Spatial correlations in time and frequency domains between chlorophyll-a concentration and environmental factors in the Bohai Sea

Based on the reconstructed MODIS data and ECMWF reanalysis data from 2003 to 2021,spatial correlations between chlorophyll a(Chl a)and sea surface temperature(SST),photosynthetically available radiation(PAR),aerosol optical thickness(AOT),and wind speed(WS)in the Bohai Sea were analyzed from the perspective of time domain and frequency domain.Results indicate that the frequency domain analysis was more conducive to revealing the correlations between Chl a and environmental factors.The spatial pattern of time-domain correlations was similar to the isobaths of the Bohai Sea,which was positive in shallow waters and negative in deep waters for SST,PAR,and AOT,and was reversed for WS.Frequency-domain correlations were obtained by performing Fourier Transform and were higher than correlations in time domain.The spatial distributions indicated that the effects of SST and PAR on Chl a were greater than AOT and WS in the Bohai Sea.Additionally,cross-spectrum analysis was applied to explore the response relationships.A depth-dependent pattern was shown in correlations and time lags,indicating that the influential mechanism of environmental factors on Chl-a concentration is related to seawater depth.

Spatial correlations in ground motion intensity measuring from the 2023 Türkiye earthquake

When evaluating an area's seismic risk or resilience,it is necessary to use the spatial correlation to analyze the ground motion parameters of multiple sites together in an earthquake.These two large earthquakes in Türkiye provided the possibility for spatial correlation analysis of ground motion intensity measurements in this area.Based on the strong motion records provided by The Disaster and Emergency Management Authority of Türkiye(AFAD),this study uses the local ground motion prediction equation in Türkiye to give spatial correlation analysis of Intensity Measurements.This study gives an exponential model based on a semivariogram and compares it with the correlation model obtained from previous studies.

Spatial Analysis of the Aging Population and Socio-economic Factors of China:Global and Local Perspectives

Population aging has become an inevitable trend and exerted profound influences on socio-economic development in China.In this study,we utilized data from national population census and statistical yearbooks in 2010 and 2020 to explore spatio-temporal patterns of aging population and its coupling correlations with socio-economic factors from both global and local perspectives.The results from Local Indicators of Spatial Association(LISA)uncover notable spatial disparities in aging population rates,with higher rates concentrated in the eastern regions and lower rates in the western areas of the Chinese mainland.The results from the global correlation analysis with the changes in aging population rates show significant positive correlations with government interventions and industrial structures,but negatively correlated with economic development,social consumption,and medical facilities.From a local perspective,a Geographically Weighted(GW)correlation analysis is employed to uncover local correlations between aging trends and socio-economic factors.The insights gained from this technique not only underscore the complexity and diversity of economic implications stemming from population aging,but also provide invaluable guidance for crafting region-specific economic policies tailored to various stages of population aging.

Spatial correlations between urbanization and river water pollution in the heavily polluted area of Taihu Lake Basin, China

Water pollution in the Taihu Lake Basin has been the focus of attention in China and abroad for a long time, due to its position in the forefront of urban development in China. Based on data gathering and processing from 84 monitoring sections in this heavily polluted area, this study first analyzes spatial patterns of urbanization and the distribution of river water pollution, and then uses the GeoDa bivariate spatial autocorrelation model to investigate the spatial correlation between urbanization and river water pollution at the scale of township units. The results show that urbanization has adverse impacts on water pollution, and the influence varies in different levels of development areas. The urban township units have the highest level of urbanization and highest pollution, but the best water quality; the suburban units have lower level of urbanization, but higher pollution and worse water quality; however the rural units have the lowest level of urbanization and lowest pollution, mainly affected by upstream pollution, but worst water quality. Lastly, urban and rural planning committees, while actively promoting the process of development in the region, should gradually resolve the issue of pollution control lagging behind urban life and urban develop- ment, giving priority to construction of centralized sewage treatment facilities and associated pipeline network coverage in the rural areas and suburban areas.

Spatial Correlation Module for Classification of Multi-Label Ocular Diseases Using Color Fundus Images

To prevent irreversible damage to one’s eyesight,ocular diseases(ODs)need to be recognized and treated immediately.Color fundus imaging(CFI)is a screening technology that is both effective and economical.According to CFIs,the early stages of the disease are characterized by a paucity of observable symptoms,which necessitates the prompt creation of automated and robust diagnostic algorithms.The traditional research focuses on image-level diagnostics that attend to the left and right eyes in isolation without making use of pertinent correlation data between the two sets of eyes.In addition,they usually only target one or a few different kinds of eye diseases at the same time.In this study,we design a patient-level multi-label OD(PLML_ODs)classification model that is based on a spatial correlation network(SCNet).This model takes into consideration the relevance of patient-level diagnosis combining bilateral eyes and multi-label ODs classification.PLML_ODs is made up of three parts:a backbone convolutional neural network(CNN)for feature extraction i.e.,DenseNet-169,a SCNet for feature correlation,and a classifier for the development of classification scores.The DenseNet-169 is responsible for retrieving two separate sets of attributes,one from each of the left and right CFI.After then,the SCNet will record the correlations between the two feature sets on a pixel-by-pixel basis.After the attributes have been analyzed,they are integrated to provide a representation at the patient level.Throughout the whole process of ODs categorization,the patient-level representation will be used.The efficacy of the PLML_ODs is examined using a soft margin loss on a dataset that is readily accessible to the public,and the results reveal that the classification performance is significantly improved when compared to several baseline approaches.

Delayed response to the photovoltaic performance in a double quantum dots photocell with spatially correlated fluctuation

A viable strategy for enhancing photovoltaic performance is to comprehend the underlying quantum physical regime of charge transfer in a double quantum dots(DQD) photocell. This work explored the photovoltaic performance dependent spatially correlated fluctuation in a DQD photocell. The effects of spatially correlated fluctuation on charge transfer and output photovoltaic efficiency were explored in a proposed DQD photocell model. The results revealed that the charge transport process and the time to peak photovoltaic efficiency were both significantly delayed by the spatially correlated fluctuation, while the anti-spatially correlated fluctuation reduced the output peak photovoltaic efficiency. Further results revealed that the delayed response could be suppressed by gap difference and tunneling coefficient within two dots. Subsequent investigation demonstrated that the delayed response was caused by the spatial correlation fluctuation slowing the generative process of noise-induced coherence, which had previously been proven to improve the quantum photovoltaic performance in quantum photocells. And the reduced photovoltaic properties were verified by the damaged noise-induced coherence owing to the anti-spatial correlation fluctuation and a hotter thermal ambient environment. The discovery of delayed response generated by the spatially correlated fluctuations will deepen the understanding of quantum features of electron transfer, as well as promises to take our understanding even further concerning quantum techniques for high efficiency DQD solar cells.

Spatial Characteristics and Change for Tree Species (Genera) Along Northeast China Transect (NECT)

The 16 tree species on Northeast China Transect (NECT) were analyzed from the change of geographical distribution, frequency and dominance pattern and the spatial correlation at landscape scale in 1986 and 1994. Pinus koraiensis Sieb. et Zucc. and Fraxinus rhynchophylla Hemsl. had spread rapidly towards west and east, respectively. The frontier form of species had close relation with its movement. The patch size of Pinus koraiensis , Populus davidiana Dode., Phellodendron amurense Rupr., Juglans mandshurica Maxim., Fraxinus mandshurica Rupr., Betula dahurica Pall., Picea koraiensis Nakai, Abies nephrolepis Maxim. and Larix olgeusis var. koreana Nakai decreased, however, Quercus mongolica Fisch., Betula costata Trautv., Acer mono Maxim., Tilia spp., Ulmus spp., Betula platyphylla Suk. and Fraxinus rhynchophylla increased. The frequency pattern of Populus davidiana , Betula platyphylla , Fraxinus rhynchophylla and Betula dahurica changed significantly. The dominance pattern of Populus davidiana , Tilia spp., Juglans mandshurica , Betula platyphylla , Betula dahurica and Abies nephrolepis changed significantly. The spatial correlation between Quercus mongolica and Betula dahurica , Betula costata and Picea spp., Betula costata and Abies nephrolepis , Picea spp. and Abies nephrolepis declined, however, the spatial correlation between Larix spp. and Betula platyphylla , Acer mono and Ulmus spp. increased.

Spatial correlation of the high intensity zone in deep-water acoustic field

The spatial correlations of acoustic field have important implications for underwater target detection and other ap- plications in deep water. In this paper, the spatial correlations of the high intensity zone in the deep-water acoustic field are investigated by using the experimental data obtained in the South China Sea. The experimental results show that the structures of the spatial correlation coefficient at different ranges and depths are similar to the transmission loss structure in deep water. The main reason for this phenomenon is analyzed by combining the normal mode theory with the ray theory. It is shown that the received signals in the high intensity zone mainly include one or two main pulses which are contributed by the interference of a group of waterbome modes with similar phases. The horizontal-longitudinal correlations at the same receiver depth but in different high intensity zones are analyzed. At some positions, more pulses are received in the arrival structure of the signal due to bottom reflection and the horizontal-longitudinal correlation coefficient decreases accordingly. The multi-path arrival structure of receiving signal becomes more complex with increasing receiver depth.

Spatial pattern dynamics among co-dominant populations in early secondary forests in Southwest China

The canopy of subtropical natural forests usually consists of several co-dominant populations(CDPs),which play a crucial role in forest structure,formation of the forest environment,and ecological function.However,little attention has been given to changes in spatial patterns in CDPs during natural succession.Cyclobalanopsis glauca(Thunb.)Oerst.,Quercus variabilis Blume,and Pinus yunnanensis var.tenuifolia W.C.Cheng & Y.W.Law are canopy species that form CDPs in zonal forests along the Nanpan River in southwest China.We used the g(r) function and its bivariate distribution model,g_(12)(r),which is based on distances between pairs of points,to explore the dynamics of the three CDP species with respect to distribution patterns and spatial correlations in two secondary forests(one 30-year-old forest [30-YF] and one 57-year-old forest [57-YF]).The following key results were obtained:(1) there was a clumped pattern in the 30-YF,but the intensity of aggregation varied among populations and life stages.The distribution pattern gradually shifted to become random with longer succes sion time(i.e.,30-YF vs.57-YF),expansion of the observation scale(r=0-20 m),and at later life stages.(2) Aside from the mid-sized C.glauca trees and large P.yunnanensis trees,the trees repulsed each other at certain scales(r=0-2,5-6,11-12,14-16 m) in the 30-YF.Almost all of the life stages in the CDPs were independently correlated.This independent correlation was exacerbated by a longer succession time.(3) An increase in life stages and longer succession also promoted independent changes in intraspecific correlations.(4) Intraspecific correlations were stronger than interspecific correlations.Our results showed that reducing exclusive competition is essential to coexistence in CDPs.Inter-and intra-specific repulsion may occur at the same time,but intraspecific repulsion was the main driving force behind the random distributions and independent correlations.

Spatial distribution pattern of Picea schrenkiana population in the Middle Tianshan Mountains and the relationship with topographic attributes

The spatial distribution of plant populations is an important feature of population structure and it de- termines the population＇s ecological preferences, biological characteristics and relationships with environmental factors. The point pattern analysis method was adopted to study the distribution pattern of Picea schrenkiana indi- viduals of different size classes and the correlations between two size classes as well as the impact of topog- raphical attributes on the population distribution. With increasing diameter at breast height, the plant density of the P. schrenkiana population showed a declining trend. Old trees showed a random distribution at a small spatial scale （0-12 m）, whereas saplings, small trees and big trees all had an aggregated distribution at all scales. With the increase of tree age, the scales at which maximal aggregation occurred gradually increased and the aggregation strength decreased. At a small scale （0-16 m）, all size classes showed a negative correlation and the larger the difference between tree size, the more significant the negative correlation. The number of medium, big and old trees had a significantly positive correlation with elevations, whereas the number of saplings and small trees was not significantly correlated with elevations. The numbers of saplings, small and medium trees showed a significant positive correlation with slope gradient, whereas the number of big trees was not significantly correlated, and the number of old trees was negatively correlated with gradient. With the exception of old trees, saplings, small, me- dium and big trees showed negative correlations with convexity index. The study provides a theoretical basis for the conservation, rehabilitation and sustainable management of forest ecosystems in the Tianshan Mountains.

Spatial correlation-based characterization of acoustic emission signal-cloud in a granite sample by a cube clustering approach

To extract more in-depth information of acoustic emission(AE)signal-cloud in rock failure under triaxial compression,the spatial correlation of scattering AE events in a granite sample is effectively described by the cube-cluster model.First,the complete connection of the fracture network is regarded as a critical state.Then,according to the Hoshen-Kopelman(HK)algorithm,the real-time estimation of fracture con-nection is effectively made and a dichotomy between cube size and pore fraction is suggested to solve such a challenge of the one-to-one match between complete connection and cluster size.After,the 3D cube clusters are decomposed into orthogonal layer clusters,which are then transformed into the ellip-soid models.Correspondingly,the anisotropy evolution of fracture network could be visualized by three orthogonal ellipsoids and quantitatively described by aspect ratio.Besides,the other three quantities of centroid axis length,porosity,and fracture angle are analyzed to evaluate the evolution of cube cluster.The result shows the sample dilatancy is strongly correlated to four quantities of aspect ratio,centroid axis length,and porosity as well as fracture angle.Besides,the cube cluster model shows a potential pos-sibility to predict the evolution of fracture angle.So,the cube cluster model provides an in-depth view of spatial correlation to describe the AE signal-cloud.

Spatial Correlation and Ecological Characteristics Analysis of Man-agement Area for Biodiversity Conservation and Relevant Regionalization

Formulation of different ecological zone plans according to the corresponding protection targets and the necessity of proper conservation policy is one of the measures to achieve the goal of ecological conservation in China.In order to clarify the interrelation among key ecological zone plans,this paper carried out the research on spatial relation of priority areas of biodiversity conservation and three key ecological areas(key ecological function areas,key regions of ecological service function,national nature reserves)and the research on ecological conditions,based on multi-scale ecological spatial theme information,which incorporates elements like ecological quality and type,and by the aid of spatial information analysis and GIS modeling.The results showed a contrastively fine spatial consistency with 68.8%of priority areas of biodiversity conservation overlapping with three key ecological areas.Although the environment in priority areas of biodiversity conservation were in good conditions,protection pressure is also increasing,powerful supervision and protection should not be ignored.The environmental conditions in the overlapping areas,as a whole,were superior to those in the non-overlapping areas.Since two areas have different characteristics,targeted protection measures should be formulated based on this difference,which will be very important for biodiversity conservation in priority areas of biodiversity conservation.

A geometric Model for the Spatial Correlation of an Acoustic Vector Field in Surface-generated Noise

Spatial correlation of sound pressure and particle velocity of the surface noise in horizontally stratified media was demonstrated, with directional noise sources uniformly distributed on the ocean surface. In the evaluation of particle velocity, plane wave approximation was applied to each incident ray. Due to the equivalence of the sound source correlation property and its directivity, solutions for the spatial correlation of the field were transformed into the integration of the coherent function generated by a single directional source. As a typical horizontally stratified media, surface noise in a perfect waveguide was investigated. Correlation coefficients given by normal mode and geometric models show satisfactory agreement. Also, the normalized covariance between sound pressure and the vertical component of particle velocity is proportional to acoustic absorption coefficient, while that of the surface noise in semi-infinitely homogeneous space is zero.

SPATIAL CORRELATION ANALYSIS OF CROP YIELD IN THE MIDDLE AND WEST OF JILIN PROVINCE

In this paper,spatial correlation of crop yield in the middle and west of Jilin Province is analyzed by us-ing the method of geostatistics semivariogram,taking the NDVI of NOAA/AVHRR spectrum data as the regionalized vari-able,aiming to provide theory and practical basis for field sampling of crop yield estimation using remote sensing.The ratio of nugget variance and sill of semivariograms are 21.1% and 9.7% in the west and middle regions in Jilin Province respectively.This shows that the crop yields are spatially correlated.The degree and range of correlation are far different in the different situations.In the west test region,the range is 49.9 km and the sill is 0.00019.In the middle testre-gion,the range is 16.5 km and the sill is0.00453.The dissimilarity in the western test region is larger than that in the middle one.The range in which the correlation existed of the former is far larger than the later.Different character is tics of spatial correlation of crop yield are decided by the environmental factors.Samples for crop yield estimation should be extracted according to the characteristic of spatial distribution of crop yield to promote the efficiency of sampling.

NLoS Mitigation in ToA Localization Based on Spatial Correlation Filter and Iterative Minimum Residual

To mitigate the Non-Line-of-Sight (NLoS) error which seriously affects the localization accuracy and robustness in complex indoor environment,a novel Iterative Minimum Residual (IMR) based on the consistency hypothesis of the residual and the error is proposed in this paper.It chooses the best subset of measurements to calculate the coordinates of the unknown node by comparing the residuals obtained with different subsets of beacons.To reduce the time complexity of the IMR algorithm,Spatial Correlation Filter (SCF) is also proposed,which can remove the most serious NLoS distance with low calculation cost.Combined with the proposed SCF and IMR algorithm,nodes can be localized with high accuracy and low time complexity.Experimental results with real dataset demonstrate that the proposed algorithm can identify the NLoS range effectively with about 50% time cost of employing SCF only.

Spatial pattern analysis of forest trees based on the vectorial mark

Analysis of spatial patterns to describe the spatial correlation between a tree location and marks(i.e.,structural variables),can reveal stand history,population dynamics,competition and symbiosis.However,most studies of spatial patterns have concentrated on tree location and tree sizes rather than on crown asymmetry especially with direct analysis among marks characterizing facilitation and competition among of trees,and thus cannot reveal the cause of the distributions of tree locations and quantitative marks.To explore the spatial correlation among quantitative and vectorial marks and their implication on population dynamics,we extracted vertical and horizontal marks(tree height and crown projection area)characterizing tree size,and a vectorial mark(crown displacement vector characterizing the crown asymmetry)using an airborne laser scanning point cloud obtained from two forest stands in Oxfordshire,UK.Quantitatively and vectorially marked spatial patterns were developed,with corresponding null models established for a significance test.We analyzed eight types of univariate and bivariate spatial patterns,after first proposing four types.The accuracy of the pattern analysis based on an algorithm-segmented point cloud was compared with that of a truly segmented point cloud.The algorithm-segmented point cloud managed to detect 70–86%of patterns correctly.The eight types of spatial patterns analyzed the spatial distribution of trees,the spatial correlation between tree size and facilitated or competitive interactions of sycamore and other species.These four types of univariate patterns jointly showed that,at smaller scales,the trees tend to be clustered,and taller,with larger crowns due to the detected facilitations among trees in the study area.The four types of bivariate patterns found that at smaller scales there are taller trees and more facilitation among sycamore and other species,while crown size is mostly homogeneous across scales.These results indicate that interspecific facilitation and competition mainly affect tree height in the study area.This work further confirms the connection of tree size with individual facilitation and competition,revealing the potential spatial structure that previously was hard to detect.

Low spatial correlation at base station uniform linear antennas

A spatial channel propagation model is presented. Consider a uniform linear antenna （ULA） at the base station （BS） and narrowband signals transmitted at the mobile. In two types of propagating environments： indoor and outdoor, performance of low spatial correlation is investigated and some results are provided, which are significant to an,3. lyze the performance of diversity systems and configuration of army. The results also show that the configuration of array with either smaller angular spread or bigger angle of arrival （AOA） dominates the impact on spatial correlation, and that increasing angular spread or decreasing AOA diminishes, or even eliminates this impact.

Quantitative assessment of the spatio-temporal correlations of seismic events induced by longwall coal mining

Rock failure process as a natural response to mining activities is associated with seismic events, which can pose a potential hazard to mine operators, equipment and infrastructures. Mining-induced seismicity has been found to be internally correlated in both time and space domains as a result of rock fracturing during progressive mining activities. Understanding the spatio-temporal(ST) correlation of mininginduced seismic events is an essential step to use seismic data for further analysis, such as rockburst prediction and caving assessment. However, there are no established methods to perform this critical task. Input parameters used for the prediction of seismic hazards, such as the time window of past data and effective prediction distance, are determined based on site-specific experience without statistical or physical reasons to support. Therefore, the accuracy of current seismic prediction methods is largely constrained, which can only be addressed by quantitively assessing the ST correlations of mininginduced seismicity. In this research, the ST correlation of seismic event energy collected from a study mine is quantitatively analysed using various statistical methods, including autocorrelation function(ACF), semivariogram and Moran’s I analysis. In addition, based on the integrated ST correlation assessment, seismic events are further classified into seven clusters, so as to assess the correlations within individual clusters. The correlation of seismic events is found to be quantitatively assessable, and their correlations may vary throughout the mineral extraction process.

Does Foreign Direct Investment Affect S0_(2) Emissions in the Yangtze River Delta?A Spatial Econometric Analysis

As the major source of air pollution,sulfur dioxide(S0_(2))emissions have become the focus of global attention.However,existing studies rarely consider spatial effects when discussing the relationship between foreign direct investment(FDI)and S0_(2) emissions.This study took the Yangtze River Delta as the research area and used the spatial panel data of 26 cities in this region for 2004-2017.The study investigated the spatial agglomeration effects and dynamics at work in FDI and S0_(2) emissions by using global and local measures of spatial autocorrelation.Then,based on regression analysis using a results of traditional ordinary least squares(OLS)model and a spatial econometric model,the spatial Durbin model(SDM)with spatial-time effects was adopted to quantify the impact of FDI on S0_(2) emissions,so as to avoid the regression results bias caused by ignoring the spatial effects.The results revealed a significant spatial autocorrelation between FDI and S0_(2) emissions,both of which displayed obvious path dependence characteristics in their geographical distribution.A series of agglomeration regions were observed on the spatial scale.The estimation results of the SDM showed that FDI inflow promoted S0_(2) emissions,which supports the pollution haven hypothesis.The findings of this study are significant in the prevention and control of air pollution in the Yangtze River Delta.

Single foggy image restoration based on spatial correlation analysis of dark channel prior

Focusing on the degradation of foggy images, a restora- tion approach from a single image based on spatial correlation of dark channel prior is proposed. Firstly, the transmission of each pixel is estimated by the spatial correlation of dark channel prior. Secondly, a degradation model is utilized to restore the foggy image. Thirdly, the final recovered image, with enhanced contrast, is obtained by performing a post-processing technique based on just-noticeable difference. Experimental results demonstrate that the information of a foggy image can be recovered perfectly by the proposed method, even in the case of the abrupt depth changing scene.