Kernel Density Method Research Articles

Analysis on the Evolution Characteristics of Rural Tourism Public Service System from the Perspective of Digitalization—Empirical Evidence from the Silk Road Economic Belt

The integration of digitalization with public tourism services has emerged as a new model for the development of the rural tourism public services. The Silk Road Economic Belt is a crucial area for the future development of the tourism industry. Exploring the coupling of the digitalization and the development trends of the rural tourism public services is significant for advancing rural tourism in this region. This study applies Complex Adaptive Systems theory and Synergy theory to the development of the digitization of rural tourism public services, clarifying the structure of the digitization of the rural tourism public service system. Based on this, a collaborative development evaluation system for the digitization of rural tourism public services is constructed, focusing on the Silk Road Economic Belt. By using the SMI-P evaluation model, ArcGIS spatial visualization, Gini coefficient, and kernel density methods, the collaborative development of the digitization of the rural tourism public service system was measured and analyzed in this paper. The findings reveal the following: (1) The collaborative development of the digitization of the rural tourism public service system in the Silk Road Economic Belt shows a gradual upward trend, yet the overall level of the collaboration is transitioning from a state of imbalance. (2) Compared to the Southwest, the Northwest exhibits a lower overall level of collaboration, with growing disparities in collaborative development indices among provinces, although there is a trend toward higher levels of aggregation. (3) The development of the rural tourism public services is trending toward a favorable state of multi-dimensional collaboration, characterized by significant regional features, including multi-polarization and unbalanced development. Finally, optimization paths for the digital development of the rural tourism public services were proposed in this study, which can provide guidance for improving the construction of the digitization of the rural tourism public service system and exploring clear development pathways.

A novel framework for evidence-based assessment of flood resilience integrating multi-source evidence: A case study of the Yangtze River Economic Belt, China

Floods are extremely destructive to the society, economy and nature, and severely restrict sustainable urban development. There is an urgent need to assess the level of flood resilience, analyze its evolutionary characteristics and improve the flood resilience of the region. However, few previous studies have integrated multi-source evidence into a framework for assessing flood resilience over a longer time span. This study integrated multi-source evidence to analyze the Yangtze River Economic Belt, including literature-based evidence, policy texts and social media data. Subsequently, the Kruskal algorithm and Jaccard coefficient were used to construct collinear networks and identify the clustering dimensions of flood resilience. After evidence judgment, a flood resilience indicator system was constructed. The flood resilience index was calculated using the improved Critic method. The dynamic evolution characteristics and key influencing factors were illustrated by the Kernel density and Grey correlation methods, respectively. The principal contribution is to integrate multi-source evidence to assess flood resilience, with a newly constructed indicator system that systematically considers local public demand, policy priorities and common indicators from previous literature. The results show that: the flood resilience index of the Yangtze River Economic Belt is in the range of [0.16, 0.75] from 2000 to 2022, with higher values in the downstream compared to those in the midstream and upstream. The social dimension dominating the overall flood resilience. The kernel density curve of the YREB is characterized by a right trailing. The inter-regional differences tend to widen and have a polarization effect. The special funds for water conservancy finances and the length of flood prevention levees are key factors influencing the level of flood resilience. Finally, strategies for enhancing flood resilience were proposed. This study provides a feasible framework for constructing an indicator system and assessing flood resilience by integrating multi-source data. It is important for flood risk management and helps to the development of urban flood prevention and resilience strategies.

Seismic fragility analysis of long-span rigid-frame bridge on mountainous soft clay site

In order to assess the damage condition of bridge components for a large-span rigid bridge in a soft clay site in a mountainous area in China southwest, a finite element model of a large-span rigid bridge is established based on the OpenSees software, and the joint probability density distribution function of the ground motion strength and seismic demand and the marginal distribution function of the ground motion are introduced into the kernel density function. As a basis to get the method of calculating the fragility of the bridge members, and the method is verified for its feasibility, on this basis, the damage condition of the bridge components are analyzed, and finally the damage condition of the bridge system are analyzed by the first-order bounds method and the improved PCM method (IPCM). The results showed that: (1) Kernel density method (KDE) can effectively calculate the damage probability of each component, for example, under ground motions with PGA equal to 0.2 g, the probability of slight damage of the 1# pier is 29%, that of the intermediate consolidation pier (2# pier ~ 4# pier) is about 90%; the probability of slight damage of the 1# bearing is 48%, and that of the 2# bearing is 87%. (2) Reasonable value of the expansion joints can effectively reduce the probability of main beam collision. In this investigation, the value is taken as 0.18 m ~ 0.24 m. (3) The bridge system is more likely to be damaged than a single component in the system, and the damage probability of a single component cannot be used as a criterion for the bridge system in the actual working condition. Comparing the first-order boundary law with the IPCM method, the IPCM method has higher accuracy.

Zonasi Kawasan Wisata Pantai di Kota Padang Sumatera Barat Menggunakan Pemodelan Viewshed

Padang City is one of the cities in West Sumatra which has a coastline with a coastline of 68 km. The coast of Padang City is a special interest tourist area in West Sumatra Province. This research aims to determine the approximate zoning of coastal tourist areas using geotagging photo data and determine the range of visibility using viewshed modeling. Zoning is carried out using the Kernel Density method. Kernel Density divides zones through the density of geotagging photo coordinate point data. In this research, the geotagging photo data used is photos that capture coastal views in the city of Padang. The viewshed is carried out towards the mainland because it has topographic diversity. This type of research is qualitative research. The data used is secondary data obtained through the Ina-Geoportal agency. The results of the research showed that there are 6 core zones of coastal tourist areas that are usually visited by tourists in Padang City, West Sumatra Province. The tourist beach area has a viewshed area ranging from 0.174 km2 to 4,569 km2.

Exploring the spatiotemporal impacts of urban green space patterns on the core area of urban heat island

The key to managing urban heat island (UHI) is identifying and cooling the core areas of UHI. Studies have shown that spatial differences in urban green space (UGS) indicators have a significant impact on spatial differences in land surface temperature (LST). However, previous studies have mainly explored UGS and LST in the entire region, with few focusing on the urban core area. In this study, we extracted the urban core area based on the Point of Interest (POI) and kernel density methods. Correlation and regression analyses were then used to investigate the correlation between UGS indicators and seasonal LST in the urban core area. Our results confirm the significant cooling effect of UGS at the urban core scale. The effects of UGS landscape composition and configuration on LST varied across seasons and across urban green space ratio (UGSR) gradients. In the warm season, increasing the UGSR proved to be the most effective way to mitigate the urban thermal environment. In urban core areas where expanding UGS is not possible or in cores with high UGSR, designing UGS with complex shapes and clusters can better achieve the cooling effect. These results suggest that the influence of UGS landscape features on the urban surface thermal environment at the urban core area scale is very complex. Therefore, implementing urban greening to mitigate the UHI problem requires considering the premise of multifactorial analysis.

Ecological risk assessment and spatial–temporal differentiation of soil and water resources in the Hefei metropolitan area

There are important ways to solve the ecological risk problems of regional water resources and soil resources, and to promote the benign development of soil and water resources, involving scientific evaluation of the ecological risk of soil and water resources in Hefei metropolitan area, clarifying the intrinsic evolution law of ecological risk and identifying the characteristics of spatial and temporal variations. Based on the conceptual model of “ST-QS-RR”, the evaluation indicator system is constructed, the CRITIC method is used to assign weights, and the TOPSIS method, kernel density method, markov chain and resistance model are used to measure and analyse the spatial and temporal characteristics of ecological risk of soil and water resources, and to explore the main factors that cause ecological risk of soil and water resources. The results of the study show that: (1) Hefei metropolitan area and its cities show a steady decline and the characteristics of “high in the north and low in the south, high in the west and low in the east”. (2) Most of the subsystems in the Hefei metropolitan area and the cities show a decreasing trend, with its resistance factors mainly concentrated in the QS system. (3) There is club convergence in Hefei metropolitan area. When the type of adjacent domain is higher, the change of risk type is more sensitive.

Spatial Distribution Analysis of Urban Retail Industry Using POI Big Data

With the development of social economy, it is very important to identify urban functional areas and understand the spatial distribution characteristics of urban functional areas for urban scientific planning and government decision-making. Reasonable spatial distribution of urban retail industry is of great significance to promote urban economic development, optimize urban structure, and meet the consumption needs of urban residents. Based on the data of retail industry's POI, GDP, population and transportation in Nanning, China, this paper analyzes the spatial distribution characteristics and formation mechanism of different retail industry clusters in the city, and studies the spatial correlation between retail industry and population, economy, transportation, etc., using the methods of kernel density method, spatial correlation analysis, Getis-Ord G * index statistics, and average nearest neighbor distance. The results show that:(1)On the whole, the retail industry is concentrated in the central urban area of Nanning, spreading from the middle to the surrounding areas. (2)The retail hot spots have formed a multi-center development and surrounding spread pattern in spatial distribution. (3) The spatial distribution of the retail industry is highly related to the main traffic lines. At the same time, the concentration and distribution of the retail industry have a strong spatial correlation with the economy and population.

Spatiotemporal Patterns of Reptile and Amphibian Road Fatalities in a Natura 2000 Area: A 12-Year Monitoring of the Lake Karla Mediterranean Wetland.

The pervasive expansion of human-engineered infrastructure, particularly roads, has fundamentally reshaped landscapes, profoundly affecting wildlife interactions. Wildlife-vehicle collisions, a common consequence of this intricate interplay, frequently result in fatalities, extending their detrimental impact within Protected Areas (PAs). Among the faunal groups most susceptible to road mortality, reptiles and amphibians stand at the forefront, highlighting the urgent need for global comprehensive mitigation strategies. In Greece, where road infrastructure expansion has encroached upon a significant portion of the nation's PAs, the plight of these road-vulnerable species demands immediate attention. To address this critical issue, we present a multifaceted and holistic approach to investigating and assessing the complex phenomenon of herpetofauna road mortality within the unique ecological context of the Lake Karla plain, a rehabilitated wetland complex within a PA. To unravel the intricacies of herpetofauna road mortality in the Lake Karla plain, we conducted a comprehensive 12-year investigation from 2008 to 2019. Employing a combination of statistical modeling and spatial analysis techniques, we aimed to identify the species most susceptible to these encounters, their temporal and seasonal variations, and the ecological determinants of their roadkill patterns. We documented a total of 340 roadkill incidents involving 14 herpetofauna species in the Lake Karla's plain, with reptiles, particularly snakes, being more susceptible, accounting for over 60% of roadkill occurrences. Moreover, we found that environmental and road-related factors play a crucial role in influencing roadkill incidents, while spatial analysis techniques, including Kernel Density Estimation, the Getis-Ord Gi*, and the Kernel Density Estimation plus methods revealed critical areas, particularly in the south-eastern region of Lake Karla's plain, offering guidance for targeted interventions to address both individual and collective risks associated with roadkill incidents.

Spatiotemporal Characteristics of Land Cover Change in the Yellow River Basin over the Past Millennium

Investigating the ecological and environmental impacts stemming from historical land use and land cover change (LUCC) holds paramount importance in systematically comprehending the fundamental human-land relationship, a pivotal focus within geographical research. The Yellow River Basin (YRB), often referred to as the cradle of Chinese civilization, ranks as the fifth-largest river basin globally. Early inhabitants made significant alterations to the landscape, resulting in substantial damage to natural vegetation, giving rise to prominent regional ecological challenges. By now, the examination of historical LUCC in the YRB over the past millennium remains in the qualitative research stage, primarily due to the limited availability of high-confidence gridded historical LUCC data. This study aims to advance the current historical LUCC research in the YRB from primarily qualitative analysis to an exploration incorporating timing, positioning, and quantification. Based on reconstructed historical cropland, forest, and grassland grid data of 10 km × 10 km from 1000 AD to 2000 AD, the degree of cropland development and the depletion of forests and grasslands were calculated, respectively. Then, the kernel density method was employed for spatiotemporal analysis and interpretation of dynamic changes in land cover. Subsequently, a cartographic visualization depicting the migration trajectories of the land cover gravity centers was generated, allowing for an assessment of the distance and direction of the centroids’ movement of cropland, forest, and grassland. The results indicate that the cropland coverage in the YRB escalated from the initial 11.65% to 29.97%, while the forest and grassland coverage dropped from 63.36% to 44.49%. The distribution of cultivated land continually expanded outward from the southeast of the Loess Plateau and the southwest of the North China Plain. All three types of land cover experienced a westward shift in their gravity centers between 1000 and 2000 AD. Besides the population growth and technological advancements, the regime shifts induced by wars, along with land use policies in distinct periods, always served as the predominant factors influencing the conversion between different land covers. This research will present a paradigmatic regional case study contributing to the investigation of historical changes in land use and land cover. Additionally, it will offer historical perspectives beneficial for the advancement of China’s objectives in “Ecological Conservation and High-Quality Development of the Yellow River Basin”.

Forecast Zoning of Forest Fire Occurrence: A Case Study in Southern China

Forest fires in the southern region of China pose significant threats to ecological balance, human safety, and socio-economic stability. Forecast zoning the occurrence of these fires is crucial for timely and effective response measures. This study employs the random forest algorithm and geospatial analysis, including kernel density and standard deviation ellipse methods, to predict forest fire occurrences. Historical fire data analysis reveals noteworthy findings: (i) Decreasing Trend in Forest Fires: The annual forest fire count in the southern region exhibits a decreasing trend from 2001 to 2019, indicating a gradual reduction in fire incidence. Spatial autocorrelation in fire point distribution is notably observed. (ii) Excellent Performance of Prediction Model: The constructed forest fire prediction model demonstrates outstanding performance metrics, achieving high accuracy, precision, recall, F1-scores, and AUC on the testing dataset. (iii) Seasonal Variations in High-Risk Areas: The probability of high-risk areas for forest fires in the southern region shows seasonal variations across different months. Notably, March to May sees increased risk in Guangxi, Guangdong, Hunan, and Fujian. June to August concentrates risk in Hunan and Jiangxi. September to November and December to February have distinct risk zones. These findings offer detailed insights into the seasonal variations of fire risk, providing a scientific basis for the prevention and control of forest fires in the southern region of China.

Identifying Accessibility and Equity Defects of Elderly Care Services in Developing Countries: Insights From Xiamen City

Background: The global aging population has raised concerns about the fair distribution of elderly care resources. China, as the largest developing country, has made efforts to address population aging challenges. However, equitable distribution of elderly care resources remains a concern. This study analyzed the spatial layout and accessibility of elderly care service facilities (ECSFs) in Xiamen City to improve resource allocation and enhance the elderly care system in China. The findings provide valuable insights for other developing countries and regions seeking to improve their own elderly care resource allocation.Methods: Xiamen City was chosen as the research area due to its unique geographical location and advanced information technology infrastructure. The study examined the spatial distribution, accessibility, and equity of ECSFs. Using Python, point of interest (POI) data were collected and evaluated using the kernel density method and two‐step floating catchment area method. Spatial autocorrelation analysis identified areas of aggregation and dispersion in ECSF accessibility.Results: Xiamen currently has 660 ECSFs, including nursing homes, adult day care centers, home care agencies, and rural elderly care homes. The analysis revealed spatial disparities, with ECSFs clustering primarily in the central area of Xiamen Island. Significant differences in accessibility were found among the four types of ECSFs. Spatial autocorrelation analysis identified cold and hot spot areas, indicating variations in accessibility across regions.Conclusion: Xiamen City has made progress in allocating elderly care resources and constructing service facilities. However, equity in resource allocation remains a concern. Areas with limited accessibility were identified, leading to unequal access to elderly care resources and timely physical care. To address these challenges, decision‐making departments should consider increasing facilities, improving transportation, enhancing macro planning, and improving facility service quality and accessibility. These measures will optimize ECSF accessibility and promote equitable distribution of elderly care resources.

Performance evaluation of inclusive green growth in China: Dynamic evolution, regional differences, and spatial correlation.

Inclusive green growth is an essential way to achieve sustainable development. We construct an index system for inclusive green growth performance levels (IGGPLs) in Chinese cities and measure the IGGPLs of 271 cities in the Chinese mainland from 2006 to 2020 based on the vertical and horizontal scatter degree method. We employ the Kernel density method, Dagum Gini coefficient method, Moran index method, and Markov chain method to investigate distribution evolution, regional disparities, spatial correlations, and state transition of IGGPLs at the city level, respectively. The research results reveal that: (1) China's IGGPL has improved rapidly, but regions with lower IGGPLs still predominate. The eastern region is far ahead, followed by the northeastern region, with the western and center regions trailing; (2) The development trends of IGGPLs in the eastern and central regions are positive, with no signs of polarization. Although polarizations are obvious in the western and northeastern but have been improved significantly; (3) Regional differences exist, but are gradually narrowing over time. By decomposing regional differences, we find that regional differences are the main cause of total differences; (4) The IGGPLs of cities have significant spatial correlations, presenting the spatial agglomeration characteristics of "high-high" and "low-low".

Forest Structure of Pinus ayacahuite in Southern Mexico

Spatial structure refers to the horizontal and vertical arrangement of individual trees, and the most accurate way to describe it within a community is to characterize tree strata in terms of their dimensions. The aim of this study was to determine the horizontal and vertical structure of pure stands of Pinus ayacahuite Ehrenb. ex Schltdl., in forests of southern Mexico. Forest measurement data from 24 sample plots were used. For analysis of the horizontal structure, diameters within a range of 0.20 cm to 77 cm were used, while for the vertical structure, heights were from 0.09 m to 40.9 m. Non-parametric histograms and Kernel density methods were used in the analysis, and Fisher and Marron multimodality tests were performed. The homogeneity of the forest stands was determined by the coefficient of homogeneity, and the vertical and horizontal structures were described using the stratification proposed by Pretzsch. The results indicate that the horizontal structure corresponds to a diameter distribution with a reversed "J" shape in 79.2% of the sample plots, while 91.8% of the sites were classified as irregular with coefficients of homogeneity of 1.0 to 3.0. In the vertical structure, it was observed that the lower stratum predominated in 75% of the plots, while 25% had a higher concentration of individuals in the middle stratum. The upper stratum had accumulation percentages ranging from 1.3% to 33.3% but did not predominate in any of the plots. According to the multimodality tests, 50% of the plots present multimodality in the horizontal structure, while in the vertical structure this condition is present in 38% of the plots. Knowledge of the spatial structure of Pinus ayacahuite forest stands is essential to define silvicultural strategies that ensure the sustainable functioning of the ecosystem in terms of yield continuity and conservation.

SPATIAL ANALYSIS OF COVID-19 SPREAD PATTERN USING KERNEL DENSITY METHOD IN SURAKARTA

The COVID-19 pandemic caused by the SARS-CoV-2 virus, which spreads through the respiratory system and can cause respiratory problems, began in Wuhan, China, in December 2019 and quickly spread worldwide, including Indonesia. Surakarta experienced a significant increase in cases from April to June due to factors such as the celebration of Eid al-Fitr. The author used the Kernel Density method to map the spatial distribution of COVID-19 cases in Surakarta and to investigate the relationship between vaccination rates and positive patients. The methodology involved a quantitative descriptive study using secondary data from the Surakarta Health Agency in May 2021. Based on the research, it was found that there was no relationship between the achievement of the first dose of vaccination and the number of confirmed COVID-19 cases in the city of Surakarta. The spread of COVID-19 was more influenced by activities carried out by the community in public facilities or outdoor spaces, as well as compliance with the health protocols provided by the government.

Research and Application of Early Identification of Geological Hazards Technology in Railway Disaster Prevention and Control: A Case Study of Southeastern Gansu, China

Geological hazards significantly threaten the safety of China’s railway network. As the railway system continues to expand, particularly with the effects of accelerated climate change, approximately 70% of the newly encountered geohazards occur outside of known areas. This study proposes a novel approach that can be applied to railway systems to identify potential geohazards, analyze risk areas, and assess section vulnerability. The methodology uses integrated remote sensing technology to effectively enhance potential railway hazard identification timeliness. It combines kernel density, hotspot, and inverse distance-weighted analysis methods to enhance applicability and accuracy in the risk assessment of railway networks. Using a case study in southeastern Gansu as an example, we identified 3976 potential hazards in the study area, analyzed five areas with high concentrations of hazards, and 11 districts and counties prone to disasters that could threaten the railway network. We accurately located 16 sections and 20 significant landslide hazards on eight railway lines that pose operational risks. The effectiveness of the methodology proposed in this paper has been confirmed through field investigations of significant landslide hazards. This study can provide a scientific basis for the sustainability of the railway network and disaster risk management.

Examining Changes in Consumer Spatial Structure and Sustainable Development Issues in Beijing before and after the Outbreak of COVID-19

Urban consumption spatial structure has a direct impact on the sustainable development and quality of life of urban residents. This study investigates the impact of COVID-19 on Beijing’s urban consumption spatial structure within the Sixth Ring Road. Utilizing POI (Point of Interest) data and the Kernel Density method, the spatial distribution of commercial centers is analyzed. Consumption data from China UnionPay for 2019 and 2020, along with the Weighted Voronoi diagram method, are employed to assess changes in the radiation range of commercial centers. The findings indicate that: (1) owing to the pandemic’s repercussions, commercial centers at different levels and locations have different changes. (2) There is an overarching decline in UnionPay consumer spending across diverse streets in Beijing. (3) Following the epidemic, large-scale consumption hubs have maintained their dominance, ensuring the overall stability of the city’s consumption spatial pattern. In conclusion, the changes in commercial centers and the significant decrease in consumer spending underscore the dynamic interplay between urban consumption and external shocks like the pandemic. These insights are crucial for urban planning strategies aiming to enhance both resilience and sustainability in the face of unforeseen challenges. The spatial restructuring of traditional commercial centers requires nuanced urban planning. Recognizing the resilience and expansion of smaller centers suggests the importance of fostering localized economic activities. Policymakers could incentivize their development to promote community engagement and economic sustainability.

DAILY FLOWS, URBAN POLYCENTRICITY, AND TRANSIT COMMUTING PATTERNS: A STUDY OF SHANGHAI, CHINA

ABSTRACT Employment center locations, the jobs-housing relationship, and commuting patterns are inextricably connected in a megacity that heavily relies on the urban transit system to shuttle commuters. Using a transit smartcard dataset, a machine learning method is employed as a preliminary filter to sift through commuter flows and isolate key data, then kernel density and topological analysis methods are implemented to delve into the primary research questions, providing a detailed look at how these patterns unfold. The results show that transit commuting behavior in Shanghai is a dispersal activity based on multi-level employment centers characterized as hierarchical, boundary-clear, and functionally oriented. Further analysis illustrates that the intensity of commuting linkages correlates with the employment center level, shaping a hybrid pattern that couples a core-periphery pattern with a spoke-hub pattern. The commuting network connections present corridor, neighborhood, capture, and replacement features, highlighting the importance of employment centers in shaping commuting patterns. From a daily flow perspective, these findings echo the central place theory and verify that the employment center distribution in Shanghai is also multi-layered and well-nested, forming the basis for commuting links. Policy implications are provided for polycentric megacities with progressively sophisticated urban transit systems.

Cooling capacity assessment in Karet Tengsin Platinum Integrated Area

The increasing trend of urbanisation has resulted in land use changes and increased urban activities, which led to the emergence of the Urban Heat Island (UHI) phenomenon. The readiness of urban design and planning in mitigating UHI becomes crucial, to reduce the demand for cooling energy and enhance productivity. This study aimed to calculate the cooling capacity index of the Karet Tengsin Platinum Area design, using InVEST 3.12.1, based on shading, evapotranspiration, albedo, and distance from cooling islands, and it has a range of 0-1. The index was further analysed, using the kernel density method, to examine the spatial density patterns to identify the priority features that need to be intervened to mitigate UHI in the Area. The research findings show that, the Karet Tengsin Platinum Area design has a cooling capacity index ranging from 0.22 to 0.83, dominated with a low index value, below 0.3, indicating that, this area has poor cooling capacity. Low index values are distributed in built-up areas, which show that, the materials used in built-up areas need to be prioritised as features that need to be intervened to enhance the cooling capacity. Additionally, this study also discusses urban cooling strategies, through other features that are less explored in the modelling. This study method can be used as a reference for urban designers in integrating urban cooling approaches, as UHI mitigation strategies, in urban area planning and design.

A statistical study of wind speed and its connectivity with relative humidity and temperature in Ughelli, Delta State, Nigeria

One of the vital climatic parameters with significant roles in many natural phenomena is wind. The importance of wind cannot be overemphasized due to its role as a source of renewable energy. The understanding of wind is of great importance particularly for the purpose of prediction and management of severe weather events. However, wind as a climatic parameter depends on relative humidity and temperature as well as other weather parameters and several statistical approaches such as time series analysis, extreme value analysis and spatial analysis have been used to analyze wind speed data. This study uses the kernel density method in analyzing wind speed in Ughelli, Delta State and its connection with relative humidity and temperature using the Gaussian kernel function for a period of five consecutive years from 2018 to 2022. The performance measure employ is the asymptotic mean integrated squared error (AMISE) with the Pearson R test that measures the strength of the relationship that exists between parameters. The results of the investigation with regards to the AMISE shows that 2018 recorded best performance with wind speed and relative humidity while 2021 recorded best performance for wind speed and temperature but 2019 recorded unsatisfactory outcomes for wind speed and the two parameters. This implies that human activities that depend on these parameters for their performance did best in 2018 and 2021 respectively. Furthermore, in terms of connectivity, wind speed and relative humidity are negatively correlated in 2018 and 2022 but positively correlated in 2019, 2020 and 2021 while wind speed and temperature are negatively correlated which implies that as temperature increases, wind speed decreases.

Climate impact on flood changes – an Austrian-Ukrainian comparison

Abstract This study compares the flood regime of rivers in Ukraine and Austria over the last decades. We used data from mountain and lowland watersheds, where floods are caused by different processes. In order to identify possible shifts in the day of occurrence of annual flood maxima, we apply the kernel density method to the time series of two subperiods (1960–1987 and 1988–2015). We use the Mann Kendall test at a 5% significance level to identify significant positive or negative trends in the series of annual maximum discharges. In Austria, we observe an increasing trend in summer floods associated with increasing precipitation. In the lowland areas of Ukraine, a clear reduction in spring floods is observed, linked to shallower snow packs in a warming climate. In the Ukrainian Carpathians, on the other hand, where floods occur throughout the year, an increase in the portion of liquid precipitation during the cold period of the year leads to earlier floods and an increase in the probability of flooding in winter.