bluuebunny/crossref_metadata_2025 huggingface dataset:
How Not to Object to Demonic Realism
Authors: Guthrie Shandon L.
Published: July 2022

There are few academics today who actively argue against demonic realism. Much of this is perhaps due to the fact that there are comparably few defenders of such. This has created a vacuum for critics to comfortably object to the existence of demons without sophistication (for it is only in the professional exchange of ideas do bad arguments get weeded out and good arguments gain vitality). Add to this the common perception of demonology as an anti-intellectual superstition and we end up with a threshold for the success of anti-realist arguments to be set quite low. In this paper, I shall survey three of the most familiar objections to demonic realism to arise out of this skeptical intellectual environment: First, and most ambitiously, there is the impossibility of justified belief objection that proffers that belief in demons cannot even in principle be justified no matter how much (scientific) evidence there is. Alternative explanations are always to be preferred. Second, there is the demon-of-the-gaps objection (or category of objections) which insists that demonic realism is hastily posited as a pre-scientific explanation for physical, medical, and psychological mysteries. Third, there is what I call the ethical argument from scapegoating that questions the existence of demons on grounds that, if they in fact exist, such a fact would preclude moral responsibility and the possibility of retributive justice since we could never know if a bad actor was himself morally culpable for his own evils or if he was under the coercive influence of demonic agents. I argue that, despite their rhetorical appeal and kinship with the anti-supernatural sentiments of many academics today, these three arguments are not successful, for these are either based on egregious philosophical assumptions or assumptions about demonology few if any adopt.
The Cross in Rūmī’s Maṯnawī
Authors: Mokrani Adnane
Published: July 2022

A cursory reading of Rūmī’s Maṯnawī suggests that the author follows the dominant Qur’ānic interpretation denying Jesus Christ’s Crucifixion. Closer analysis demonstrates, however, that Rūmī interprets the Cross and considers its spiritual significance in a subtle and symbolic way. This study addresses this contradiction by developing a synthesis that clarifies Rūmī’s spiritual anthropology. In the Islamic context, his writing constitutes a significant attempt to understand and interpret the Christian Scriptures and overcome sensitive points of conflict that are considered dividing lines between the faiths.
Attitudes of Polish Young Adults towards the Roman Catholic Church: A Sociological and Pastoral Analysis of Empirical Research among Young Adults and Teachers
Authors: Szymczak Wioletta , Mąkosa Paweł Michał , Adamczyk Tomasz
Published: July 2022

The article provides a sociological and pastoral analysis of a representative empirical study conducted by means of an interview questionnaire among 1003 secondary school students in 2020 and 2021. The analysis was expanded to include data from parallel and similarly designed sociological studies carried out among teachers of religious education in order to obtain a broader view of the research problems and a better understanding of young adults by becoming familiar with the perceptions and opinions of teachers on the analysed issues. The article reflects on and discusses the following issues: personal relationships between young adults and the Church along with their expectations towards the latter, factors considered to persuade young adults to develop their faith and be part of the Church, as well as Church activities and offers regarded by the surveyed subjects as particularly needed. These issues, presented from an interdisciplinary perspective, provide a deeper insight into people’s relations with the Church and allow for diagnosis of their needs and expectations. They also enable identification of the elements and aspects of the functioning of the religious institution, which, in a pluralistic society and the course of the ever-advancing secularisation, requires a profound diagnosis, a thorough analysis and questions about the adequacy of forms and methods of evangelisation, as well as ways of reaching the target audience and the fulfilment of the fundamental religious mission.
“γάλα ἀντὶ αἵματος”—An Unwonted Hagiographic Topos
Authors: Boicu Dragoş
Published: July 2022

Some Christian texts, and especially hagiographic and hymnographic ones, record a miraculous phenomenon at the violent deaths of several martyrs: from the beheaded bodies, milk flows instead of blood. After a superficial reading of the biographical passages in the synaxaria and iambic stichoi recorded in the Menaia, we can identify at least ten such cases, among which we find well-known saints, such as Apostle Paul and St. Katherine. This article attempts to revisit this unwonted topos of Christian literature, and to list its occurrences in the liturgical texts of the Orthodox Church and Acta Sanctorum.
Crisis, Solidarity, and Ritual in Religiously Diverse Settings: A Unitarian Universalist Case Study
Authors: Johnson Sarah Kathleen
Published: July 2022

How can religious ritual foster solidarity in religiously diverse communities in times of crisis? This question is crucial in social contexts characterized by increasing religious and nonreligious diversity and ongoing intersecting crises associated with violence, inequality, and climate change. Solidarity is necessary both as an immediate response to crisis and to the pursuit of long-term solutions that address underlying causes. Situated in the literature on disaster ritual, this study draws on Randall Collins’ sociological theory of interaction ritual chains to analyze the weekly ritual of sharing “Joys and Concerns” followed by a “Meditation” practiced by a theistically diverse Unitarian Universalist congregation. Anchored in one year of ethnographic research in this community, it concludes that the trusted structures, shared stories, and embodied symbols associated with this practice contain the ritual ingredients necessary to produce social solidarity in response to personal and societal crises and may be a model to apply in other religiously diverse contexts.
The Defense of Religious Freedom in the Catholic Magazine Vida Nueva during a Catholic Confessional Dictatorship
Authors: Sánchez-Camacho Jesús
Published: July 2022

After the Second Vatican Council ended in 1965, and during a National Catholic dictatorship in Spain, the religious magazine Vida Nueva tried to support the principles of religious freedom promoted by the conciliar assembly. This study focuses on the promotion of liberties during a regime in which political power was not separated from religious power. The study conducts a quantitative and qualitative content analysis to explore the editorials published by the Vida Nueva weekly between 1968 and 1975. The results show the impact of the Second Vatican Council on the editorial approach of a journal constrained by Franco’s Regime. I show that the weekly reflected the thinking of a significant number of Spanish Catholic readers; it was deeply democratic and promoted the freedom of religion, press, political thought, and association. Consequently, Vida Nueva opposed the repression of the Regime and aimed for a separation of powers between Church and State, mainly so that the Church could preach and promote its social thought in public life.
Saint Wilgefortis: A Queer Image for Today
Authors: Budwey Stephanie A.
Published: July 2022

An increasing number of people identify outside of the sex/gender binary, many of whom are in crisis and under attack simply because of how they choose to identify. There are few opportunities for them to experience healing in liturgies, particularly as these liturgies often perpetuate a normative view of the sex/gender binary through language and art. This article offers Saint Wilgefortis as an emancipatory image that offers healing while also transforming ethical attitudes and behaviors toward those who identify outside of the sex/gender binary. First is an examination of the history of the cult of Wilgefortis. This is followed by interpretations of the medieval devotion to Wilgefortis, providing a liberating depiction of someone who blurs boundaries, who is ‘both and neither,’ who is and is not Christ (human and divine), and who is and is not ‘female’ or ‘male.’ Next is an exploration of contemporary portrayals of Wilgefortis, providing a queer, multivalent, and prophetic image for today. Finally, there is a discussion of how Wilgefortis could be incorporated into liturgies that minister especially to those who identify outside of the sex/gender binary while also expanding the imagination of those who struggle to see sex/gender as a spectrum.
Does Spirituality Influence Happiness and Academic Performance?
Authors: David Rajasekhar , Singh Sharda , Ribeiro Neuza , Gomes Daniel Roque
Published: July 2022

One of the key issues of the learning experience is students’ performance during the course, as this is pointed to as one of the main indicators for boosting competences’ development and skills’ improvement. This study explores the roles of spirituality, forgiveness, and gratitude on students’ academic performance, proposing a model of analysis revealing a first-order moderation effect of spirituality in the mediation effect of happiness, on the relation between gratitude and forgiveness with students’ academic performance. Two hundred twenty management students from various Indian universities voluntarily participated in the study. To avoid common method-bias issues, data concerning the study variables were obtained in two distinct moments. To test for the moderated-mediation model of analysis, we have followed the PROCESS analytical procedure. Results showed that forgiveness and gratitude were positively and significantly related to happiness and academic performance. It was also possible to see that spirituality moderates the relationship between forgiveness for self and student happiness. Finally, the moderated-mediating impact of spirituality and happiness on the relationship between gratitude and academic performance was also supported. The present study has taken the lead from positive psychology to assess the students’ character strengths related to their well-being and success. It proposes an innovative model of analysis, supported by theoretical reasoning, pointing to the existence of a moderated-mediation relation predicting students’ academic performance.
A Variable-Scale Coherent Integration Method for Moving Target Detection in Wideband Radar
Authors: Lu Tingkun , He Feng , Yu Lei , Wu Manqing
Published: July 2022

Accurate integration of the extended target’s energy is one of the important challenges of moving target detection in wideband radar. In this paper, a coherent integration method for wideband radar, i.e., variable-scale moving target detection (VSMTD), is proposed to resist range migration and Doppler broadening. On the one hand, subband decomposition can effectively integrate the energy of the extended target in range using variable-scale transformation, accomplished by modulating the filter bank. On the other hand, it increases the coherent integration time by mitigating the range migration in a sufficiently narrow subband. The discrete Fourier transform (DFT) modulated filter bank and the fast Fourier transform (FFT) algorithm are also used to achieve fast VSMTD implementation. Finally, the simulation results demonstrate the superior performance of the proposed VSMTD method.
Live Fuel Moisture Content Mapping in the Mediterranean Basin Using Random Forests and Combining MODIS Spectral and Thermal Data
Authors: Cunill Camprubí Àngel , González-Moreno Pablo , Resco de Dios Víctor
Published: July 2022

Remotely sensed vegetation indices have been widely used to estimate live fuel moisture content (LFMC). However, marked differences in vegetation structure affect the relationship between field-measured LFMC and reflectance, which limits spatial extrapolation of these indices. To overcome this limitation, we explored the potential of random forests (RF) to estimate LFMC at the subcontinental scale in the Mediterranean basin wildland. We built RF models (LFMCRF) using a combination of MODIS spectral bands, vegetation indices, surface temperature, and the day of year as predictors. We used the Globe-LFMC and the Catalan LFMC monitoring program databases as ground-truth samples (10,374 samples). LFMCRF was calibrated with samples collected between 2000 and 2014 and validated with samples from 2015 to 2019, with overall root mean square errors (RMSE) of 19.9% and 16.4%, respectively, which were lower than current approaches based on radiative transfer models (RMSE ~74–78%). We used our approach to generate a public database with weekly LFMC maps across the Mediterranean basin.
SRT: A Spectral Reconstruction Network for GF-1 PMS Data Based on Transformer and ResNet
Authors: Mu Kai , Zhang Ziyuan , Qian Yurong , Liu Suhong , Sun Mengting , Qi Ranran
Published: July 2022

The time of acquiring remote sensing data was halved after the joint operation of Gao Fen-6 (GF-6) and Gao Fen-1 (GF-1) satellites. Meanwhile, GF-6 added four bands, including the “red-edge” band that can effectively reflect the unique spectral characteristics of crops. However, GF-1 data do not contain these bands, which greatly limits their application to crop-related joint monitoring. In this paper, we propose a spectral reconstruction network (SRT) based on Transformer and ResNet to reconstruct the missing bands of GF-1. SRT is composed of three modules: (1) The transformer feature extraction module (TFEM) fully extracts the correlation features between spectra. (2) The residual dense module (RDM) reconstructs local features and avoids the vanishing gradient problem. (3) The residual global construction module (RGM) reconstructs global features and preserves texture details. Compared with competing methods, such as AWAN, HRNet, HSCNN-D, and M2HNet, the proposed method proved to have higher accuracy by a margin of the mean relative absolute error (MRAE) and root mean squared error (RMSE) of 0.022 and 0.009, respectively. It also achieved the best accuracy in supervised classification based on support vector machine (SVM) and spectral angle mapper (SAM).
AVHRR GAC Sea Surface Temperature Reanalysis Version 2
Authors: Petrenko Boris , Pryamitsyn Victor , Ignatov Alexander , Jonasson Olafur , Kihai Yury
Published: July 2022

The 40+ years-long sea surface temperature (SST) dataset from 4 km Global Area Coverage (GAC) data of the Advanced Very High-Resolution Radiometers (AVHRR/2s and/3s) flown onboard ten NOAA satellites (N07/09/11/12/14/15/16/17/18/19) has been created under the NOAA AVHRR GAC SST Reanalysis 2 (RAN2) Project. The data were reprocessed with the NOAA Advanced Clear Sky Processor for Ocean (ACSPO) enterprise SST system. Two SST products are reported in the full ~3000 km AVHRR swath: ‘subskin’ (highly sensitive to true skin SST, but debiased with respect to in situ SST) and ‘depth’ (a closer proxy for in situ data, but with reduced sensitivity). The reprocessing methodology aims at close consistency of satellite SSTs with in situ SSTs, in an optimal retrieval domain. Long-term orbital and calibration trends were compensated by daily recalculation of regression coefficients using matchups with drifters and tropical moored buoys (supplemented by ships for N07/09), collected within limited time windows centered at the processed day. The nighttime Sun impingements on the sensor black body were mitigated by correcting the L1b calibration coefficients. The Earth view pixels contaminated with a stray light were excluded. Massive cold SST outliers caused by volcanic aerosols following three major eruptions were filtered out by a modified, more conservative ACSPO clear-sky mask. The RAN2 SSTs are available in three formats: swath L2P (144 10-min granules per 24 h interval) and two 0.02° gridded (uncollated L3U, also 144 granules/24 h; and collated L3C, two global maps per 24 h, one for day and one for the night). This paper evaluates the RAN2 SST dataset, with a focus on the L3C product and compares it with two other available AVHRR GAC L3C SST datasets, NOAA Pathfinder v5.3 and ESA Climate Change Initiative v2.1. Among the three datasets, the RAN2 covers the global ocean more completely and shows reduced regional and temporal biases, improved stability and consistency between different satellites, and in situ SSTs.
Inferring 2D Local Surface-Deformation Velocities Based on PSI Analysis of Sentinel-1 Data: A Case Study of Öræfajökull, Iceland
Authors: Dittrich Jirathana , Hölbling Daniel , Tiede Dirk , Sæmundsson Þorsteinn
Published: July 2022

Two-dimensional deformation estimates derived from Persistent Scatterer Interferometric (PSI) analysis of Synthetic Aperture Radar (SAR) data can improve the characterisation of spatially and temporally varying deformation processes of Earth’s surface. In this study, we examine the applicability of Persistent Scatterer (PS) Line-Of-Sight (LOS) estimates in providing two-dimensional deformation information, focusing on the retrieval of the local surface-movement processes. Two Sentinel-1 image stacks, ascending and descending, acquired from 2015 to 2018, were analysed based on a single master interferometric approach. First, Interferometric SAR (InSAR) deformation signals were corrected for divergent plate spreading and the Glacial Isostatic Adjustment (GIA) signals. To constrain errors due to rasterisation and interpolation of the pointwise deformation estimates, we applied a vector-based decomposition approach to solve the system of linear equations, resulting in 2D vertical and horizontal surface-deformation velocities at the PSs. We propose, herein, a two-step decomposition procedure that incorporates the Projected Local Incidence Angle (PLIA) to solve for the potential slope-deformation velocity. Our derived 2D velocities reveal spatially detailed movement patterns of the active Svínafellsjökull slope, which agree well with the independent GPS time-series measurements available for this area.
Characteristics of Freeze–Thaw Cycles in an Endorheic Basin on the Qinghai-Tibet Plateau Based on SBAS-InSAR Technology
Authors: Zhou Huayun , Zhao Lin , Wang Lingxiao , Xing Zanpin , Zou Defu , Hu Guojie , Xie Changwei , Pang Qiangqiang , Liu Guangyue , Du Erji , Liu Shibo , Qiao Yongping , Zhao Jianting , Li Zhibin , Liu Yadong
Published: July 2022

The freeze–thaw (F-T) cycle of the active layer (AL) causes the “frost heave and thaw settlement” deformation of the terrain surface. Accurately identifying its amplitude and time characteristics is important for climate, hydrology, and ecology research in permafrost regions. We used Sentinel-1 SAR data and small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) technology to obtain the characteristics of F-T cycles in the Zonag Lake-Yanhu Lake permafrost-affected endorheic basin on the Qinghai-Tibet Plateau from 2017 to 2019. The results show that the seasonal deformation amplitude (SDA) in the study area mainly ranges from 0 to 60 mm, with an average value of 19 mm. The date of maximum frost heave (MFH) occurred between November 27th and March 21st of the following year, averaged in date of the year (DOY) 37. The maximum thaw settlement (MTS) occurred between July 25th and September 21st, averaged in DOY 225. The thawing duration is the thawing process lasting about 193 days. The spatial distribution differences in SDA, the date of MFH, and the date of MTS are relatively significant, but there is no apparent spatial difference in thawing duration. Although the SDA in the study area is mainly affected by the thermal state of permafrost, it still has the most apparent relationship with vegetation cover, the soil water content in AL, and active layer thickness. SDA has an apparent negative and positive correlation with the date of MFH and the date of MTS. In addition, due to the influence of soil texture and seasonal rivers, the seasonal deformation characteristics of the alluvial-diluvial area are different from those of the surrounding areas. This study provides a method for analyzing the F-T cycle of the AL using multi-temporal InSAR technology.
UAV Video-Based Approach to Identify Damaged Trees in Windthrow Areas
Authors: Furukawa Flavio , Morimoto Junko , Yoshimura Nobuhiko , Koi Takashi , Shibata Hideaki , Kaneko Masami
Published: July 2022

Disturbances in forest ecosystems are expected to increase by the end of the twenty-first century. An understanding of these disturbed areas is critical to defining management measures to improve forest resilience. While some studies emphasize the importance of quick salvage logging, others emphasize the importance of the deadwood for biodiversity. Unmanned aerial vehicle (UAV) remote sensing is playing an important role to acquire information in these areas through the structure-from-motion (SfM) photogrammetry process. However, the technique faces challenges due to the fundamental principle of SfM photogrammetry as a passive optical method. In this study, we investigated a UAV video-based technology called full motion video (FMV) to identify fallen and snapped trees in a windthrow area. We compared the performance of FMV and an orthomosaic, created by the SfM photogrammetry process, to manually identify fallen and snapped trees, using a ground survey as a reference. The results showed that FMV was able to identify both types of damaged trees due to the ability of video to deliver better context awareness compared to the orthomosaic, although providing lower position accuracy. In addition to its processing being simpler, FMV technology showed great potential to support the interpretation of conventional UAV remote sensing analysis and ground surveys, providing forest managers with fast and reliable information about damaged trees in windthrow areas.
Analyzing Canopy Height Patterns and Environmental Landscape Drivers in Tropical Forests Using NASA’s GEDI Spaceborne LiDAR
Authors: Adrah Esmaeel , Wan Mohd Jaafar Wan Shafrina , Omar Hamdan , Bajaj Shaurya , Leite Rodrigo Vieira , Mazlan Siti Munirah , Silva Carlos Alberto , Chel Gee Ooi Maggie , Mohd Said Mohd Nizam , Abdul Maulud Khairul Nizam , Cardil Adrián , Mohan Midhun
Published: July 2022

Canopy height is a fundamental parameter for determining forest ecosystem functions such as biodiversity and above-ground biomass. Previous studies examining the underlying patterns of the complex relationship between canopy height and its environmental and climatic determinants suffered from the scarcity of accurate canopy height measurements at large scales. NASA’s mission, the Global Ecosystem Dynamic Investigation (GEDI), has provided sampled observations of the forest vertical structure at near global scale since late 2018. The availability of such unprecedented measurements allows for examining the vertical structure of vegetation spatially and temporally. Herein, we explore the most influential climatic and environmental drivers of the canopy height in tropical forests. We examined different resampling resolutions of GEDI-based canopy height to approximate maximum canopy height over tropical forests across all of Malaysia. Moreover, we attempted to interpret the dynamics underlining the bivariate and multivariate relationships between canopy height and its climatic and topographic predictors including world climate data and topographic data. The approaches to analyzing these interactions included machine learning algorithms, namely, generalized linear regression, random forest and extreme gradient boosting with tree and Dart implementations. Water availability, represented as the difference between precipitation and potential evapotranspiration, annual mean temperature and elevation gradients were found to be the most influential determinants of canopy height in Malaysia’s tropical forest landscape. The patterns observed are in line with the reported global patterns and support the hydraulic limitation hypothesis and the previously reported negative trend for excessive water supply. Nevertheless, different breaking points for excessive water supply and elevation were identified in this study, and the canopy height relationship with water availability observed to be less significant for the mountainous forest on altitudes higher than 1000 m. This study provides insights into the influential factors of tree height and helps with better comprehending the variation in canopy height in tropical forests based on GEDI measurements, thereby supporting the development and interpretation of ecosystem modeling, forest management practices and monitoring forest response to climatic changes in montane forests.
CAISOV: Collinear Affine Invariance and Scale-Orientation Voting for Reliable Feature Matching
Authors: Luo Haihan , Liu Kai , Jiang San , Li Qingquan , Wang Lizhe , Jiang Wanshou
Published: July 2022

Reliable feature matching plays an important role in the fields of computer vision and photogrammetry. Due to the complex transformation model caused by photometric and geometric deformations, and the limited discriminative power of local feature descriptors, initial matches with high outlier ratios cannot be addressed very well. This study proposes a reliable outlier-removal algorithm by combining two affine-invariant geometric constraints. First, a very simple geometric constraint, namely, CAI (collinear affine invariance) has been implemented, which is based on the observation that the collinear property of any two points is invariant under affine transformation. Second, after the first-step outlier removal based on the CAI constraint, the SOV (scale-orientation voting) scheme was then adopted to remove remaining outliers and recover the lost inliers, in which the peaks of both scale and orientation voting define the parameters of the geometric transformation model. Finally, match expansion was executed using the Delaunay triangulation of refined matches. By using close-range (rigid and non-rigid images) and UAV (unmanned aerial vehicle) datasets, comprehensive comparison and analysis are conducted in this study. The results demonstrate that the proposed outlier-removal algorithm achieves the best overall performance when compared with RANSAC-like and local geometric constraint-based methods, and it can also be applied to achieve reliable outlier removal in the workflow of SfM-based UAV image orientation.
Mapping the Recent Vertical Crustal Deformation of the Weihe Basin (China) Using Sentinel-1 and ALOS-2 ScanSAR Imagery
Authors: Qu Feifei , Zhang Qin , Niu Yufen , Lu Zhong , Wang Shuai , Zhao Chaoying , Zhu Wu , Qu Wei , Yang Chengsheng
Published: July 2022

The Weihe Basin, located in central China, is a Cenozoic rift basin that is characterized by a complicated geological background, with intense tectonic movement and relatively significant seismic activity. The faulting behaviors, slip rates, geometrical structures, and possible surface traces of the active faults in the Weihe Basin are still not well known. The goal of this work is to provide a more complete picture of recent vertical ground deformation of the basin and to identify active faults. We derived two basin-wide average InSAR deformation maps during 2015–2019 using C-band Sentinel-1A/B and L-band ALOS PALSAR2 ScanSAR imagery. The basin-wide vertical and east–west deformation components decomposed from ascending and descending InSAR measurements show that vertical movement dominates the deformation of the Weihe Basin. Subsidence and uplift maxima both occurred over the Xi’an region at rates of about −146 and 20 mm/y, respectively. A subsidence of ~38 mm/y was found at Sanyuan, Fuping, Weinan, Lantian, Qianxian, and Xingping while an uplift of ~11 mm/y was found at Fufeng, Huxian, Jingyang, Fuping, Pucheng, and Huaxian. The significant vertical deformation in these regions is spatially linked to previously identified or unmapped faults. A slip rate of ~13.7 mm/y on faults F20, F6, F10, and F7 explained the observed uplift of up to 5 mm/y in the Fufeng and Wugong areas. Furthermore, surface fault traces were clearly identified for faults F7-1, F8-1, F20, F25, and F26 based on discontinuities in the InSAR-derived vertical deformation measurements. Our results provide an accurate and economical way to delineate the surface deformation and fault movement and the associated geohazards over the Weihe Basin, and offer independent unprecedented data for further geological and geophysical interpretation.
A Lightweight Convolutional Neural Network Based on Hierarchical-Wise Convolution Fusion for Remote-Sensing Scene Image Classification
Authors: Shi Cuiping , Zhang Xinlei , Wang Tianyi , Wang Liguo
Published: July 2022

The large intra-class difference and inter-class similarity of scene images bring great challenges to the research of remote-sensing scene image classification. In recent years, many remote-sensing scene classification methods based on convolutional neural networks have been proposed. In order to improve the classification performance, many studies increase the width and depth of convolutional neural network to extract richer features, which increases the complexity of the model and reduces the running speed of the model. In order to solve this problem, a lightweight convolutional neural network based on hierarchical-wise convolution fusion (LCNN-HWCF) is proposed for remote-sensing scene image classification. Firstly, in the shallow layer of the neural network (groups 1–3), the proposed lightweight dimension-wise convolution (DWC) is utilized to extract the shallow features of remote-sensing images. Dimension-wise convolution is carried out in the three dimensions of width, depth and channel, and then, the convoluted features of the three dimensions are fused. Compared with traditional convolution, dimension-wise convolution has a lower number of parameters and computations. In the deep layer of the neural network (groups 4–7), the running speed of the network usually decreases due to the increase in the number of filters. Therefore, the hierarchical-wise convolution fusion module is designed to extract the deep features of remote-sensing images. Finally, the global average pooling layer, the fully connected layer and the Softmax function are used for classification. Using global average pooling before the fully connected layer can better preserve the spatial information of features. The proposed method achieves good classification results on UCM, RSSCN7, AID and NWPU datasets. The classification accuracy of the proposed LCNN-HWCF on the AID dataset (training:test = 2:8) and the NWPU dataset (training:test = 1:9), with great classification difficulty, reaches 95.76% and 94.53%, respectively. A series of experimental results show that compared with some state-of-the-art classification methods, the proposed method not only greatly reduces the number of network parameters but also ensures the classification accuracy and achieves a good trade-off between the model classification accuracy and running speed.
Improving Soil Moisture Estimation via Assimilation of Remote Sensing Product into the DSSAT Crop Model and Its Effect on Agricultural Drought Monitoring
Authors: Zhou Hongkui , Geng Guangpo , Yang Jianhua , Hu Hao , Sheng Li , Lou Weidong
Published: July 2022

Accurate knowledge of soil moisture is crucial for agricultural drought monitoring. Data assimilation has proven to be a promising technique for improving soil moisture estimation, and various studies have been conducted on soil moisture data assimilation based on land surface models. However, crop growth models, which are ideal tools for agricultural simulation applications, are rarely used for soil moisture assimilation. Moreover, the role of data assimilation in agricultural drought monitoring is seldom investigated. In the present work, we assimilated the European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture product into the Decision Support System for Agro-technology Transfer (DSSAT) model to estimate surface and root-zone soil moisture, and we evaluated the effect of data assimilation on agricultural drought monitoring. The results demonstrate that the soil moisture estimates were significantly improved after data assimilation. Root-zone soil moisture had a better agreement with in situ observation. Compared with the drought index based on soil moisture modeled without remotely-sensed observations, the drought index based on assimilated data could improve at least one drought level in agricultural drought monitoring and performed better when compared with winter wheat yield. In conclusion, crop growth model-based data assimilation effectively improves the soil moisture estimation and further strengthens soil moisture-based drought indices for agricultural drought monitoring.
Annual Wetland Mapping in Metropolis by Temporal Sample Migration and Random Forest Classification with Time Series Landsat Data and Google Earth Engine
Authors: Wang Ming , Mao Dehua , Wang Yeqiao , Song Kaishan , Yan Hengqi , Jia Mingming , Wang Zongming
Published: July 2022

Wetlands provide various ecosystem services to urban areas, which are crucial for sustainable urban management. With intensified urbanization, there has been marked loss of urban natural wetland, degradation, and related urban disasters in the past several decades. Rapid and accurate mapping of urban wetland extent and change is thus critical for improving urban planning toward sustainability. Here, we have developed a rapid method for continuous mapping of urban wetlands (MUW) by combining automatic sample migration and the random forest algorithm (SM&RF), the so-called MUW_SM&RF. Using time series Landsat images, annual training samples were generated through spectral angular distance (SAD) and time series analysis. Combined with the RF algorithm, annual wetland maps in urban areas were derived. Employing the Google Earth Engine platform (GEE), the MUW_SM&RF was evaluated in four metropolitan areas in different geographical and climatic regions of China from 1990 to 2020, including Tianjin, Hangzhou, Guangzhou, and Wuhan. In all four study areas, the generated annual wetland maps had an overall accuracy of over 87% and a Kappa coefficient above 0.815. Compared with previously published datasets, the urban wetland areas derived using the MUW_SM&RF approach achieved improved accuracy and thus demonstrated its robustness for rapid mapping of urban wetlands. Urban wetlands in all four cities had variable distribution patterns and showed significantly decreased trends in the past three decades. The annual urban wetland data product generated by the MUW_SM&RF can provide invaluable information for sustainable urban planning and management, so as for assessment related to the United Nation’s sustainable development goals.
Influence of the Nocturnal Effect on the Estimated Global CO2 Flux
Authors: Jin Rui , Yu Tan , Tao Bangyi , Shao Weizeng , Hu Song , Wei Yongliang
Published: July 2022

We found that significant errors occurred when diurnal data instead of diurnal–nocturnal data were used to calculate the daily sea-air CO2 flux (F). As the errors were mainly associated with the partial pressure of CO2 in seawater (pCO2w) and the sea surface temperature (SST) in the control experiment, pCO2w and SST equations were established, which are called the nocturnal effect of the CO2 flux. The root-mean-square error between the real daily CO2 flux (Freal) and the daily CO2 flux corrected for the nocturnal effect (Fcom) was 11.93 mmol m−2 d−1, which was significantly lower than that between the Freal value and the diurnal CO2 flux (Fday) (46.32 mmol m−2 d−1). Thus, the errors associated with using diurnal data to calculate the CO2 flux can be reduced by accounting for the nocturnal effect. The mean global daily CO2 flux estimated based on the nocturnal effect and the sub-regional pCO2w algorithm (cor_Fcom) was −6.86 mol m−2 y−1 (September 2020–August 2021), which was greater by 0.75 mol m−2 y−1 than that based solely on the sub-regional pCO2w algorithm (day_Fcom = −7.61 mol m−2 y−1). That is, compared with cor_Fcom, the global day_Fcom value overestimated the CO2 sink of the global ocean by 10.89%.
Grassland Aboveground Biomass Estimation through Assimilating Remote Sensing Data into a Grass Simulation Model
Authors: Zhang Yuxin , Huang Jianxi , Huang Hai , Li Xuecao , Jin Yunxiang , Guo Hao , Feng Quanlong , Zhao Yuanyuan
Published: July 2022

Grassland aboveground biomass is crucial for evaluating grassland desertification, degradation, and grassland and livestock balance. Given the lack of understanding of mechanical processes and limited simulation accuracy for grassland aboveground biomass estimation, especially at the regional scale, this study investigates a new method combining remote sensing data assimilation technology and a grassland process-based model to estimate regional grassland biomass, focusing on improving the simulation accuracy by modeling and revealing the mechanism interpretability of grassland growth processes. Xilinhot City of Inner Mongolia was used as the study area. The ModVege model was selected as the grass dynamic simulation model. A likelihood function was constructed composed of the LAI, grassland aboveground biomass, and daily measurements wherein the accumulated temperature reached ST2 (the temperature sum defining the end of reproductive growth). Then, the Markov chain Monte Carlo (MCMC) methodology was adapted to calibrate the ModVege model by maximizing the likelihood function. The time-series LAI from MOD15A3H was assimilated into the ModVege model, and the model parameters ST2 and BMGV0 (initial biomass and green vegetative tissues, respectively) were optimized at a 500 m pixel scale based on the four-dimensional variational method (4DVar) method. Compared with August 15th, the RMSE and MAPE of aboveground biomass were 242 kg/ha and 10%, respectively, after calibration. Data assimilation improved this accuracy, with the RMSE decreasing to 214 kg/ha. Overall, the aboveground grassland biomass of Xilinhot City shows spatial distribution patterns of high value in the northeast and low value in the central and southeast areas. Generally, the method implemented in this study provides an important reference for the aboveground biomass estimation of regional grassland.
Large-Scale Debris Cover Glacier Mapping Using Multisource Object-Based Image Analysis Approach
Authors: Mitkari Kavita V. , Arora Manoj K. , Tiwari Reet Kamal , Sofat Sanjeev , Gusain Hemendra S. , Tiwari Surya Prakash
Published: July 2022

Large-scale debris cover glacier mapping can be efficiently conducted from high spatial resolution (HSR) remote sensing imagery using object-based image analysis (OBIA), which works on a group of pixels. This paper presents the spectral and spatial capabilities of OBIA to classify multiple glacier cover classes using a multisource approach by integrating multispectral, thermal, and slope information into one workflow. The novel contributions of this study are effective mapping of small yet important geomorphological features, classification of shadow regions without manual corrections, discrimination of snow/ice, ice-mixed debris, and supraglacial debris without using shortwave infrared bands, and an adaptation of an area-weighted error matrix specifically built for assessing OBIA’s accuracy. The large-scale glacier cover map is produced with a high overall accuracy of ≈94% (area-weighted error matrix). The proposed OBIA approach also proved to be effective in mapping minor geomorphological features such as small glacial lakes, exposed ice faces, debris cones, rills, and crevasses with individual class accuracies in the range of 96.9–100%. We confirm the portability of our proposed approach by comparing the results with reference glacier inventories and applying it to different sensor data and study areas.
An Ensemble-Based Machine Learning Model for Estimation of Subsurface Thermal Structure in the South China Sea
Authors: Qi Jifeng , Liu Chuanyu , Chi Jianwei , Li Delei , Gao Le , Yin Baoshu
Published: July 2022

Reconstructing the vertical structures of the ocean from sea surface information is of great importance for ocean and climate studies. In this study, an ensemble machine learning (Ens-ML) model is proposed to retrieve ocean subsurface thermal structure (OSTS) by using satellite-derived sea surface data and Argo data in the South China Sea (SCS). The input data include sea surface height (SSH), sea surface temperature (SST), sea surface salinity (SSS), sea surface wind (SSW), and geographic information (including longitude and latitude). We select three stable machine learning models, namely, extreme gradient boosting (XGBoost), RandomForest and light gradient boosting machine (LightGBM) as our benchmark models, and then use an artificial neural network (ANN) technique to combine outputs from the three individual models. The proposed Ens-ML model using sea surface data only by SSH, SST, SSS, and SSW performs less satisfactorily than that considering the contribution of geographical information, indicating that the geographical information is essential to estimate the OSTS accurately. The estimated OSTS from the Ens-ML model are compared with Argo data. The results show that the proposed Ens-ML model can accurately estimate the OSTS (upper 1000 m) in the SCS, which is relatively more accurate and precise than the individual models. The performance of the Ens-ML model also varies with season, and better estimation is obtained in winter, which is probably due to stronger mixing and weaker stratification. This study shows the great potential and advantage of the multi-model ensemble of machine learning algorithm for the ocean’s interior information retrieving, showing great potential in expanding the scope of ocean observations.
Comparative Study of Predominantly Daytime and Nighttime Lightning Occurrences and Their Impact on Ionospheric Disturbances
Authors: Osei-Poku Louis , Tang Long , Chen Wu , Chen Mingli , Acheampong Akwasi Afrifa
Published: July 2022

Space weather events adversely impact the operations of Global Navigation Satellite Systems (GNSS). Understanding space weather mechanisms, interactions in the atmosphere, and the extent of their impact are useful in developing prediction and mitigation models. In this study, the hourly lightning occurrence and its impact on ionospheric disturbances, quantified using the Rate of Total electron content Index (ROTI), were assessed. The linear correlation between diurnal lightning activity and ROTI in the coastal region of southern China where lightning predominates in the daytime was initially negative contrary to a positive correlation in southern Africa where lighting predominates in the evening. After appreciating and applying the physical processes of gravity waves, electromagnetic waves and the Trimpi effect arising from lightning activity, and the time delay impact they have on the ionosphere, the negative correlation was overturned to a positive one using cross-correlation. GNSS has demonstrated its capability of revealing the impact lightning has on the ionosphere at various times of the day.
Spatiotemporal Evolution of Cultivated Land Non-Agriculturalization and Its Drivers in Typical Areas of Southwest China from 2000 to 2020
Authors: Chen Yan , Wang Shiyuan , Wang Yahui
Published: July 2022

Cultivated land resources are crucial to food security and economic development. Exploring the spatiotemporal pattern of cultivated land non-agriculturalization and its drivers is a prerequisite for cultivated land conservation. This paper used GlobeLand30 data to reveal the spatial and temporal pattern, the shift of the gravity center and the drivers of cultivated land non-agriculturalization by employing spatial analysis, gravity center model and the geographical detector model. The results show a dramatic increase in the non-agriculturalization of cultivated land in the period of 2010–2020 compared to 2000–2010. Spatially, the cultivated land non-agriculturalization mainly occurred in areas with high urbanization levels, such as eastern Sichuan Province and western Chongqing Municipality, while the cultivated land non-agriculturalization in other areas was small-scale and spatially scattered. Furthermore, the speed of cultivated land non-agriculturalization showed spatial unevenness, and the gravity center of cultivated land non-agriculturalization shifted towards the northeast at a distance of 123.21 km. The cultivated land non-agriculturalization was affected by GDP per capita, population density, GDP per unit of land and total retail sales of social consumer goods. The key drivers for the cultivated land non-agriculturalization in the study area were the continuous expansion of urban space and the large-scale cultivation of economic fruit trees. The government should promote small-scale machinery suitable for agricultural cultivation in the mountainous and hilly areas of Southwest China, and appropriately develop economic fruit groves and livestock farming to reduce the phenomenon of cultivated land non-foodization.
Analyzing the Dynamic Spatiotemporal Changes in Urban Extension across Zhejiang Province Using NPP-VIIRS Nighttime Light Data
Authors: Yan Yangyang , Lei Hui , Chen Yihong , Zhou Bin
Published: July 2022

Nighttime light remote sensing technologies provide methods for studying spatiotemporal changes in urban areas. In this research, we study the changes in the urban zone in Zhejiang Province based on NPP/VIIRS nighttime light data. Moreover, we propose a methodology to extract urban zones through a buffer threshold analysis method and apply the standard deviation ellipse, urban scale increment, “dual-core” primacy and urban-scale Gini index to uncover the evolution of urban dynamics in Zhejiang Province. The results show that the highest overall urban area extraction accuracy was 95.9%; the highest Kappa coefficient was 91%. The nighttime light intensity changes observed in most cities in Zhejiang Province reflected three periods: “high-speed growth” from 2012–2014, “low-speed growth” from 2014–2018 and “high-speed growth” from 2019–2020. The growth rates observed during the 2019–2020 “high-speed growth” period exceeded those of the 2012–2014 period. Over nine years, the growth rates of the total nighttime light values in all cities ranged from 40% to 319%. Third-tier cities such as Quzhou and Lishui showed significant increases. Second-tier cities, such as Jinhua, Huzhou and Taizhou, had growth rates over 100%. From 2012–2014, the development rates increased in cities in southern Zhejiang Province, such as in Wenzhou and Taizhou, thus promoting a southward shift in the center of gravity. After 2014, the development rates increased in cities in northern Zhejiang Province, such as Hangzhou, Ningbo and Jiaxing, thus promoting a northward shift in the center of gravity, with the center stabilizing in the Keqiao District-Yuecheng District of Shaoxing. According to the changes observed in the “dual-core” primacy and urban-scale Gini index results derived from 2012 to 2020, the development of cities in Zhejiang Province has become more balanced over the past nine years.