on its own with no opposing concept. However, as Chinese Buddhism continued to develop throughout the Tang, biaoquan and zhequan came to be firmly associated and popularized as a pair of opposites. Looking at the doctrinal as well as the translation history of these two terms, this paper focuses on how they were used as a pair of opposing philosophical concepts, followed by an analysis of the profound influence of these two concepts on Chinese Buddhism.
The International Discourse on Ecumenical Diaconia as a Chance to Strengthen the Specific Profile and Potential of Churches as Actors of Eco-Social Transformation—A German Perspective
Authors: Werner Dietrich
Published: April 2023

There has always been a conviction in the ecumenical movement that social service is part of the essence of what it means to be the church. The strengthening of social and political witness of churches through church-related agencies and networks in the context of the beginning development discourse from the 1960s until the 1990s, however, led to a scenario in which the secular language of development and political action received much attention. In 2014 at the Malawi consultation, the World Council of Churches (WCC) and Action of Churches Together (ACT Alliance) reviewed their working relationships and explored better collaboration between agencies and churches, stating that the specific nature of churches as entities with an added value and particular profile in the area of social and political service would be strengthened. From this consultation, a mandate was given by the WCC Central Committee to develop a study document on the understanding and core components of the concept of “ecumenical diaconia”, which then was made available to the 11th Assembly of the WCC in Karlsruhe, 2022. This article introduces the context, major content, and key convictions of this study document and related discussions in Karlsruhe. It answers the question: what is the significance of the global ecumenical fellowship of churches in focusing on a common language of diaconia and a more explicit church-related terminology to describe and strengthen the social services of churches and their engagement in diaconia and social witness? It is recognized that this article is predominantly written from a German context and perspective in its construction of the international discourse on ecumenical diaconia.
High-Temperature Oxidation of Magnesium- and Iron-Rich Olivine under a CO2 Atmosphere: Implications for Venus
Authors: Zhong Shan-Shan , Zhao Yu-Yan Sara , Lin Honglei , Chang Rui , Qi Chao , Wang Junhu , Mo Bing , Wen Yuanyun , Yu Wen , Zhou Di-Sheng , Yu Xiao-Wen , Li Xiongyao , Liu Jianzhong
Published: April 2023

Understanding crust–atmosphere interactions on Venus is fundamentally important to interpretations of Venus’ surface spectroscopic data. Olivine, in basaltic crust, is oxidized under a heated CO2 atmosphere. However, the oxidation rates, product assemblages and spectral characteristics of olivine samples with different Fa# values remain largely unclear. Herein, we investigated the oxidation of olivine with different Fa# values (Fa09, Fa29 and Fa71) under CO2 atmosphere at 470 °C and 900 °C and characterized the oxidation products (both microscopically and macroscopically), conversion rates and VNIR spectra. The results showed that the oxidation of olivine produced magnesioferrite, magnetite, laihunite, hematite and maghemite at 470 °C and hematite, magnetite, magnesioferrite and amorphous SiO2 at 900 °C. Both high temperature and high Fa# values accelerated the oxidation rates. The production of oxide coatings on olivine grains (74 μm in size) was estimated to be completed within tens to hundreds of years at 470 °C in natural settings, with even shorter periods under higher temperatures. Thus, CO2 oxidation would quickly eliminate olivine spectral characteristics, and spectral parameters at 850 and 1020 nm, as well as other relevant spectral windows (considering shifts induced by the elevated temperature), could be used to trace olivine oxidation processes. This work presented a case study connecting microscopic features to spectral characteristics for Venus’ surface–atmosphere interactions. Further studies considering more realistic Venus’ surface–atmosphere conditions will be essential to better interpret the measured spectroscopic data and determine the origins of the high emissivity detected on elevated terrain on Venus.
A Remote Sensing and GIS Analysis of Rockfall Distributions from the 5 July 2019 Ridgecrest (MW7.1) and 24 June 2020 Owens Lake (MW5.8) Earthquakes
Authors: Scuderi Louis A. , Onyango Evans A. , Nagle-McNaughton Timothy
Published: April 2023

We examine the coseismic influence of the 5 July 2019, MW7.1 Ridgecrest and the 24 June 2020 MW5.8 Owens Lake earthquakes on rockfall distributions in two undisturbed high-altitude areas of the southern Sierra Nevada Mountains, California, USA. These events occurred within the geologically recent (<2 Mya) Walker Lane/eastern California shear zone. While both study areas are characterized as plutonic, the Owens Lake event largely affected terrain that was formerly glaciated and oversteepened while the Ridgecrest event affected non-glaciated terrain. Our inventory of rockfall locations was derived from analysis of Sentinel-2 images acquired just prior to and immediately after the events. This difference mapping approach using readily-available Sentinel-2 imagery allows for rapid rockfall and landslide mapping. GIS analysis shows that even though the total area assessed for both earthquakes was similar (~1500 km2), the significantly lower magnitude Owens Lake event produced nearly twice as many (102) mappable rockslides as the significantly stronger Ridgecrest event (58), a difference likely due to slope oversteepening in the formerly glaciated area. Significant seismic amplification by topography and reactivation of preexisting failures was apparent for both areas. Inclusion of these factors may improve failure predictions and rockfall probability estimation.
Application of YOLOv5 for Point Label Based Object Detection of Black Pine Trees with Vitality Losses in UAV Data
Authors: Hofinger Peter , Klemmt Hans-Joachim , Ecke Simon , Rogg Steffen , Dempewolf Jan
Published: April 2023

Monitoring tree diseases in forests is crucial for managing pathogens, particularly as climate change and globalization lead to the emergence and spread of tree diseases. Object detection algorithms for monitoring tree diseases through remote sensing rely on bounding boxes to represent trees. However, this approach may not be the most efficient. Our study proposed a solution to this challenge by applying object detection to unmanned aerial vehicle (UAV)-based imagery, using point labels that were converted into equally sized square bounding boxes. This allowed for effective and extensive monitoring of black pine (Pinus nigra L.) trees with vitality-related damages. To achieve this, we used the “You Only Look Once’’ version 5 (YOLOv5) deep learning algorithm for object detection, alongside a 16 by 16 intersection over union (IOU) and confidence threshold grid search, and five-fold cross-validation. Our dataset used for training and evaluating the YOLOv5 models consisted of 179 images, containing a total of 2374 labeled trees. Our experiments revealed that, for achieving the best results, the constant bounding box size should cover at least the center half of the tree canopy. Moreover, we found that YOLOv5s was the optimal model architecture. Our final model achieved competitive results for detecting damaged black pines, with a 95% confidence interval of the F1 score of 67–77%. These results can possibly be improved by incorporating more data, which is less effort-intensive due to the use of point labels. Additionally, there is potential for advancements in the method of converting points to bounding boxes by utilizing more sophisticated algorithms, providing an opportunity for further research. Overall, this study presents an efficient method for monitoring forest health at the single tree level, using point labels on UAV-based imagery with a deep learning object detection algorithm.
Water Temperature Reconstruction via Station Position Correction Method Based on Coastal Acoustic Tomography Systems
Authors: Xu Pan , Xu Shijie , Yu Fenyuan , Gao Yixin , Li Guangming , Hu Zhengliang , Huang Haocai
Published: April 2023

Underwater acoustic tomography is an advanced technology in water environment observation. Sound propagation duration between transceivers is used for underwater parameter distribution profile reconstruction in the inverse problem. The key points of acoustic tomography are accurate station distance and time synchronization. Two methods are introduced in this study for sound station position correction. The direct signal transmission correction (DSC) method corrects the multi-peak (expect direct ray) travel time via the travel time difference between different sound rays and reference direct ray. The ray-model position correction (RMC) method calculates exact station position by the station drift distance obtained from transceiver depth variations to correct direct ray travel time; the other multi-peak travel time is revised by the corrected direct ray travel time. A water temperature observation experiment was carried out in a reservoir using coastal acoustic tomography (CAT) systems to verify the flexibility of these two methods. Multi-ray arrival peaks are corrected using DSC and RMC methods; water temperature inversion results in a 2D vertical profile are obtained. The reliability of the method is proved by comparison with temperature depth sensor (TD) data. The methods improve the quality of initial data and can be attempted for further water environment observation in acoustic tomography observation studies.
Stratospheric Temperature Observations by Narrow Bands Ultra-High Spectral Resolution Sounder from Nadir-Viewing Satellites
Authors: Wang Sufeng , Feng Yutao , Fu Di , Kong Liang , Li Hongbo , Han Bin , Lu Feng
Published: April 2023

Accurate stratospheric temperature observations are crucial for weather forecasts and climate change studies. This paper discusses a precise measurement method for the stratospheric temperature profile using narrow bands with ultra-high spectral resolution from nadir-viewing satellites. First, the CO2 absorption band around 15 μm is selected as the major sounding source by the calculation and analysis of the temperature Jacobian and the atmospheric molecular spectra. Next, the influence of spectral resolution, spectral range and instrumental noise on the sounding capability is analyzed, and the sounding feasibility of the single spectral band and multiple spectral bands is discussed under the condition that the spaceborne long-wave infrared space heterodyne spectrometer (SHS) is selected as suggested sounder onboard the satellite. Finally, the optimal joint-sounding scheme of narrow bands is proposed. The temperature retrieval and validation show that the joint-sounding of two discontinuous narrow bands can realize the high precision measurement of the stratospheric temperature profile for the given spectral resolution, spectral range, and instrumental noise. When the sounder adopts two narrow bands (the regions of 666.87–676.44 cm−1 and 683.58–693.15 cm−1) and a spectral resolution of 0.03 cm−1, the retrieval accuracy (RMSE) is about 0.9 K over a pressure range of 200 to 0.7 hPa (11.5–50 km). This study will provide technical preparation for high-precision and low-cost satellite sounder design for stratospheric temperature observations.
Panoptic SwiftNet: Pyramidal Fusion for Real-Time Panoptic Segmentation
Authors: Šarić Josip , Oršić Marin , Šegvić Siniša
Published: April 2023

Dense panoptic prediction is a key ingredient in many existing applications such as autonomous driving, automated warehouses, or remote sensing. Many of these applications require fast inference over large input resolutions on affordable or even embedded hardware. We proposed to achieve this goal by trading off backbone capacity for multi-scale feature extraction. In comparison with contemporaneous approaches to panoptic segmentation, the main novelties of our method are efficient scale-equivariant feature extraction, cross-scale upsampling through pyramidal fusion and boundary-aware learning of pixel-to-instance assignment. The proposed method is very well suited for remote sensing imagery due to the huge number of pixels in typical city-wide and region-wide datasets. We present panoptic experiments on Cityscapes, Vistas, COCO, and the BSB-Aerial dataset. Our models outperformed the state-of-the-art on the BSB-Aerial dataset while being able to process more than a hundred 1MPx images per second on an RTX3090 GPU with FP16 precision and TensorRT optimization.
Hyperspectral Denoising Using Asymmetric Noise Modeling Deep Image Prior
Authors: Wang Yifan , Xu Shuang , Cao Xiangyong , Ke Qiao , Ji Teng-Yu , Zhu Xiangxiang
Published: April 2023

Deep image prior (DIP) is a powerful technique for image restoration that leverages an untrained network as a handcrafted prior. DIP can also be used for hyperspectral image (HSI) denoising tasks and has achieved impressive performance. Recent works further incorporate different regularization terms to enhance the performance of DIP and successfully show notable improvements. However, most DIP-based methods for HSI denoising rarely consider the distribution of complicated HSI mixed noise. In this paper, we propose the asymmetric Laplace noise modeling deep image prior (ALDIP) for HSI mixed noise removal. Based on the observation that real-world HSI noise exhibits heavy-tailed and asymmetric properties, we model the HSI noise of each band using an asymmetric Laplace distribution. Furthermore, in order to fully exploit the spatial–spectral correlation, we propose ALDIP-SSTV, which combines ALDIP with a spatial–spectral total variation (SSTV) term to preserve more spatial–spectral information. Experiments on both synthetic data and real-world data demonstrate that ALDIP and ALDIP-SSTV outperform state-of-the-art HSI denoising methods.
Mapping Forage Biomass and Quality of the Inner Mongolia Grasslands by Combining Field Measurements and Sentinel-2 Observations
Authors: Zhao Xia , Wu Bo , Xue Jinxin , Shi Yue , Zhao Mengying , Geng Xiaoqing , Yan Zhengbing , Shen Haihua , Fang Jingyun
Published: April 2023

Grasslands provide essential forage sources for global livestock production. Remote sensing approaches have been widely used to estimate the biomass production of grasslands from regional to global scales, but simultaneously mapping the forage biomass and quality metrics (e.g., crude fiber and crude protein) is still relatively lacking despite an increasing need for better livestock management. We conducted novel gradient grass-cutting experiments and measured hyperspectral reflectance, forage biomass, crude fiber per area (CFarea), and crude protein per area (CParea) across 19 temperate grassland sites in the Xilingol region, Inner Mongolia, China. Based on these measurements, we identified sensitive spectral bands, calculated nine potential spectral indices (Normalized Difference Vegetation Index, Enhanced Vegetation Index, Red Edge Normalized Difference Vegetation Index, Red-Edge Inflection Point, Inverted Red-Edge Chlorophyll Index algorithm, Normalized Difference Red Edge Index, Nitrogen Reflectance Index, Normalized Greenness Index, Land Surface Water Index) and established Random Forest (RF) models that well predicted forage biomass (R2 = 0.67, NRMSE = 12%), CFarea (R2 = 0.59, NRMSE = 14%), and CParea (R2 = 0.77, NRMSE = 10%). Among these nine indices, Land Surface Water Index (LSWI, calculated by R785-900 and R2100-2280) was identified to be the most important predictor and was then used to establish empirical power law models, showing comparable prediction accuracies (forage biomass, R2 = 0.53; NRMSE = 14%; CFarea, R2 = 0.40, NRMSE = 17%; CParea, R2 = 0.72, NRMSE = 11%) in comparison to Random Forest models. Combining the empirical power law models with the LSWI calculated from Sentinel-2 observations, we further mapped the forage biomass and quality and estimated the livestock carrying capacity. The predicted forage biomass, CFarea, and CParea all showed a significant increase with higher mean annual precipitation, but showed no significant correlations with mean annual temperature. Compared with the estimates based on crude protein, the conventional approach solely based on forage biomass consistently overestimated livestock carrying capacity, especially in wetter areas. Our work provides an approach to simultaneously map the forage biomass and quality metrics and recommends a LSWI-based power law model for rapid and low-cost assessment of regional forage status to guide better livestock management.
Research on Cotton Field Irrigation Amount Calculation Based on Electromagnetic Induction Technology
Authors: Han Jianwen , Wang Mingyue , Wang Nan , Wang Jiawen , Peng Jie , Feng Chunhui
Published: April 2023

The rapid and efficient acquisition of field-scale farmland soil profile moisture-distribution information is very important for achieving precise irrigation and the adjustment and deployment of irrigation strategies in farmland. EM38-MK2 is a portable, non-invasive device that induces electric currents in soil to generate secondary magnetic fields for the rapid measurement of apparent electrical conductivity in the field. In this study, cotton fields were used as experimental objects to obtain soil apparent conductivity data for three periods, which were combined with soil-moisture content data collected simultaneously from soil samples and measured in the laboratory to construct an apparent soil-profile moisture regression model. A simple kriging interpolation method was used to map the distribution of the irrigation volume in the field, considering only the highest irrigation volume in the field as the maximum water-holding capacity in the field. The results showed that EM38 could accurately detect the spatial variation of soil moisture in the field. The R2 of the linear fit between measured and predicted soil-water content ranged from 0.51 to 0.89; the RMSE ranged from 0.66 to 1.87; and the R2 and RPD of each soil-layer water content model of the single-period model were higher than those of the full-period model. By plotting the distribution of field irrigation, it could be seen that by comparing the predicted field irrigation with the actual irrigation, at least 160 m3 ha−1 of irrigation could be saved in all three periods at an irrigation depth of 40 cm, which is about 30% of the actual irrigation; at an irrigation depth of 60 cm, about 30% and 15% of irrigation could be reduced in July and August, respectively. There are three areas in the study area with high fixed-irrigation volumes located in the northwest corner, near 500 m in the northern half of the study area and 750 m east of the southern half of the study area. The results of this study proved that the use of EM38-MK2 to monitor and evaluate the soil-moisture content of the farmland at different periods can, to a certain extent, guide the irrigation amount needed to achieve efficient and precise irrigation in the field.
Location and Activity Changes of Slow-Moving Landslides Due to an Earthquake: Perspective from InSAR Observations
Authors: He Caihong , Sun Qian , Hu Jun , Gui Rong
Published: April 2023

Strong earthquakes can not only trigger many landslides in a short period of time but can also change the stability of slopes in the earthquake area, causing them to be active for a long time after the earthquake. Research on the variation of slow-motion slopes before and after earthquakes can help us to better understand the mechanism of earthquake-affected landslides, which is also crucial for assessing the long-term landslide risk in seismically active areas. Here, L-band ALOS-2 PALSAR-2 images are utilized with the SBAS-InSAR algorithm to monitor and assess the location and activity changes of slow-moving landslides in the Iburi region (Hokkaido, Japan) before and after an earthquake occurred on 6 September 2018. Unlike previous studies, which focused on single typical landslides, we tracked all the landslides within a 33 × 55 km region close to the epicenter. According to the results, the majority of the co-seismic landslides that quickly failed during the earthquake are now stable, and a few of them are still moving. In contrast, due to near-field seismic shaking, certain slopes that did not show substantial surface changes during the earthquake period continued to move and eventually developed into slow-moving landslides. In addition, it can be seen from the spatial distribution of slow-moving landslides after the earthquake that this distribution is not only dependent on strong earthquake seismic vibration or the hanging-wall effect. Far-field weak vibrations can also accelerate landslides. Additionally, we discovered that the earthquake made the unstable slopes move more quickly but also tended to stabilize the slopes that were already in motion before the earthquake. The various response modes of slow-moving landslides to seismic events are related not only to the intensity of seismic vibration but also to the geological conditions of the region and to the size of the landslide itself. These findings are extremely valuable for studying the mechanism of earthquake-affected landslides.
Quantitative Evaluation of Maize Emergence Using UAV Imagery and Deep Learning
Authors: Liu Minguo , Su Wen-Hao , Wang Xi-Qing
Published: April 2023

Accurate assessment of crop emergence helps breeders select appropriate crop genotypes, and farmers make timely field management decisions to increase maize yields. Crop emergence is conventionally quantified by manual calculations to quantify the number and size of seedlings, which is laborious, inefficient, and unreliable and fails to visualize the spatial distribution and uniformity of seedlings. Phenotyping technology based on remote sensing allows for high-throughput evaluation of crop emergence at the early growth stage. This study developed a system for the rapid estimation of maize seedling emergence based on a deep learning algorithm. The RGB images acquired from an unmanned aerial vehicle (UAV) were used to develop the optimal model for the recognition of seedling location, spacing, and size, and the prediction performance of the system was evaluated in three stations during 2021–2022. A case study was conducted to show the evaluation of the system for maize seedlings and combined with TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) analysis. The results show that the system has good prediction performance for maize seedling count with an average R2 value of 0.96 and an accuracy of 92%; however, shadows and planting density influence its accuracy. The prediction accuracy reduces significantly when the planting density is above 90,000 plants/ha. The distribution characteristics of seedling emergence and growth were also calculated based on the average value and variation coefficient of seedling spacing, seedling area, and seedling length. The estimation accuracies for the average value of seedling spacing, the coefficient of variation of seedling spacing, the average value of the seedling area, the coefficient of variation of the seedling area, and the average value of the seedling length were 87.52, 87.55, 82.69, 84.51, and 90.32%, respectively. In conclusion, the proposed system can quickly analyze the maize seeding growth and uniformity characteristics of experimental plots and locate plots with poor maize emergence.
Problems with and Improvement of HCHO/NO2 for Diagnosing Ozone Sensitivity—A Case in Beijing
Authors: Kang Yanyu , Tang Guiqian , Li Qihua , Liu Baoxian , Yao Dan , Wang Yiming , Wang Yinghong , Wang Yuesi , Liu Wenqing
Published: April 2023

Rfn (formaldehyde/nitrogen dioxide) is a common indicator based on satellite observations used to classify ozone formation sensitivity. However, it may underestimate anthropogenic volatile organic compounds (VOCs) in heavily polluted cities when only formaldehyde (HCHO) is used in Rfn to measure VOCs, since it is mainly derived from natural sources worldwide. In this study, we used multiaxis differential optical absorption spectroscopy to acquire tropospheric observations of nitrogen dioxide (NO2), HCHO and glyoxal (CHOCHO) in Beijing from 1 April 2019 to 31 March 2020. Combined with VOCs detected simultaneously by gas chromatography—mass spectrometry and proton transfer reaction–time-of-flight/mass spectrometry near the ground, we evaluated the representativeness of HCHO column densities on total VOCs (TVOC) in equivalent propylene concentrations, which is called reactivity. The results showed that there were significant seasonal differences in the response of HCHO to TVOC reactivity, with fitting slopes of 2.3 (spring), 2.6 (summer), 2.9 (autumn) and 1.0 (winter) in the four seasons, respectively. Since CHOCHO can be used to partly characterize the contribution of anthropogenic VOC emissions and demonstrated a better response to TVOC reactivity in winter, with fitting slopes of 0.2 (spring), 0.2 (summer), 0.2 (autumn) and 0.5 (winter) in the four seasons, respectively, we introduced CHOCHO to construct a new indicator (HCHO + 6 × CHOCHO). The fitting slopes of the four seasons were more similar, being 3.2 (spring), 3.6 (summer), 4.0 (autumn) and 4.0 (winter). The ratio of the new indicator to NO2, Rmn ((HCHO + 6 × CHOCHO)/NO2), was used to reclassify the ozone formation sensitivity of urban areas in North China, revealing that it is a transition regime before 1300 LST (LST = UST + 8) and an NOx-limited regime afterwards. Rmn improved the sensitivity from the VOC-limited regime to the NOx-limited regime, enhancing the sensitivity of NOx and providing new robust support for ozone pollution prevention and control.
Synergistic Use of Earth Observation Driven Techniques to Support the Implementation of Water Framework Directive in Europe: A Review
Authors: Samarinas Nikiforos , Spiliotopoulos Marios , Tziolas Nikolaos , Loukas Athanasios
Published: April 2023

The development of a sustainable water quality monitoring system at national scale remains a big challenge until today, acting as a hindrance for the efficient implementation of the Water Framework Directive (WFD). This work provides valuable insights into the current state-of-the-art Earth Observation (EO) tools and services, proposing a synergistic use of innovative remote sensing technologies, in situ sensors, and databases, with the ultimate goal to support the European Member States in effective WFD implementation. The proposed approach is based on a recent research and scientific analysis for a six-year period (2017–2022) after reviewing 71 peer-reviewed articles in international journals coupled with the scientific results of 11 European-founded research projects related to EO and WFD. Special focus is placed on the EO data sources (spaceborne, in situ, etc.), the sensors in use, the observed water Quality Elements as well as on the computer science techniques (machine/deep learning, artificial intelligence, etc.). The combination of the different technologies can offer, among other things, low-cost monitoring, an increase in the monitored Quality Elements per water body, and a minimization of the percentage of water bodies with unknown ecological status.
Quantifying the Contribution of Driving Factors on Distribution and Change of Net Primary Productivity of Vegetation in the Mongolian Plateau
Authors: Yin Chaohua , Chen Xiaoqi , Luo Min , Meng Fanhao , Sa Chula , Bao Shanhu , Yuan Zhihui , Zhang Xiang , Bao Yuhai
Published: April 2023

In recent years, multiple disturbances have significantly altered terrestrial ecosystems in arid and semi-arid regions, particularly on the Mongolian Plateau (MP). Net primary productivity (NPP) of vegetation is an essential component of the surface carbon cycle. As such, it characterizes the state of variation in terrestrial ecosystems and reflects the productive capacity of natural vegetation. This study revealed the complex relationship between the natural environment and NPP in the ecologically fragile and sensitive MP. The modified Carnegie–Ames–Stanford Approach (CASA) model was used to simulate vegetation NPP. Further, the contributions of topography, vegetation, soils, and climate to NPP’s distribution and spatiotemporal variation were explored using the geographic detector model (GDM) and structural equation model (SEM). The study’s findings indicate the following: (1) NPPs for different vegetation types in the MP were in the order of broad-leaved forest > meadow steppe > coniferous forest > cropland > shrub > typical steppe > sandy land > alpine steppe > desert steppe. (2) NPP showed an increasing trend during the growing seasons from 2000 to 2019, with forests providing larger vegetation carbon stocks. It also maintained a more stable level of productivity. (3) Vegetation cover, precipitation, soil moisture, and solar radiation were the key factors affecting NPP’s spatial distribution. NPP’s spatial distribution was primarily explained by the normalized difference vegetation index, solar radiation, precipitation, vegetation type, soil moisture, and soil type (-statistics = 0.86, 0.71, 0.67, 0.67, 0.57, and 0.57, respectively); the contribution of temperature was small (-statistics = 0.26), and topographic factors had the least influence on NPP’s distribution, as their contribution amounted to less than 0.20. (4) A SEM constructed based on the normalized difference vegetation index (NDVI), solar radiation, precipitation, temperature, and soil moisture explained 17% to 65% of the MP’s NPP variations. The total effects of the MP’s NPP variations in absolute values were in the order of NDVI (0.47) > precipitation (0.33) > soil moisture (0.16) > temperature (0.14) > solar radiation (0.02), and the mechanisms responsible for NPP variations differed slightly among the relevant vegetation types. Overall, this study can help understand the mechanisms responsible for the MP’s NPP variations and offer a new perspective for regional vegetation ecosystem management.
Accuracy Assessment of the Positioning of a Swarm of Underwater Vehicles in Relation to Four Surface Vehicles Using the TDOA Method
Authors: Naus Krzysztof
Published: April 2023

This paper presents the results of research on the accuracy assessment of the positioning of a swarm of underwater vehicles based on hydroacoustic measurements made with respect to four surface vehicles under the time difference of arrival (TDOA) method. The assessment consisted of the estimation of accuracy parameters for determining the position of an underwater vehicle in relation to surface vehicles forming a so-called moving geometrical measurement structure (MGMS) in the following shapes: square, rectilinear, triangular, and three-pointed. This demonstrated that MGMS makes it possible to estimate the relative position of underwater vehicles in a swarm with an accuracy of 2.1 m (RMS) over an area of approx. 1000 m2 and approx. 3.0 m (RMS) over an area of approx. 1600 m2. The most favourable MGMS shapes include three-pointedwhile maximising the size of the positioning area, where the positioning accuracy should not exceed 3.0 m (RMS)—and rectilinear—while maximising the size of the positioning area, where the positioning accuracy should not exceed 10.0 m (RMS).
Identifying Spatial Variation of Carbon Stock in a Warm Temperate Forest in Central Japan Using Sentinel-2 and Digital Elevation Model Data
Authors: Pei Huiqing , Owari Toshiaki , Tsuyuki Satoshi , Hiroshima Takuya
Published: April 2023

The accurate estimation of carbon stocks in natural and plantation forests is a prerequisite for the realization of carbon peaking and neutrality. In this study, the potential of optical Sentinel-2A data and a digital elevation model (DEM) to estimate the spatial variation of carbon stocks was investigated in a mountainous warm temperate region in central Japan. Four types of image preprocessing techniques and datasets were used: spectral reflectance, DEM-based topography indices, vegetation indices, and spectral band-based textures. A random forest model combined with 103 field plots as well as remote sensing image parameters was applied to predict and map the 2160 ha University of Tokyo Chiba Forest. Structural equation modeling was used to evaluate the factors driving the spatial distribution of forest carbon stocks. Our study shows that the Sentinel-2A data in combination with topography indices, vegetation indices, and shortwave-infrared (SWIR)-band-based textures resulted in the highest estimation accuracy. The spatial distribution of carbon stocks was successfully mapped, and stand-age- and forest-type-level variations were identified. The SWIR-2-band and topography indices were the most important variables for modeling, while the forest stand age and curvature were the most important determinants of the spatial distribution of carbon stock density. These findings will contribute to more accurate mapping of carbon stocks and improved quantification in different forest types and stand ages.
Landslide Identification in Human-Modified Alpine and Canyon Area of the Niulan River Basin Based on SBAS-InSAR and Optical Images
Authors: Yang Shuo , Li Deying , Liu Yujie , Xu Zhihui , Sun Yiqing , She Xiangjie
Published: April 2023

Landslide identification in alpine and canyon areas is difficult due to the terrain limitations. The main objective of this research was to explore the method of combining small baseline subset interferometric synthetic aperture radar (SBAS-InSAR), multi-temporal optical images and field surveys to identify potential landslides in the human-modified alpine and canyon area of the Niulan River in southwestern China based on terrain visibility analysis. The visibility of the terrain is analyzed using the different incident and heading angles of the Sentinel satellite’s ascending and descending orbits. Based on the SAR image data of Sentinel-1A satellites from 2016 to 2019, the SBAS-InSAR method was used to identify landslides, and then multi-temporal optical images were used to facilitate landslide identification. Field surveys were carried out to verify the identification accuracy. A total of 28 landslides were identified, including 13 indicated by SBAS-InSAR, 8 by optical imaging and 7 by field investigation. Many landslides were induced by the impoundment and fluctuation of reservoir water. The comparison and verification of typical landslide monitoring data and reservoir water fluctuations revealed that a sudden drop of reservoir water had a great influence on landslide stability. These research results can facilitate a comprehensive understanding of landslide distribution in the reservoir area and guide the follow-up landslide risk management.