Temporal and spatial distribution of spending in the city using bank cards transactions

In view of the difficulty in giving a quantitative description of the degree of uneven distribution of water resources, this paper, based on a cloud model, explores the temporal and spatial distribution characteristics of water resources in some research areas in Guangdong Province by using quantitative methods. The results show that, firstly, cloud images of a cloud model make it possible to describe intuitively the characteristics of the temporal and spatial distribution of water resources and present the differences of these characteristics in different areas through numerical characteristic values. Secondly, there are the least amounts of water resources in western Guangdong and the most in the Pearl River Delta Area. Temporal allocation of water resources is difficult in the northern and eastern parts of this province while spatial allocation difficult in the eastern and western parts. Thirdly, there are more water resources, less non-uniformity in the temporal distribution, greater stability in terms of temporal and spatial distribution but greater non-uniformity in the spatial distribution of water resources in the downstream than upstream of the Pearl River in Guangdong Province. Fourthly, there is less non-uniformity in the spatial distribution than in the temporal distribution in northern Guangdong while stability of spatial distribution is worse than that of the temporal distribution in western Guangdong. In addition, there is less uniformity but greater stability in the spatial distribution than in the temporal distribution of water resources in each research area.

The spatial and temporal distribution, species composition, and host preference of phlebotomine sand flies in the Bethlehem District of Palestine

<p>Agriculture is an essential driving force in the management of water resources in Mediterranean countries as it has a dominant role in sustaining the growth of rural areas and at the same time represents by far the major water consumer. However, detailed assessment of the irrigation water requirements spatial and temporal distribution is challenging in the case of poorly gauged regions and especially in countries characterized by vast spatial and temporal variability like Greece, as water absractions in agriculture are spatially scattered, various water sources are used in each field, and the corresponding monitoring infrastructure is scarce.</p><p>This study presents a modelling approach for the assessment of irrigation water requirements spatial and temporal distribution in Greece on the basis of farm structure survey data, annual crop statistics and meteorological data. The proposed methodology is using an entirely spatially distributed, continuous hydrological model, in order to estimate the spatial distribution of the hydrological balance components at every point of the studied region as well as plants water deficit, and irrigation water requirements in a daily time step for the entire country. The developed approach is directly relevant to agricultural water policies design and evaluation. A special algorithm that is able to link each farm parcel polygon (over 6,000,000 polygons) of the spatial database of the Integrated Administration and Control System (IACS) with the nearest corresponding grid cell of the model was also developed. In this way, the developed approach utilizes all the information included in the IACS database (e.g. irrigation system, water source, applied agri-environmental measures) and provides very precise information at farm parcel level facilitating further analysis. Remote sensing data (Sentinel-Copernicus) and methods were also used for the validation of the crop patterns and of the irrigated fields in IACS database. The model was applied for 34 years reference period (1971-2004) at a daily time step. The obtained results were analyzed to identify spatial patterns and relationships, to investigate the temporal variability and the presence of trends and to provide detailed information on the water requirements of various crops and regions providing valuable information concerning agricultural water management.</p>

Larvae of Phyllophaga spp. (Coleoptera: Scarabaeidae) are important direct and indirect turfgrass pests in the southern United States. Confirming the presence of these larvae is an important integrated pest management practice in turf production systems and determines the need for treatment. However, several different species (e.g., P. crinita, P. submucida, and P. crassissima) are known to occur within the same turfgrass stand, and each species has a different oviposition period. The objective of this study was to determine the spatial and temporal distribution of Phyllophaga spp. in intensely managed bermudagrass. During spring through summer of 2009, larvae were collected after harvesting bermudagrass turf from two sod farms in Oklahoma. The location of each grub was determined using global positioning system tracking. Identification of larvae was based on polymerase chain reaction amplification and sequencing of the cytochrome c oxidase I gene. Species spatial and temporal distribution patterns were analyzed by detrended correspondence analysis using CANOCO 5.04. Seven species of Phyllophaga were collected, and each study site contained at least one species that was not found at the other. Detrended correspondence analysis resulted in low β diversity values. Beta diversity reflects how far apart species are in the gradient of species composition. The low β diversity scores obtained in this study show that different species of Phyllophaga were present in no recognizable pattern of temporal or spatial distribution.

BackgroundThe subtypes diagnosis of disease symptom clusters, grounded in the theory of “Treatment in Accordance with Three Categories of Etiologic Factors” and International Classification of Diseases 11th Revision (ICD-11), is a vital strategy for Chinese Medicine (CM) in treating unknown respiratory infectious diseases. However, the classification of disease symptom clusters continues to depend on empirical observations and lacks robust scientific evidence. Consequently, this study seeks to explore the temporal, spatial and demographic distributions characteristics of Corona Virus Disease 2019 (COVID-19) symptom clusters in China.MethodsPubMed, Web of Science, Science direct, WHO, Litcovid, CNKI databases were searched from inception until December 31, 2023. Optical character recognition technology and image recognition technology were employed to identify tables within the papers. Four researchers independently screened and extracted data, resolving conflicts through discussion. Heat mapping and hierarchical clustering techniques were utilized to analyze COVID-19 symptom clusters. Data analysis and visualization were conducted using R software (4.2.0), while the association analysis of symptom clusters was performed using Cytoscape (3.10.2).ResultsA total of 366 COVID-19 clinical trials with 86,972 cases including 66 clinical symptoms of 7 disease systems and other clinical manifestations in China were included. In temporal distribution, 63 symptoms centered around fatigue and 44 symptoms focused on chest tightness are characteristic of symptom clusters in spring and winter, respectively. With the addition of spatial distribution, the symptom clusters in middle and low latitudes during spring are characterized by 53 symptoms centered around fatigue and cough, and 51 symptoms focused on fatigue, respectively. During winter, the symptom clusters in middle and low latitudes are characterized by 38 symptoms centered around chest tightness and 37 symptoms focused on fever, respectively. When considering demographic distribution, the symptom clusters for < 50 years are characterized by fatigue as the core symptom in middle (44 symptoms)/low (28 symptoms) latitudes during spring and middle latitude (25 symptoms) during winter. For ≥ 50 years, the symptom clusters in middle latitude (49 symptoms) during spring and low latitudes (35 symptoms) during winter are centered around cough, while in low latitude (27 symptoms) focuses on diarrhea during spring, and middle latitude (35 symptoms) emphasizes both diarrhea and chest tightness during winter.ConclusionIn summary, variations in symptom clusters and core symptoms of COVID-19 in temporal, spatial and demographic distributions in China offer a scientific rationale for the “Treatment in Accordance with Three Categories of Etiologic Factors” theory. These interesting findings prompt further investigation into CM patterns in the ICD-11, and suggest potential strategies for personalized precision treatment of COVID-19. High-quality clinical studies focusing on individual symptoms are warranted to enhance understanding of respiratory infectious diseases.

Understanding the temporal and spatial distribution characteristics of the cultural heritage of the Yellow River Basin can effectively improve the scientific understanding of the historical changes, environmental evolution, and cultural and economic development of the Yellow River Basin and thus provide a scientific and reasonable decision-making basis for the protection and development of its cultural heritage. The research object of this paper are the national cultural relic protection units. These are examined using the GIS spatial analysis method to explore the spatial and temporal distribution characteristics and spatial structure of 2,102 national material cultural heritage sites in the Yellow River basin. The results show that the spatial distribution of cultural heritage has a significant spatial agglomeration effect. The whole basin is concentrated in stable high- and low-value areas, and the difference between the high- and low-value areas is clear. Some aspects of the spatial structure heterogeneity are strong, showing a low value dispersion distribution trend. In different periods, the distribution direction and scope of cultural heritage have low ranges of rotation, a clear direction, and a high degree of centripetal distribution. The spatial and temporal distribution of cultural heritage is the result of the combined action of natural geographical environment such as climate change, topography, river hydrology, and human environment such as administrative institutional changes, ideological evolution, and social and economic development.

Understanding the temporal and spatial distribution characteristics of the cultural heritage of the Yellow River Basin can effectively improve the scientific understanding of the historical changes, environmental evolution, and cultural and economic development of the Yellow River Basin and thus provide a scientific and reasonable decision-making basis for the protection and development of its cultural heritage. The research object of this paper are the national cultural relic protection units. These are examined using the GIS spatial analysis method to explore the spatial and temporal distribution characteristics and spatial structure of 2,102 national material cultural heritage sites in the Yellow River basin. The results show that the spatial distribution of cultural heritage has a significant spatial agglomeration effect. The whole basin is concentrated in stable high- and low-value areas, and the difference between the high- and low-value areas is clear. Some aspects of the spatial structure heterogeneity are strong, showing a low value dispersion distribution trend. In different periods, the distribution direction and scope of cultural heritage have low ranges of rotation, a clear direction, and a high degree of centripetal distribution. The spatial and temporal distribution of cultural heritage is the result of the combined action of natural geographical environment such as climate change, topography, river hydrology, and human environment such as administrative institutional changes, ideological evolution, and social and economic development.

Heritage buildings are significant humanistic tourism resources for a city. Yangzhou’s heritage buildings have conservation and utilization value and are a key vehicle for promoting urban tourism development. However, there is a lack of research on their spatiotemporal distribution characteristics and subdivision types. This study aims to explore the spatial and temporal clustering and distribution characteristics of Yangzhou’s heritage buildings, as well as the factors contributing to the formation of these distribution patterns, as a means of promoting the tourism development of Yangzhou. Using mathematical statistics and GIS spatial analysis methods, this study analyzes the geographical distribution patterns of 528 heritage buildings and their influencing factors by using average nearest neighbor analysis, an imbalance index, and density mapping. This study reveals the following findings: (1) The temporal distribution shows an “Λ” shape, in which ancient buildings, modern historical sites, and important modern historical sites and representative buildings account for a significant proportion. (2) The temporal center shows a trend of shifting over time, moving from the southwest to the northwest and then to the northeast. (3) The spatial distribution is uneven; most of these are clustered in Hanjiang District, Gaoyou District, and Baoying County, while few are distributed in other regions. (4) The distribution is influenced by both natural and human factors, including topography, water resources, salt merchant culture, revolutionary culture, war culture, and canal transportation culture, with humans and human factors having a more profound impact than natural factors. Based on these findings, strategies such as regional integration and route planning, the prioritization of sustainable tourism development and preservation, and culture fusion and innovative promotion are proposed in this study as references for the all-for-one tourism development and cultural dissemination of Yangzhou.

In Tianjin, there are many heavy pollution events with PM2.5 as the primary pollutant. It is clear that the spatial and temporal distribution of PM2.5 concentration and the source of heavy pollution process have far-reaching significance for the comprehensive management of PM2.5. Using Tianjin's environmental data for 2014-2017 and in 2016, meteorological data, combined with WRF-Chem model, studied the spatial and temporal distribution characteristics of PM2.5 concentration in Tianjin and the source of heavy pollution process. The results show that since 2014, the concentration of PM2.5 in Tianjin has been decreasing year by year. The monthly variation curve of PM2.5 concentration showed a “U”-shaped distribution, which was seasonal in winter and spring, and low in autumn and summer. The daily variation of PM2.5 concentration is bimodal, with the main peak appearing at 08:00-09:00 and the second peak occurring at 21:00-00:00. The spatial distribution of PM2.5 concentration in Tianjin is different in each season. The spring, summer, autumn and winter highvalue centers are located in Jinghai District in the southwest of Tianjin, Beichen District in the north of the central city, Wuqing District in the west and Yinzhou District in the north. The source of pollutants in the autumn and winter seasons of Tianjin simulated by WRF-Chem model showed that the local source contribution rate was 56%, and the external source transportation contribution rate was 44%, including transportation in Hebei Province and Shandong Province.

The spatial and temporal distribution of agricultural water requirement can provide a scientific basis for regional drought and disaster mitigation management and optimal allocation of irrigation water resources. The irrigation water requirement and irrigation water requirement index of the Hebei Plain during 57 years were calculated by a long series of data of 22 weather stations from 1961 to 2017, and the spatial and temporal distribution characteristics were also analysed. The results show that (a) in this long‐term series, the irrigation water requirement was between 164 and 759 mm, and the irrigation water requirement index was between 0.33 and 0.78, which fluctuated between 1961 and 2017, and in 1977 began to show a downward trend; (b) irrigation water requirement and irrigation water requirement index in the Hebei Plain area had obvious seasonal changes during the year. Irrigation water requirement and irrigation water requirement index were the largest in April, the reasons for this phenomenon being high evapotranspiration and low effective precipitation; (c) the spatial distribution of irrigation water requirement and irrigation water requirement index in the Hebei Plain area are significantly different, both of which are larger in the central region and smaller in the Northeast and Southwest regions.

Due to its rapidly economic development, China is currently facing severe air pollution in a large scale, resulting in increasingly serious influence. It has the characteristics of regional scale and complex components with high concentration level, especially in the eastern China. For the discussion of such environmental strategies and regional efforts, it is necessary to investigate temporal and spatial distribution of pollutants, emissions and pollution transport for better understanding of the impact of various sources on air quality. Differential Optical Absorption Spectroscopy (DOAS), as a spectroscopic remote sensing technique, is of great advantage for the measurement of atmospheric pollutants, such as in real-time, automatization, reliable running. Recently, DOAS techniques have been developed to map the distribution of regional pollutants (gases and aerosols) with various platforms (e.g. network, mobile and airborne DOAS).An overview of MAX-DOAS (Multi-Axes DOAS), mobile DOAS and airborne DOAS is presented. MAX-DOAS can derive information on the vertical profile of the observed trace gases, as well as aerosols, by performing measurements at several elevation angles (from the horizon to the zenith). We established a MAX-DOAS network in the eastern China. Mobile DOAS can rapidly detect spatial and temporal distributions and emissions of air pollutants via mounting the Zenith or MAX- DOAS systems on mobile platform. Airborne imaging DOAS can provide pollutant mapping in a large scale. The principle, instrumentation and inversion algorithm are given. As typical applications of these techniques, measurements of investigating regional pollution in Guangzhou, Nanjing and North China Plain are discussed in the aspects of characteristics of temporal and spatial distribution, pollution transport pathway, emission sources and amounts. The prospect of DOAS in regional air pollution monitoring is further discussed for estimation of total emission and comparison with emission inventory.

A statistical analysis of the distribution of convective windstorms and their radar characteristics in Hubei Province, China. Part 2

The increasing proportion of night consumption in the total daily consumption means the night economy has become an indispensable part of national economic development. However, early social science research on alcohol in the night economy and social science research on the night leisure industry dominated our understanding of the night city. Few researchers have built effective mathematical statistical models to explore the spatio-temporal distribution and regional interactions of the night economy. This paper presents a method to analyze the spatial and temporal distribution pattern of the night economy based on multi-source data. Firstly, K-Means++ and DBSCAN were used to cluster OD points to identify the gathering areas of night activities. Then, the local L-function in “flow space” was used to extract the aggregated flow of each aggregation area and analyze the regional interactions. Finally, the correlation between night activity and night service facilities was calculated by using geographic detector, and night activity and lighting were coupled by the profit and loss value. The research shows that this method can identify the main areas of night activity, dig out the interrelationships at the community level, and find the new night activity gathering points and night economic growth areas in the future. This study extends the current situation that the night economy is limited to theoretical research and research in central urban areas, provides the temporal and spatial distribution of night activities and night lighting supplies from the perspective of big data, and provides a basis for future night economy research, urban planning, and relevant policy issuance.

Towards a new urban geography of expenditure: Using bank card transactions data to analyze multi-sector spatiotemporal distributions

Atmospheric ducting is a highly refractive propagation condition that frequently occurs at sea and significantly impacts radar and communication equipment. This paper analyzes the spatiotemporal distribution of lower atmospheric ducts (LAD) in the South China Sea (SCS) and the variation of their occurrence rate with the monsoon by using reanalysis data from the ECMWF from 1980 to 2022. Additionally, the study discusses the relationship between ducting occurrences and atmospheric and oceanic conditions. The results indicate that wind dynamics in the SCS significantly impact ducting incidents. During the high-incidence period of LAD, humidity-gradient-constructed ducts are the primary mechanism. Before the onset of the monsoon, the mountains in the western part of Luzon Island obstruct the easterly wind, resulting in high temperatures and strong evaporation along the western coast of the mountains. Meanwhile, low temperatures and humidity prevail in the eastern part of the mountains, and they lead to a stratified atmosphere characterized by dry and cold upper layers and warm and humid lower layers in the western part of Luzon Island, which causes a distinct decrease in humidity with height. After the onset of the monsoon, the air from the Indochina Peninsula to the ocean is dry and cold, but the high-altitude area blocks it. This weakens the horizontal mobility of the low-level humid atmosphere over the sea, resulting in atmospheric stratification in the eastern coastal area of the Indochina Peninsula. This stratification leads to dry and cold upper layers and warm and humid lower layers. Significance Statement Atmospheric ducting is a superrefractive propagation condition that frequently occurs at sea and has a significant impact on radar and communication equipment and is related to large-scale or medium- and small-scale atmospheric stratification. The distribution of land and sea around the South China Sea (SCS) and the monsoon are important factors affecting the existence of atmospheric ducts in this region. Many scholars have studied the mechanism of atmospheric ducts in local areas based on observation data (or reanalysis data). The literature on the atmospheric ducts in the SCS mainly focuses on the spatial and temporal statistical distribution of seasons, months, and days, and gives the spatial and temporal distribution characteristics of the region within the statistical time, emphasizing the important influence of the monsoon on the duct, but there is no relevant research on the reasons for the existence of the specific relationship and its temporal and spatial distribution characteristics. The manuscript analyzes the temporal and spatial distribution of lower atmospheric ducts in the SCS and the variation of their occurrence rate with the monsoon, quantifies the contributions of temperature, humidity, and air pressure to the ducting occurrence, meanwhile discussing the ducting occurrence relation with atmospheric and oceanic conditions. In the end, we demonstrate that the development of high-incidence areas for SCS ducts prior to and following the onset of monsoon season is connected to factors such as wind patterns, seawater evaporation, and topography. Furthermore, unstable vertical transport of water vapor in both the atmosphere and oceanic conditions plays a crucial role in facilitating the creation of humidity-type ducts.