Spatiotemporal Analysis Research Articles

Molecular and functional characterization of a β-tubulin gene in Plutella xylostella.

The β-tubulin gene is essential for reproductive development, especially for male fertility, in different insects including Bombyx mori and Drosophila melanogaster. Targeting reproductive genes such as β-tubulin offers a promising approach to pest control that is more sustainable than chemical pesticides. However, there is limited research on the functional role of β-tubulin in Plutella xylostella, a highly damaging pest of vegetable crops. In the present study, we first identified and cloned the β-tubulin gene in P. xylostella (Pxβtubulin-1). Pxβtubulin-1 protein contains two conserved domains of Tubulin and Tubulin-C, and β-tubulin were conserved in the Lepidoptera. Spatiotemporal expression analysis revealed that Pxβtubulin-1 was highly expressed in male pupae, adult males, and testes, suggesting its testis-specific function. Using CRISPR/Cas9 technology, we generated two homozygous Pxβtubulin-1 mutant strains of P. xylostella. Mutant strains exhibited significantly lower egg production and hatching rates compared with the wild type. Dissection and measurement of reproductive organs revealed that the testes and bursa copulatrix in mutant strains were significantly reduced in size compared with the wild type. In conclusion, Pxβtubulin-1 is vital for male fertility as it influences the development of reproductive organs and can be a potential target for the control of P. xylostella.

Spatiotemporal comparative analysis of three carbon emission inventories in mainland China

Spatiotemporal comparative analysis of three carbon emission inventories in mainland China

Spatio-temporal Variation and Trend Analysis of Ground-Level Ozone in Major Indian Metropolitan Cities: A Geospatial Approach

Air pollution refers to any chemical, physical, or biological contamination that contaminates an interior or outdoor environment and modifies the intrinsic qualities of the atmosphere. It can be produced by natural or anthropogenic activities. Among those pollutants mentioned by the World Health Organisation (WHO), ground-level ozone, also known as tropospheric ozone, possesses a significant impact on human life. The current study was developed in response to the need to study ground-level ozone concentrations around India and metropolitan cities. Using geospatial methods, the spatiotemporal variation of India was discovered. Using trend tests, trend analysis of the main metropolises in Bangalore, Chennai, Delhi, Hyderabad, Kolkata, and Mumbai was presented. 18 years of data (2005–2022) from the Ozone Monitoring Instrument (OMI) were used to conduct the test. According to geospatial research results, the northern region of India has a higher concentration of ozone than other locations. Delhi has a higher ozone rate than other metropolitan cities, ranging from 0.1219 to 0.1567 mol/m2, followed by Kolkata (0.1085 to 0.1418 mol/m2). In these cities, summertime is often the time of year when the ground-level ozone concentration is at its maximum. Trend analysis using the Mann-Kendall and modified Mann-Kendall tests from 2005 to 2022 shows that the concentration increases with each year that goes by, even though there isn't a significant trend (p <0.05) across all of the monthly, seasonal, or annual periods. The research identifies high ozone areas and seasons, guiding policies, health advisories, urban planning, and accurate pollution forecasts.

Spatiotemporal variation analysis of Tigris River water quality in Mosul, Iraq during 2020–2023 based on environmetric techniques

Spatiotemporal variation analysis of Tigris River water quality in Mosul, Iraq during 2020–2023 based on environmetric techniques

Digital Information System for the Polish Marine Areas - Modelling of Structures and Dynamics of Physical Processes in the Southern Baltic

Researching the dynamic environment of the Baltic Sea requires an interdisciplinary approach, with numerical models and computer simulations becoming essential tools. The 3D CEMBS-PolSEA ecosystem model, developed at the Institute of Oceanology of the Polish Academy of Sciences, aims to determine the basic hydrodynamic parameters of the southern Baltic Sea. The CSI-POM service (Digital Information System on the Environment of Polish Marine Areas) consists of new tools for studying the structures, dynamics, and variability of physical processes in the southern Baltic. The service includes tools for determining the thermocline, halocline, and pycnocline, conducting spatio-temporal analysis of water column structure, automatic detection of vortices, testing water mass inertia under forecasted wind forces, and automatic detection of upwelling currents. The novelty of this work lies in the development of tools for studying the dynamics of the structure and variability of physical processes in the southern Baltic Sea. These innovative techniques support scientists, the maritime community, and regulatory bodies by providing detailed insights into local phenomena such as vortex formation, water mixing. The tools are implemented on the project server and the Tryton+ supercomputer, enabling high temporal and spatial resolution results. The CSI-POM system's operational mode ensures access to the latest model results, with real-time and forecasted data. This enhances understanding and forecasting capabilities, informing about the current state of the environment and potential threats in the open sea.

Spatiotemporal analysis of vegetation fires and hot spots in watersheds in southeastern Amazonia

O trabalho teve como objetivo mapear os riscos de ocorrência de incêndios vegetacionais em três sub-bacias hidrográficas do rio Xingu, no sudeste da Amazônia brasileira, para o ano de 2021. Com o auxílio de técnicas de geoprocessamento realizou-se o cruzamento de nove variáveis ambientais afim de construir um mapa de risco de ocorrência de incêndios vegetacionais. As variáveis ambientais foram classificadas e reclassificadas conforme sua relevância para o risco de ocorrência de incêndios vegetacionais e as análises e ponderações seguiram o método Analise Hierárquica de Processos – AHP. A metodologia AHP foi eficiente e os riscos alcançados nas três sub-bacias formam divididos em cinco classes: baixo, moderado, alto, muito alto e extremo. Conforme o mapeamento de risco de ocorrência de incêndios vegetacionais, na sub-bacia hidrográfica do rio Culuene os focos de calor tiveram ocorrência concentrada nos meses de julho e agosto e 99,72% ocorreram em áreas pertencentes as classes de risco muito alto e extremo. Para a sub-bacia hidrográfica do rio Comandante Fontoura os focos de calor ocorreram em volume maior entre junho e outubro e 98,14% destes, acontecem em áreas das classes de risco alto e muito alto. Já na sub-bacia hidrográfica do rio Fresco o maior número de focos de calor foi registrado em agosto e setembro, quando 96,32% dos focos foram registrados em áreas das classes de risco alto e muito alto.

Spatio-temporal analysis of extreme air pollution and risk assessment.

Extreme air pollution poses global health and environmental threats, necessitating robust policy interventions. This study first analyses the surface mass concentration of major aerosols (such as black carbon, organic carbon, dust, sea salts, and sulphates) to estimate global PM2.5 concentrations from 1980 to 2023. The developed model-estimated PM2.5 database was validated against data from 526 cities worldwide, showing strong accuracy, with RMSE, r, and R2 values of 7.47μg/m³, 0.87, and 0.75, respectively. The motivation arises from the need to understand whether recent pollution increases are driven by rising emissions or natural variability, given the significant impacts on life and property. To assess both short-and long-term pollution trends, magnitudes, and risks, we proposed twelve novel extreme pollution indices, which comprehensively characterize the spatial and temporal variations in pollution. The highest PM2.5 concentrations were observed in regions near the Saharan Desert, reaching up to 90,000μg/m³. However, significant PM2.5TOT (total pollution) concentrations were also found in the Indo-Gangetic Plain (IGP) and eastern China, ranging from 20,000 to 40,000μg/m³. Persistent pollution burdens North Africa for approximately 350 days annually, while the IGP and eastern China experience extreme pollution for over 200 days yearly. Other pollution indices highlight the intensity and frequency of pollution in regions such as North Africa, IGP, Eastern Russia, Western USA, and Eastern China, revealing critical regional air quality challenges. Our analysis identifies cities in low-income and middle-income countries, such as New Delhi, Lahore, Dhaka, and Dammam, as being at extreme risk scores above 90 out of 100. Meanwhile, cities like Ghaziabad, Chongqing, Kolkata, Mumbai, and East London fall into the high-risk category, scoring between 60 and 80. Conversely, most cities in the EU, USA, and Canada are at very low risk, a result of the effective implementation of strategic air pollution norms and policies. The study promotes a phased approach for low- and middle-income regions, emphasizing achievable air quality standards, low-cost monitoring, targeted interventions, urban greening, public awareness, and innovative financing for improvements.

Machine learning and spatio-temporal analysis of meteorological factors on waterborne diseases in Bangladesh.

Bangladesh is facing a formidable challenge in mitigating waterborne diseases risk exacerbated by climate change. However, a comprehensive understanding of the spatio-temporal dynamics of these diseases at the district level remains elusive. Therefore, this study aimed to fill this gap by investigating the spatio-temporal pattern and identifying the best tree-based ML models for determining the meteorological factors associated with waterborne diseases in Bangladesh. This study used district-level reported cases of waterborne diseases (cholera, amoebiasis, typhoid and hepatitis A) obtained from the Bangladesh Bureau of Statistics (BBS) and meteorological data (temperature, relative humidity, wind speed, and precipitation) sourced from NASA for the period spanning 2017 to 2020. Exploratory spatial analysis, spatial regression and tree-based machine learning models were utilized to analyze the data. From 2017 and 2020, Bangladesh reported 73, 606 cholera, 38, 472 typhoid, 2, 510 hepatitis A and 1, 643 amoebiasis disease cases. Among the waterborne diseases cholera showed higher incidence rates in Chapai-Nawabganj (456.23), Brahmanbaria (417.44), Faridpur (225.07), Nilphamari (188.62) and Pirojpur (171.62) districts. The spatial regression model identified mean temperature (β = 12.16, s.e: 3.91) as the significant risk factor of waterborne diseases. The optimal XGBoost model highlighted mean and minimum temperature, relative humidity and precipitation as determinants associated with waterborne diseases in Bangladesh from 2017 to 2020. The findings from the study, incorporating the One Health perspective, provide insights for planning early warning, prevention, and control strategies to combat waterborne diseases in Bangladesh and similar endemic countries. Precautionary measures and intensified surveillance need to be implemented in certain high-risk districts for waterborne diseases across the country.

Assessment of watershed health, integrating environmental, social, and climate change criteria into a fuzzy logic framework.

Spatio-temporal analyses of environmental and social criteria in the context of climate change, facilitate understanding of how historical and current conditions have influenced watershed health. Previous studies have analyzed watershed health, but very few have integrated fuzzy logic with the CRITIC method (Criteria Importance Through Intercriteria Correlation), which enables us to explore alternatives to improve watershed performance. The objective of this study was to evaluate changes in watershed health through historical and projected climate change scenario in the tropical Santa Cruz watershed in Aquismón, S.L.P., Mexico (1985-2027) considering environmental criteria (hydrological and sediment connectivity, runoff, flooding, drought, landscape fragmentation) and social criteria (indigenous population density, human impact on biodiversity, health index, income index, education index). The results indicate that spatio-temporal changes can alter the Watershed Health Score (WHS) from a value of 2.69 to 6.90, particularly in areas with precarious social conditions. Moreover, the study reveals how weighting evolves overt time, as seen in the case of landscape fragmentation, whose value increased 0.0113 to 0.254. This study shows how objective methods such as CRITIC can be integrated through fuzzy logic to analyze the spatio-temporal evolution of watershed problems without the need for a large number of experts to weight the variables (subjective methods). This method can subsequently be applied and reproduced in different zones or watersheds where there is no certainty as to which criteria have the greatest influence and thus enable decisions for watershed management or restoration.

Spatio-temporal analysis of trend the hydro-climatic time series and identify factors affecting Flood Hazard

Spatio-temporal analysis of trend the hydro-climatic time series and identify factors affecting Flood Hazard

Identification and spatio-temporal analysis of Ulva prolifera in a typical coastal area using SAR imageries

Identification and spatio-temporal analysis of Ulva prolifera in a typical coastal area using SAR imageries

Spatiotemporal analysis of LST changes in Morocco: Assessing climate change impacts

Spatiotemporal analysis of LST changes in Morocco: Assessing climate change impacts

Analysis of desert locust (Schistocerca gregaria) suitability in Yemen: an integrated evaluation based on MaxEnt and space–time cube approaches

ABSTRACT Desert locust outbreaks pose severe threats to agricultural production and ecological environments. Hence, understanding the distribution of habitat suitability is crucial for establishing effective prevention and control measures. We introduce an innovative method for analyzing the temporal and spatial variations of desert locust habitat suitability in Yemen. This method integrates ecological niche models with space–time cube analysis. First, we gathered key environmental variables that affect desert locust distribution, including vegetation and soil types, precipitation, and temperature. Subsequently, we employed the MaxEnt model to assess habitat suitability for desert locusts in Yemen for 2010 and 2013–2021. Finally, we applied the space–time cube method for spatiotemporal analysis to reveal the spatiotemporal dynamics of habitat suitability distribution. The MaxEnt model results showed that the kappa coefficients exceeded 0.46 and the area under the curve exceeded 0.75. The spatiotemporal analysis results showed that from 2010 to 2021, the Red Sea coastal plains in western Yemen exhibited the highest habitat suitability levels, with significant increases in habitat suitability in the western and central regions. This study offers a new perspective on studying the spatial and temporal characteristics of desert locust habitat suitability distribution and can provides a scientific basis for the management of desert locusts.

SPREAD: Spatiotemporal Pathogen Relationships and Epidemiological Analysis Dashboard.

In the scope of public health, the rapid identification and control of infectious disease outbreaks are a paramount concern. Traditional surveillance methods often face challenges in effectively combining genetic, geographical, and temporal data, which is crucial for a comprehensive understanding of disease transmission dynamics. Addressing this critical need, the Spatiotemporal Phylogenomic Research and Epidemiological Analysis Dashboard (SPREAD) emerges as an innovative standalone web-based application. SPREAD integrates several modules for detailed genomic relationships, pinpointing genetically close pathogens, and spatial mapping, providing in-depth views of how diseases spread across populations and territories, with significant advantage to manage both bacteria and viruses based on allele and variant calling, respectively. Designed for broad accessibility, SPREAD operates seamlessly within web browsers, eliminating the need for sophisticated IT infrastructure and facilitating its use across various public health contexts. Its intuitive interface ensures that users can effortlessly navigate complex datasets, facilitating widespread access to advanced surveillance capabilities. Through its initial deployments, SPREAD has proven instrumental in quickly identifying transmission clusters, significantly aiding in the formulation of prompt and targeted public health responses. Through the integration of state-of-the-art technology with a focus on user-centered design, SPREAD offers a promising solution that highlights the potential of digital health innovations.

Spatio-temporal analysis of PM2.5 and its association with elevation by using remote sensing: the scenario of Quetta, Pakistan

Spatio-temporal analysis of PM2.5 and its association with elevation by using remote sensing: the scenario of Quetta, Pakistan

Spatio-temporal analysis of vegetation dynamics in new protected areas: Exploring the partial nature reserve of Aghien (southern Côte d'Ivoire)

The Aghien Partial Nature Reserve, located in the district of Abidjan, is a new protected area that requires special monitoring because it is subject to strong urbanization pressure. To analyse the spatio-temporal dynamics of land use at this site, field data was first collected, followed by processing of Landsat OLI/TIRS images of the reserve from 2020 and 2024. Parameters such as the average annual rate of spatial expansion (T), the conversion rate (Tc), the transition matrix and the conversion intensity were then calculated. Finally, a forecast was made for land-use dynamics up to 2032. A total of ten land-use units were identified within the administrative boundaries of the reserve. Among these units, old rubber plantations, fallow land and secondary forests are the most represented plant formations. Over the period from 2020 to 2024, vegetation dynamics are marked by the expansion of secondary forests (Tc = 9.48%; T = 2.26%), young palm plantation (Tc = 15.01%; T = 3.50%) and bare soil (Tc = 18.50%; T = 4.24%). However, the forecast to 2032 shows a significant expansion of fallow land (Tc = 11.66%; T = 0.92%) and secondary forest (Tc = 26.46%; T = 1.96%). This reflects the gradual restoration of floristic diversity in the reserve's landscape. However, given the persistence of certain human activities, the site needs to be monitored.

Spatiotemporal analysis of meteorological drivers of major foliar fungal diseases in rubber budwood gardens in Cote D'Ivoire

Latex production in Côte d'Ivoire is significantly influenced by meteorological conditions and various diseases, particularly foliar fungal diseases affecting Hevea brasiliensis, which can cause yield losses of up to 100%. This study aims to identify the climatic factors driving the severity of these diseases across different ecological zones. Surveys were conducted in budwood gardens (JBG) across six agroecological zones, with meteorological data collected on-site. The analysis identified Helminthosporium heveae, Colletotrichum gloeosporioides, and Corynespora cassiicola as the most prevalent fungi, exhibiting high incidence and severity in key production areas such as Tabou and Nouamou. Multiple regression analyses revealed that rainfall and relative humidity (correlation coefficients ranging from 0.4 to 0.55, p 0.0001) and leaf wetness duration (correlation coefficient 0.7, p 0.0001) are critical predictors of disease severity. Specifically, each additional unit of leaf wetness increased infection severity by 0.642 for H. heveae, 0.435 for C. gloeosporioides, and 0.832 for C. cassiicola. These findings underscore the importance of meteorological factors in disease development and could support the establishment of early warning systems to manage foliar fungal diseases of H. brasiliensis in Côte d'Ivoire.

Driving mechanism of urban expansion in the Bohai Rim urban agglomeration from the perspective of spatiotemporal dynamic analysis

The urban agglomeration represents the predominant form of new urbanisation, yet the evolution of its internal spatial structure exhibits pronounced spatial and temporal heterogeneity. This study concentrates on the Bohai Rim urban agglomeration, one of three major urban agglomerations in China, which has received comparatively limited research attention but has also undergone substantial urbanisation. Therefore, we reassessed and explored the spatial-temporal evolution of the spatial structure of urban expansion using Exploratory Spatiotemporal Data Analysis (ESTDA), and summarized the driving mechanisms using Geographically and Temporally Weighted Regression (GTWR). Our study found that the urban land expansion intensity of Bohai Rim urban agglomeration presented the differences between megacities and large cities, coastal and inland cities and the regional disparities exhibited a gradual narrowing and balancing over time and space, with the high-expansion intensity zones undergoing alternation. The dynamics of the local spatial structure performed a clear positive correlation with the development level and a negative correlation with the exploitation time. The urban expansion intensity was influenced by various factors, including population, economic and other variables. Over time, the main drivers shifted from emphasis on economic quantity to quality, and from financial support to government policy. The objective of this study is to substantiate the impact of socio-economic factors on the spatio-temporal heterogeneity of urban expansion and to propose strategies for alleviating urban land pressure in the Bay Area urban agglomerations. This study enriches the research on the urban expansion mechanisms of different types of urban agglomerations and enhances a comprehensive understanding of the spatiotemporal heterogeneity of urban expansion within it. The findings can provide valuable theoretical support for urban planners in future urban development and construction and can also serve as exemplars for urbanisation in other urban agglomerations.

Spatio Temporal Analysis of the Effect of Slope Gradient on the Magnitude of Erosion and Deposition in the Endikat Watershed

Erosion is a natural process caused by rainfall (R), slope gradient (λ), slope length (LS), soil type (K), and changes in land cover. These factors drive the erosion of the surface layer of the soil, intensified by steep slopes and shifts in land use. The extent of this erosion has significant implications as it contributes to a reduction in the distribution of ecosystem services (ES) both spatially and temporally in various sub-watershed areas. To analyze the magnitude of erosion, modern methodologies including the Universal Soil Loss Equation (USLE) and the refinement, the Revised Universal Soil Loss Equation (RUSLE) have been adopted particularly focusing on the slope length (LS) factor for more accurate assessments. From this analysis and the direction of deposition spatially, the results can be used to assess and consider the actual value of ES in watersheds. The results can also be used for policy in decision-making, assessing the quality and quantity of water resources, as well as managing land resources better in an economically, environmentally, and socially beneficial manner. Therefore, this study aimed to analyze the classification of the magnitude of slope in the RLKSi equation to predict the estimated spatial pattern of both erosion and deposition as well as assess the level of vulnerability to soil loss in the Endikat sub-watershed which was upstream of the Lematang watershed. The equation used was SEDRET which included the level of soil resistance to the magnitude of soil loss (RUSLE) minus actual erosion (USLE). The results of the highest erosion value of 2,205.14 tons/Ha/year occurred in an area with slope of &gt; 45% and soil type Association &amp; yellow brown podzolic with shrub land use. Although the highest eroded retention rate of - 6,710.17 tons/Ha/year occurred on slope of 39.09% with yellowish brown podzolic soil type and dry agricultural land use. Additionally, the area experiencing the greatest sedimentation occurred on slope of 5.79% with Andosol Brown &amp; Regosol soil types as well as shrub land use.

Utilizing Rhythmic Haptic Cueing in Arm Swing Training to Improve Gait Speed Among Older Adults.

Current gait rehabilitation protocols for older adults typically attempt to effect changes in leg movements, while the role of arm movements is often ignored despite evidence of the neurological coupling of the upper and lower extremities. In the present work, we examine the effectiveness of a novel wearable haptic cueing system that targets arm swing to improve various gait parameters in older adults. Twenty participants ( years) were recruited to analyze their gait during normal and fast walking without haptic cueing. Vibrotactors attached to the arms were then used to give haptic cues that were designed to either increase or decrease arm swing cycle time. The effects of such cueing on gait symmetry and spatiotemporal parameters were then analyzed. The presentation of the haptic cues significantly altered arm swing cycle time resulting in an increase in gait speed of 18.2% when arm cycle time was decreased and a 12.3% decrease in gait speed when arm cycle time was lengthened. The response to haptic cues was immediate, emphasizing the tight coupling of the arm and legs in the production of gait. Spatiotemporal analysis revealed improvements in gait parameters and symmetry metrics, indicating enhanced coordination between limbs when using tactile cues. Subjective evaluations further supported the system's potential for gait training. The results reveal the significant potential of the haptic cueing system to modulate gait through arm swing manipulation, leveraging interlimb neural coupling. This aligns with the growing need for home-based gait training solutions, particularly for the older population, and presents a novel approach that could be integrated into current gait rehabilitation practices.