Spatial pattern recognition for near-surface high temperature increases in mountain areas using MODIS and SRTM DEM

Abrupt near-surface temperature changes in mountainous areas are a special component of the mountain climate system.Fast and accurate measurements of the locations,intensity,and width of the near-surface changes are necessary but highly difficult due to the complicated environmental conditions and instrumental issues.This paper develops a spatial pattern recognition method to measure the near-surface high temperature increase(NSHTI),one of the lesser-attended changes.First,raster window measurement was proposed to calculate the temperature lapse rate using MODIS land surface temperature and SRTM DEM data.It fully considers the terrain heights of two neighboring cells on opposite or adjacent slopes with a moving window of 3×3 cell size.Second,a threshold selection was performed to identify the NSHTI cells using a threshold of-0.65℃/100 m.Then,the NSHTI strips were parameterized through raster vectorization and spatial analysis.Taking Yunnan,a mountainous province in southwestern China,as the study area,the results indicate that the NSHTI cells concentrate in a strip-like pattern along the mountains and valleys,and the strips are almost parallel to the altitude contours with a slight northward uplift.Also,they are located mostly at a 3/5 height of high mountains or within 400 m from the valley floors,where the controlling topographic index is the altitude of the terrain trend surface but not the absolute elevation and the topographic uplift height and cutting depth.Additionally,the NSHTI intensity varies with the geographic locations and the proportions increase with an exponential trend,and the horizontal width has a mean of about 1000 m and a maximum of over 5000 m.The result demonstrates that the proposed method can effectively recognize NSHTI boundaries over mountains,providing support for the modeling of weather and climate systems and the development of mountain resources.

Optimizing Spatial Pattern Analysis in Serial Remote Sensing Images through Empirical Mode Decomposition and Ant Colony Optimization

Serial remote sensing images offer a valuable means of tracking the evolutionary changes and growth of a specific geographical area over time.Although the original images may provide limited insights,they harbor considerable potential for identifying clusters and patterns.The aggregation of these serial remote sensing images(SRSI)becomes increasingly viable as distinct patterns emerge in diverse scenarios,such as suburbanization,the expansion of native flora,and agricultural activities.In a novel approach,we propose an innovative method for extracting sequential patterns by combining Ant Colony Optimization(ACD)and Empirical Mode Decomposition(EMD).This integration of the newly developed EMD and ACO techniques proves remarkably effective in identifying the most significant characteristic features within serial remote sensing images,guided by specific criteria.Our findings highlight a substantial improvement in the efficiency of sequential pattern mining through the application of this unique hybrid method,seamlessly integrating EMD and ACO for feature selection.This study exposes the potential of our innovative methodology,particularly in the realms of urbanization,native vegetation expansion,and agricultural activities.

Evaluation of COVID-19 Cases and Vaccinations in the State of Georgia, United States: A Spatial Perspective

This study evaluates the distribution of COVID-19 cases and mass vaccination campaigns from January 2020 to April 2023. There are over 235,000 COVID-19 cases and over 733,000 vaccinations across the 159 counties in the state of Georgia. Data on COVID-19 was acquired from usafact.org while the vaccination records were obtained from COVID-19 vaccination tracker. The spatial patterns across the counties were analyzed using spatial statistical techniques which include both global and local spatial autocorrelation. The study further evaluates the effect of vaccination and selected socio-economic predictors on COVID-19 cases across the study area. The result of hotspot analysis reveals that the epicenters of COVID-19 are distributed across Cobb, Fulton, Gwinnett, and DeKalb counties. It was also affirmed that the vaccination records followed the same pattern as COVID-19 cases’ epicenters. The result of the spatial error model performed well and accounted for a considerable percentage of the regression with an adjusted R squared of 0.68, Akaike Information Criterion (AIC) 387.682 and Breusch-Pagan of 9.8091. ESDA was employed to select the main explanatory variables. The selected variables include vaccination, population density, percentage of people that do not have health insurance, black race, Hispanic and these variables accounted for 68% of the number of COVID-19 cases in the state of Georgia during the study period. The study concludes that both COVID-19 cases and vaccinated individuals have spatial peculiarities across counties in Georgia state. Lastly, socio-economic variables and vaccination are very important to reduce the vulnerability of individuals to COVID-19 disease.

Effect of Quadrat Shape on Spatial Point Pattern Performance of Haloxylon ammodendron

In this study, we investigated the natural growth of Haloxylon ammodendron forest in Moso Bay, southwest of Gurbantunggut Desert. Random sample analysis was used to analyze the spatial point pattern performance of Haloxylon ammodendron population. ArcGIS software was used to summarize and analyze the spatial point pattern response of Haloxylon ammodendron population. The results showed that: 1) There were significant differences in the performance of point pattern analysis among different random quadrants. The paired t-test for variance mean ratio showed that the P values were 0.048, 0.004 and 0.301 respectively, indicating that the influence of quadrat shape on the performance of point pattern analysis was significant under the condition of the same optimal quadrat area. 2) The comparative analysis of square shapes shows that circular square is the best, square and regular hexagonal square are the second, and there is no significant difference between square and regular hexagonal square. 3) The number of samples plays a decisive role in spatial point pattern analysis. Insufficient sample size will lead to unstable results. With the increase of the number of samples to more than 120, the V value and P value curves will eventually stabilize. That is, stable spatial point pattern analysis results are closely related to the increase of the number of samples in random sample square analysis.

Noise control and utility:From regulatory network to spatial patterning

Stochasticity(or noise) at cellular and molecular levels has been observed extensively as a universal feature for living systems. However, how living systems deal with noise while performing desirable biological functions remains a major mystery. Regulatory network configurations, such as their topology and timescale, are shown to be critical in attenuating noise, and noise is also found to facilitate cell fate decision. Here we review major recent findings on noise attenuation through regulatory control, the benefit of noise via noise-induced cellular plasticity during developmental patterning and summarize key principles underlying noise control.

Spatial patterns of Picea crassifolia driven by environmental heterogeneity and intraspecifi c interactions

Research on the spatial patterns of tree populations is critical for understanding the structure and dynamic processes of forests.However,little is known about how the underlying drivers shape these patterns and species interactions in forest systems.In this study,spatial point pattern analysis investigated the combined eff ects of intraspecifi c interactions and environmental heterogeneity on the spatial structure and internal maintenance mechanisms of Picea crassifolia in the Qilian Mountain National Nature Reserve,China.Data were obtained from a 10.2-ha dynamic monitoring plot(DMP)and sixteen 0.04-ha elevation gradient plots(EGPs).Under complete spatial randomness,both mature trees and saplings in the DMP demonstratedlarge-scale aggregation with negative correlations.In EGPs,saplings were clustered in small mesoscales,mature trees were randomly distributed,and the interactions of saplingstrees at all elevations were not correlated.By eliminating the interference of environmental heterogeneity through the inhomogeneous Poisson process,saplings in the DMP and EGPs were clustered in small scales and trees randomly distributed.Intraspecifi c associations were negatively correlated,in the DMP and at low elevations,and no correlations in high elevations of EGPs.In the vertical scale,saplings showed a small-scale aggregation pattern with increase in elevation,and the aggregation degree fi rst decreased and then increased.The interactions of saplings-trees and saplings–saplings showed inhibitions at small scales,with the degree of inhibition gradually decreasing.Spatial patterns and associations of adults–adults did not change signifi-cantly.The results revealed that intraspecifi c interactions and environmental heterogeneity regulated the spatial patterns of P.crassifolia at small and large scales,respectively.Environmental heterogeneity might be the most decisive factor aff ecting the spatial patterns of saplings,while trees were more aff ected by intraspecifi c interactions.Moreover,competition between trees in this area could be more common than facilitation for the growth and development of individuals.

Spatial patterns of the main trees in a plant micro-reserve constructed in the 2022 Beijing Winter Olympics mountainous competition zone

Several plant micro-reserves were established to preserve the vegetation in local mountain areas during the construction of the Yanqing competition zone of the 2022 Beijing Winter Olympics.The spatial patterns of the main species in one of the micro-reserves and the factors affecting these patterns were characterized in this study.The distribution of arbor species was found to be mostly aggregated,especially at fine scales(<5 m).Minor species were found to be more aggregated than the major species in each forest layer.The spatial patterns were found to be affected by habitat heterogeneity,intraspecific relationships,interspecific competition,and seed dispersal limitation.Habitat heterogeneity was found to affect large-scale spatial patterns,and its effects were observed throughout population development.Interspecific competition is another factor affecting the distribution of the species,and its effects were stronger during the later stages of population development.Habitat heterogeneity was found to affect competition among species and is key for species coexistence.Both these processes are affected by the seed dispersal limitation,and intraspecific relationships are a legacy of seed dispersal.The point patterns can be used as a tool for the initial assessment of the status of communities within micro-reserves.The consideration of these relationships in the development,management,and formulation of policies for micro-reserves in mountainous areas will facilitate the achievement of conservation goals.The careful consideration of habitat conditions when selecting sites for micro-reserves establishment can promote species conservation.

Classification and Spatial Pattern of Township Development in Liaoning Province, China

The classification of township development types is an urgent problem that requires solution to enable the township to choose an appropriate development path.Using a township development classification method,we determine the township development types and their spatial patterns in Liaoning Province,China.The results showed that the patterns of township development types based on their general advantages had significant spatial differentiations.The planting,and livestock and poultry breeding township development types based on general advantages were mainly distributed across the central plain of Liaoning Province,China,and also concentrated in Dandong City−Dalian City along Yellow Sea coast,and in the northwest of Chaoyang City.The business and tourism,industry and mining,and residence township development types based on general advantages were distributed mainly along the Shenyang–Dalian Economic Belt in the central and southern Liaoning Province.The ecology township development type based on general advantages was mainly distributed in the eastern and western Liaoning Province to maintain regional ecological security.Township development types based on non-advantages were sporadically distributed in the middle and western Liaoning Province.Based on the classification and spatial patterns,the differences between the distribution of twonship development types and the plan for the major functional areas of Liaoning Province were proposed which could provide the basis for the optimization of the major functional areas.

Spatial Pattern and Distribution of Crime in Suleja Lga, Niger State, Nigeria

The study examines the Spatial Pattern and Distribution of Crime in Suleja LGA, Niger State, Nigeria. The study used GIS and statistical methods to analyse the pattern and distribution of crime incidence in the study area. The records of each crime incidence were geocoded. Microsoft Excel was used to collate and organise the crime entries before they were imported into the ArcGIS Pro 2.0 environment. A geodatabase was created where the spatial and aspatial data were encoded and geospatial analysis was performed. The study reveals that the crime distribution pattern is generally clustered with a Global Moran’s I index of 0.097, a Z-score of 1.87, and a P-value < 0.06. Furthermore, the study reveals that armed robbery (61), kidnapping (40), car theft (33), culpable homicide (31), rape (29), and robbery (13) cases rank the highest in crime rate. Equally, findings of the study show that Chaza, Kwamba, Madalla, Suleja central, and Gaboda are the major crime hotspot zones at 90% confidence, as analysed using the Getis-Ord Gi* (Hot spot analysis) spatial statistics tool in ArcGIS Pro 2.0. The research therefore recommends that more effort be put into fighting crime, especially in areas where there are low-security formations, as they mostly have the highest record of crimes committed. Also, the patrol units should be equipped with GPS for better surveillance and real-time tracking of criminal activities.

Effect of arsenic on spatial pattern of radial oxygen loss and iron plaque formation in rice

The effects of different arsenic （As） treatments on spatial pattern of radial oxygen loss （ROL）, iron （Fe） plaque formation and As accumulation in rice were investigated using three rice genotypes, planted under greenhouse conditions. Arsenic was applied to soil at 50 and 100 mg/kg, with untreated soil used as a control having an average As concentration of 8.5 mg/kg. It was demonstrated that the ratio of ROL in root tips to that at the root base slightly decreased with increasing As concentration, suggesting that the spatial ROL patterns in these groups may be shifted from the “tight” barrier towards the “partial” barrier form. Furthermore, increasing As concentration led to a increase in Fe plaque formation on root surfaces. In addition, root As concentrations of genotypes in 50 and 100 mg/kg As treatments were significantly higher than that of control treatment （P〈0.05）. Grain As concentration of genotype Nanyangzhan （with lower ROL） was significantly higher （P〈0.05） than that of genotype CNT87059-3 with higher ROL.

Spatial Pattern and Process of Urbanization in Karst Area——A Case Study in Guiyang City

ObjectiveKarst area is one of ecological fragile regions in China, where the economic and social development is lagged heavily. In recent years, with the constant development of the west regions, economy and society are developed rapidly and urbanization speed is accelerated. This study aims to investigate the spatial pattern and process of urbanization in karst area of Guiyang City, which has important significance for land management and urban planning in karst area. MethodBased on RS and GIS technologies, TM satellite images in 1986, 1995 and 2000 and CBERS-01 satellite image in 2006 were adopted to obtain the data of urban land utilization in Guiyang City in the four years. The spatial pattern and process of urbanization in Guiyang City were investigated using urbanization proportion index （UPI）, urbanization intensity index （UII） and absolute expansion intensity （AEI）. ResultThe urbanization process in Guiyang City was significant, exhibiting polygon-urbanization, line-urbanization and point-urbanization. From the perspective of spatial pattern, the urbanization in Guiyang City displayed the cluster development; from the perspective of urbanization process, the urbanization speed in some secondary central areas was higher than that of central areas. ConclusionThe spatial pattern and process of urbanization in karst area were unique and were mainly influenced by terrain, transportation, economy, society and so on.

Factors affecting land dissection density in geomorphological regions of China

Land dissection density(LDD)provides morphological evidence regarding prior intense soil erosion and quantifies the distribution of land dissections.A comprehensive understanding of the potential factors influencing the spatial pattern and value of the LDD is vital in geological disasters,soil erosion,and other related domains.Land dissection phenomena in China affects large areas with different morphological,pedological,and climatic characteristics.Prior studies have focused on the potential factors influencing the LDD at a watershed scale.However,these results are insufficient to reflect the status quo of dissection development and its primary influencing factors on a national scale.LDD’s spatial patterns and the dominant factors at a regional scale in millions of square kilometers remain to be ascertained.This study used the geomorphon-based method and the geographical detector model to quantify the spatial pattern of LDD over China and identify the dominant factors affecting this pattern in China’s six first-order geomorphological regions(GR1~GR6).The results yield the following findings:(1)LDD in China ranges from 0~4.55 km/km^(2),which is larger in central and eastern regions than in other regions of China;(2)dominant factors and their dominant risk subcategories vary with each geomorphological region’s primary internal and external forces;(3)the influence of natural factors is more significant on the large regional scale in millions of square kilometers compared to anthropogenic factors;relief degree of land surface(RDLS)is dominant in GR1,GR2,and GR5;the slope is dominant in GR6,soil type is dominant in GR3 and GR4,and lithology plays a critical role in the dominant interactions of GR3,GR4,and GR6;(4)the interactions between factors on LDD’s spatial pattern have a more significant effect than individual factors.

Examining the Spatiotemporal Dynamics and Determinants of Land Urbanization in Prefecture-level Cities,China

Examining the spatiotemporal dynamics and determinants of land urbanization is critical for promoting healthy urban development and the rational use of land resources.Based on the dataset consisting of land use change data and selected factors in 2010 and2020,this study used visual analysis to reveal the spatiotemporal dynamics of land urbanization across prefecture-level cities in China.Meanwhile,the driving forces underlying land urbanization were examined by using geographical detector technique.Following are the findings:1)we find that there exist notable spatial variances in land urbanization across prefecture-level cities.Currently,the differentiation in land urbanization between the northern and southern cities is more pronounced than that between the coastal and inland cities,or between the eastern and western cities.Prefecture-level cities located in central and western China have experienced the most rapid growth in land urbanization.Conversely,the growth rate in northeastern China is the lowest,while the velocity in eastern China remains relatively stable.By using spatial autocorrelation analysis,this study reveals that the land urbanization level in prefecture-level cities has significant spatial agglomeration.2)We further find that land urbanization in China is influenced by factors related to urban land supply and demand,and urban population growth,economic growth,land financial and political incentive have greater impact on land urbanization than other factors.3)We also find that the impacts of determinants on China’s land urbanization vary over time,the explanatory power of economic development increased,while the explanatory power of state forces declined.We argue that integrating the supply and demand factors of land urbanization can provide a more comprehensive understanding of the driving mechanisms underlying land urbanization in China and other transitional countries,and help decision-makers in these countries formulate more detailed and specific land urbanization policies.

Migration Networks Pattern of China’s Floating Population from the Perspective of Complex Network

Since China’s reform and opening-up,the growing disparity between urban and rural areas and regions has led to massive migration.With China’s Rural Revitalization Strategy and the industrial transfer from the eastern coastal areas to the inland,the migration direction and pattern of the floating population have undergone certain changes.Using the 2017 China Migrants Dynamic Survey(CMDS),excluding Hong Kong,Macao,and Taiwan regions of China,organized by China’s National Health Commission,the relationship matrix of the floating population is constructed according to the inflow place of the interviewees and their outflow place(the location of the registered residence)in the questionnaire survey.We then apply the complex network model to analyze the migration direction and network pattern of China’s floating population from the city scale.The migration network shows an obvious hierarchical agglomeration.The first-,second-,third-and fourth-tier distribution cities are municipalities directly under the central government,provincial capital cities,major cities in the central and western regions and ordinary cities in all provinces,respectively.The migration trend is from the central and western regions to the eastern coastal areas.The migration network has‘small world’characteristics,forming nine communities.It shows that most node cities in the same community are closely linked and geographically close,indicating that the migration network of floating population is still affected by geographical proximity.Narrowing the urban-rural and regional differences will promote the rational distribution this population.It is necessary to strengthen the reform of the registered residence system,so that the floating population can enjoy urban public services comparable to other populations,and allow migrants to live and work in peace.

地理大数据揭示中国主要城市建成环境物质存量的空间格局

The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important,yet hitherto largely missing stock perspective for facilitating urban system engineering and informing urban resources,waste,and climate strategies.However,our existing knowledge on the patterns of built environment stocks across and particularly within cities is limited,largely owing to the lack of sufficient high spatial resolution data.This study leveraged multi-source big geodata,machine learning,and bottom-up stock accounting to characterize the built environment stocks of 50 cities in China at 500 m fine-grained levels.The per capita built environment stock of many cities(261 tonnes per capita on average)is close to that in western cities,despite considerable disparities across cities owing to their varying socioeconomic,geomorphology,and urban form characteristics.This is mainly owing to the construction boom and the building and infrastructure-driven economy of China in the past decades.China’s urban expansion tends to be more“vertical”(with high-rise buildings)than“horizontal”(with expanded road networks).It trades skylines for space,and reflects a concentration-dispersion-concentration pathway for spatialized built environment stocks development within cities in China.These results shed light on future urbanization in developing cities,inform spatial planning,and support circular and low-carbon transitions in cities.

Spatial pattern of dominant tree species of the secondary monsoon rain forest in Lianjiang, Guangdong Province

Based on the summed dominance ratios of species in sample plots, the first three dominant species (Litchi chinensis, Elaeocarpus sylvestris and Canarium album) of the secondary monsoon rain forest of Mt. Royal Shoe in Lianjiang City, western Guangdong, were chosen for analyzing their spatial distribution pattern with the analysis methods such as frequency models of Poisson Distribution, Two Negative Items Distribution, Neyman Distribution, aggregate indexes, Taylor exponential equation and Iwao’s equation modeling. The results showed that these three species distributed in the congregate spatial pattern. Litchi chinensis and Elaeocarpus sylvestris had the characteristic of basic congregate population and attractive characteristic between their plants. The patterns for Canarium album may change and become more evenly distributed with the increase of density. The overall species spatial pattern also depended on the conservation of the secondary monsoon rain forest besides it was affected by the species reproduction characteristics and its growing environment. The congregate spatial patterns of three dominant species showed that it is important to conserve forest urgent conservation of the forest.

Study on the Spatiotemporal Pattern Evolution and Influencing Factors of Population Aging in Henan Province

This study utilized census data from Henan Province for the years 2000,2010,and 2020 to investigate the spatiotemporal evolution of population aging,defined by the proportion of the population aged 65 and above.Employing spatial analysis techniques such as spatial autocorrelation and the standard deviation ellipse,the research mapped out the progression and distribution of aging demographics.Furthermore,the study delved into the influencing factors of aging using an optimal parameters-based geographical detector.Results indicate a deepening degree of population aging in Henan Province,transitioning from an adult type to an old type structure.There is a marked positive spatial correlation among counties,with high-value aging areas initially decreasing,then increasing,and notably spreading from the central to the central and southern regions of the province.The center of gravity for population aging,specifically around Changge City and Xuchang City,exhibits a trajectory moving southeast before shifting northwest.Factor detection reveals that in 2000,2010,and 2020,the elderly dependency ratio predominantly influences the aging trend,with explanatory powers of 88.4%,87.9%,and 90.9%,respectively.Interaction analysis indicates that the interaction between the old-child ratio and the elderly dependency ratio has a strong explanatory power for the aging patterns in Henan Province,reaching 97.3%,97.0%,and 97.4%,respectively.

Geostatistical Analysis on Spatial Patterns of Eggs and Larvae of Kytorhinus immixtus

[ Objective ] The paper was to study the spatial distribution pattern and spatial correlation of eggs and larvae of Kytorhinus immixtus. [ Method ] By using geostatistical principles and methods, the number of eggs and larvae ofK. immixtus was investigated, and the obtained data were analyzed. [Result]The cir- cular model was the best fitting model for eggs and larvae of/C immixtus, and the spatial distribution pattern was aggregated distribution with a spatial correlation, and their variation ranges were 18.899 -62.922 and 13.464 -47.455. The distribution pattern of eggs and larvae of K.immistus was simulated by using ordinary Kriging method, and the result showed that their distributions had obvious agitated character, the aggregated intensity in the core area of patch was significantly higher than that in the edge. There was anisotropy of aggregation intensity, the aggregation intensity from northeast to southwest direction was significantly higher than that from northwest to southeast direction. [ Conclusion] The spatial distribution pattern of eggs and larvae of K. immixtus was aggregated distribution, and the increase of plant distance and fragmentation of patch had a certain control effect on the occurrence of K. immixtus population.

Spatial Distribution Pattern and Application of Fourth-Generation Mature Larvae of Cotton Bollworm(Helicoverpa armigera Hübner) in Corn Field

[ Objective] The paper was to study the spatial distribution pattern of fourth-generation mature larvae of cotton bellworm in corn field. [ Method] The plots with different occurrence densities of fourth-generation cotton bollworm were investigated from August to September in 2009. Six groups of sampling data were obtained, and seven indicators including aggregation index method, Iwao method and Taylor method, etc. were used to determine its spatial distribution pattern. [ Result ] Aggregation index test showed that in all plots, Moore I 〈 0, Lloyed m＊/m 〈 1, Kuno Ca 〈 0, diffusion coefficient C 〈 1, diffusion index 16 〈 1, negative binomial distribution K 〈 0, indicating that mature larvae of cotton bollworm showed uniform distribution in summer corn. Iwae regression equation of fourth-genera- tion mature larvae of cotton boUworm in summer corn was m ＊ = 0. 090 6 ＋ 0. 766 9 m, r = 0. 986 3, indicating that the basic components of cotton bollworm distribu- ted was single individual, and mature larvae of cotton bollworm in summer corn showed uniform distribution. The optimal sampling number of fourth-generation ma- ture larvae of cotton bollworm in corn under different population densities could be calculated using formula N1 = （ 1. 090 6/m -0. 233 1 ）/D2. [ Conclusion] The result provided basis for accurate evaluation of population quantities and variation law of cotton boUworm, as well as prediction and control of the pest.

Preliminary Study on Spatial Distribution Pattern of Endoclyta signifer Walker Larva

[ Objective ] The paper was to study the spatial distribution of Endoclyta signifer Walker Larva. [ Method] The larvae distribution in eucalyptus planta- tion in Beiliu and Luchuan counties of Guangxi province were investigated. Ten standard plots were set, and the spatial distribution pattern of E. signifer larva was confirmed using six different aggregation indexes and regression model analysis method. [ Result] The larvae mainly distributed in the base of tnmk lower than 1 m, and its spatial distribution pattern was mainly aggregated distribution, which was caused by the enviromnental factors. The optimum sampling formula of E. signifer larva under different population densities was n = t2 （ 1.1/m ＋ 0. 674 4）/D2, and limited sequential sampling decision model was T＇0（n）, T＇0（n） = n ＋ 1. 332√n（ m0 = 1 ）. [ Conclusion] The result provided scientific basis for sampling and forecasting of E. signifier.