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Abstract This study aims to explore the spatial distribution and site selection characteristics of cultural heritage sites, as well as the impact of the natural environment on the site’s location. A total of 448 cultural heritage sites in Jinan City (Shandong province), which have been listed as key cultural relic protection units from before the Qin Dynasty to after the Qing Dynasty (ca. 7500 BCE–present), were analyzed using spatial analysis tools in ArcGIS 10.6 software. The main research findings are as follows: (1) cultural heritage sites have a wide distribution and few cores and are characterized by spatial agglomeration and the formation of a single core area around the Lixia District; (2) in terms of spatiotemporal evolution, cultural heritage sites follow a “diffusion–aggregation–diffusion–aggregation” trend, exhibiting a “southwest–northeast–northwest” trajectory, with characteristics of continuity and a centripetal pattern; and (3) cultural heritage sites are mainly distributed in alluvial plains with heights ranging from 2.6–100 m, slopes ranging from 0–5°, and distances ≤ 1 km from water systems. The more recent the construction year of the cultural heritage site is to modern times, the more closely its type is to production and living, and the more relevant it is to the natural environment.

The impacts on living conditions and natural habitats deriving from planning decisions require complex analysis of cross-acting factors, which in turn require interdisciplinary data. At the municipal level, both data collection and the knowledge needed to interpret it are often lacking. Additionally, climate change and species extinction demand rapid and effective policies in order to preserve soil resources for future generations. Ex-ante evaluation of planning measures is insufficient owing to a lack of data and linear models capable of simulating the impacts of complex systemic relationships. Integrating machine learning (ML) into systemic planning increases awareness of impacts by providing decision-makers with predictive analysis and risk mitigation tools. ML can predict future scenarios beyond rigid linear models, identifying patterns, trends, and correlations within complex systems and depicting hidden relationships. This article focuses on a case study of single-family houses in Upper Austria, chosen for its transferability to other regions. It critically reflects on an ML approach, linking data on past and current planning regulations and decisions to the physical environment. We create an inventory of categories of areas with different features to inform nature-based solutions and backcasting planning decisions and build a training dataset for ML models. Our model predicts the effects of planning decisions on soil sealing. We discuss how ML can support local planning by providing area assessments in soil sealing within the case study. The article presents a working approach to planning and demonstrates that more data is needed to achieve well-founded planning statements.

The rehabilitation of mine waste dumps is a critical environmental challenge, particularly in areas like Uricani, Romania, where such sites are often characterized by hazardous conditions and poor ecological recovery. This study addresses the need for efficient, low-cost solutions for land reclamation by employing UAV photogrammetry and GIS spatial analysis to assess the potential for afforestation with Robinia pseudoacacia L., a species known for its soil stabilization and ecological benefits. Using UAV technology, high-resolution digital terrain models and orthophotos were generated, with an RMSE of 0.086 m, demonstrating the accuracy and efficiency of this method for large-scale landscape initiatives. GIS spatial analysis was performed to create six key terrain maps and four pedoclimatic factor maps, essential for evaluating the site’s suitability for ecological restoration. The pilot afforestation project, which involved planting R. pseudoacacia, achieved a 75% survival rate after four years, suggesting that the species can thrive under the site’s conditions. The landscape design proposal incorporates recreational spaces aimed at benefiting the local community and attracting tourism, thereby contributing to the area’s economic and cultural revitalization. The interdisciplinary integration of UAV surveying, GIS, and landscape design highlights the cost-effectiveness and interdisciplinary nature of this approach, offering a sustainable model for mine waste dump reclamation and future ecological restoration projects.

Abruzzo Periadriatic Area (Central Italy) is sadly acknowledged as highly exposed to geo-hydrological hazards, with small-to-medium size catchments and urban areas strongly affected by natural phenomena. In the present work, the Pescara River basin, hit in the past by several floods and concurrent superficial landslides due to localized and intense rain events, has been studied. A screening of morphometry, land use changes, rainfall datasets, and flooding-related effects on landscape has been carried out, both at the catchment and local scales. A morphometric and geomorphological approach was applied, supported by GIS software and implemented with literature data. It allowed us to derive insights about the interaction between land use changes and geo-hydrological phenomena. Over the past 60 years, the study area underwent increases in built-up areas from ~16 km2 in 1955 to ~67 km2 in 2019 with significant sprawl at low altitude. Rainfall datasets outlined moderate-to-low annual precipitation with occasional heavy rainfall events (>100 mm/d and 30–40 mm/h). Historical and recent events (~35 events over a 100-year period) linked to landscape and geomorphological processes were also counted. Resulting data allowed to implement knowledge about the present-day geomorphological arrangement of the basin, providing information for land management in a changing environment. These findings provide valuable insights for future urban planning, policy formulation, and sustainable development initiatives, readily available to interested stakeholders.

This study combines the traditional method of geological and geomorphological mapping with a quantitative GIS analysis to examine landforms and debris flows channels. Using a high-resolution DEM (5 m) as a base, the geomorphological map highlights the various landforms around the Alpe di Succiso (Northern Apennines, Italy), including glacial and cryoclastic features, slope landforms and deposits due to gravity (particularly debris flow) and deposits due to running waters. The methodology applied to the channels is based on the geomorphometric parameters derived from the DEM, including Topographic Wetness Index (TWI), Terrain Ruggedness Index (TRI), Slope Angle, and Elevation extracted every 10 m along each channel and grouping the channels in four classes based on their lengths. Within each class, multiple ranking criteria were employed for the identification of channels showing anomalous or common patterns. Debris flow channels exhibit anomalous patterns in the geomorphometric parameters, indicating significant variations in their topographical characteristics..

Abstract China’s northern Fujian, as one of the spatial carriers of renowned traditional Chinese cultures such as Minyue, Zhu Xi’s Neo-Confucianism, tea, and porcelain, has preserved a wealth of tangible cultural relics, showcasing a profound cultural heritage and possessing strong research value and development potential. This study employs GIS spatial statistical analysis and map visualization technology to unveil the evolutionary processes of cultural heritage sites in northern Fujian, focusing on their spatial types, forms, and densities across different historical periods. Based on this foundation, the research further delves into the intrinsic relationships between the spatial distribution characteristics of cultural heritage sites in northern Fujian during various historical periods and the local natural and cultural environment. The results indicate that: (1) the spatial distribution of cultural heritage sites in northern Fujian varies across different historical periods, with the highest concentration and quantity observed during the Ming and Qing periods. In contrast, the Qin, Han, Wei, Jin, Northern and Southern Dynasties period exhibits the lowest quantity and a more dispersed distribution. (2) Cultural heritage sites in northern Fujian are mainly distributed in the relatively flat terrain below 400 m above sea level, including middle to low-altitude mountain basins, river valleys, and low hills. In terms of distance from rivers, cultural heritage sites exhibit a clear distribution pattern along rivers, with a large number of them located within 0–6 km from the riverbanks. (3) The spatial distribution of cultural heritage sites in northern Fujian is influenced not only by macro-environmental factors such as topography, altitude, and rivers but also by micro-shaping from social and cultural elements like Minyue culture, tea and porcelain ancient road culture, Zhu Xi’s Neo-Confucianism culture, religious beliefs and customs culture, and red revolutionary culture across different historical periods. This study contributes to the establishment of a model correlating cultural heritage sites with historical periods and provides an interdisciplinary methodological framework to understand the relationship between cultural heritage sites and the geographical environment.

In this work, the 25 species of the flea beetle genus Calotheca Heyden recorded for South Africa are considered. Starting from the updated species distribution and the topographic, temperature, and precipitation variables, as well as the vegetation types in the occurrence sites, through an analysis of ecological niche modelling, a possible ecological profile is provided, both for each species and the entire genus, highlighting some of the factors that drive their occurrence and distribution patterns. Along with the vegetation type, some climatic variables were found to be particularly influential, such as the mean temperature of both the wettest and driest quarters and also the mean precipitation of the wettest period. Finally, comparing the distribution of the areas of highest suitability returned by the model obtained for Calotheca, they largely overlap with the highest-density areas of Searsia, genus of Anacardiaceae, including the main host plants for these flea beetles.

IntroductionCrop Wild Relatives (CWR) have great socioeconomic importance for humans harbouring a broad spectrum of diversity and being important elements of different habitats. Beta vulgaris subsp. maritima ((L.) Arcangeli), also known as sea beet, is an important CWR of cultivated beets (GP-1). The high adaptability of this taxon to different environmental conditions, as well as its tolerance/resistance to different biotic and abiotic stresses, makes it a vital source for sugar beet improvement. Aim of this work was to analyse the in situ and ex situ status of sea beet population conservation in Italy, so as to guide protection activities and new collecting missions.MethodsGeographical distribution data of populations were that occur in the wild and conserved in genebanks were assembled from different databases and submitted to data quality control. Distribution, habitat characterization, land cover and use of the involved sites were then evaluated to provide insight into the current condition of areas hosting this CWR diversity. The presence of populations within vs. outside Italian protected areas was also evaluated. A density analysis of the records was performed and the adequateness of sea beet ex situ conservation, in terms of number of conserved accessions, was finally estimated.ResultsA collection of 138 B. vulgaris subsp. maritima high quality georeferenced records were obtained, mainly distributed into Mediterranean Biogeographic Region. About 22% of the considered populations occurs in protected sites of the Natura 2000 Network, while about 15% in areas recorded in the Official list of protected natural areas (EUAP). Occurrences within protected areas are founded primarily in natural environments, whereas those outside are mainly located in urban and cultivated areas. The comparison of distribution and density analysis results revealed the presence of several gaps between sites hosting in situ populations and sites where ex situ conserved accessions were originally collected.DiscussionHere presented data indicates that the protection status for sea beet in Italy can be considered only partially adequate; more proactive protection measures should be foreseen to increase the role of protected areas in safeguarding in situ conservation. “Out of reserve management” for populations outside protected areas should also be developed, as well as new collecting missions carried out.

The present study falls within the scope of the analysis of the morphodynamic potential of the Bran - Dragoslavele Corridor (Romania), a low mountain area, favorable to erosion processes due to the high energy of the relief, diversified lithology, tectonic complexity, and due to the variation in the energy of atmospheric risk phenomena. For the expansion of pastoral agricultural areas and those intended for human settlements, the deforestation of the last 3-4 centuries deprived the slopes and the soil of the protective forest cover on an area of 55.44%, favoring the amplification of the action of natural morphodynamic agents. In this context, the quantitative and spatial assessment of sheet erosion, expressed as the average annual rate of surface soil erosion (measured in tons hectare–1) was approached by applying the calculation model implemented in the GIS environment by using the universal soil loss equation (USLE). Implementation of the model was realized through the spatial delimitation of the potential erosion and the rendering by susceptibility classes of the quantitative results which reveal the fact that the largest surface of the studied mountain unit (91.68%) presents tolerable values, of 0-1.5 t ha–1 year–1. The highest values, over 4 t ha–1 year–1 (1.24%), are characteristic of the calcareous areas belonging to the many sectors of the gorges with discontinuous vegetation, as well as the limestone exploitation area from Mateiaș mountain. The quantitative knowledge and spatial distribution of surface erosion becomes important for communities and local authorities, interested in the planning and management of the implementation of some agrotechnical measures to improve the quality and productivity of soils or to prevent and restrict erosion processes with a tendency to expand areally and in depth.

Global climate change and rapid urbanization have increased the frequency of flooding, making urban flood resilience a critical objective. This article introduces a methodology for assessing urban flood resilience, utilizing a social-ecological synthesis index that integrates geographical and temporal data with Geographic Information System (GIS). The study focuses on ten administrative subdistricts in Wuhua District, Kunming City, China, and selects 18 social-ecological indicators. These indicators, chosen from social and ecological perspectives, are weighted using the entropy weight method to determine their significance in the assessment system. By combining scores for each subdistrict, the study quantifies flood resilience and creates a spatial distribution map using ArcGIS. Key findings reveal that out of the ten administrative subdistricts, five in Wuhua District, particularly in the core urban area of Kunming, demonstrate strong overall flood resilience. Influenced by social-ecological indicators, there is significant spatial differentiation in flood resilience within Wuhua District, with a decreasing trend radiating from the city center to areas farther from the urban core. The research indicates that regions with well-established transportation infrastructure, a wide distribution of government institutions, improved water management facilities, and a substantial population with higher education levels contribute significantly to enhancing urban flood resilience. HIGHLIGHTS Analyzing urban flood resistance capacity from the perspective of resilience.; Considering the performance of both social and ecological dimensions in urban flood resilience.; Quantifying urban flood resilience through comprehensive index method.; Using geographic information technology to analyse the spatial characteristics of urban flood resilience.;

Toplica district represents an area in Southern Serbia with significant forms of geoheritage that have not been valorized yet. The aim of this pioneering study is to systematically analyze and evaluate all manifestations of the geodiversity in the Toplica district. Based on the geological importance, degree of attractiveness, and size, a total of six geosites were selected. The main goal of the study is to emphasize the insufficient utilization of huge geotourism potentials of the Toplica district and to determine the current geotourism development and geotourism potential of evaluated geosites. The geotourism suitability of each geosite is defined through comparative analysis. The Geosite Assessment Model (GAM) is used to assess the current state of the various elements of geodiversity in the study area. Positioning within the GAM matrix is defined by the values of the investigated parameters. Visualization of the distribution of the GAM indicators is an innovative approach for the interpretation of the obtained results. As a projection of the geotourism potential, the study presents the results of the traffic accessibility of geosites using the Geographic Information System (GIS)-based isochronous method. GIS and Digital Terrain Models are used in the visualization of the research area. The results of GAM apostrophize the current tourist value of Devil’s City, while the isochron analysis of GIS highlights the great geotourism potential of publicly little-known and touristically unaffirmed geosites. The results represent a basis that can support the affirmation of geotourism, the improvement of existing, and the development of new geotourism strategies in the Toplica district.

Understanding the mechanisms whereby parks contribute to cooling urban settings is critical to effectively addressing the challenges posed by rising temperatures in densely populated cities and ultimately improving the quality of urban life. This study employs a spatial approach with advanced analytical techniques, including local entropy mapping, to quantify surface temperature changes induced by urban parks across different geographical areas. Using satellite imagery to estimate land surface temperature (LST) during a heat wave in Mexico City, the study provides a practical approach to understanding the complex relationship between urban park size and urban heat island intensity within 300 m. The study’s findings indicate that while parks exert a cooling influence on their immediate vicinity, the extent of this effect varies spatially and depends on factors such as the size and location of the park and the nature of the surrounding terrain. Specifically, the results indicate that this relationship is not randomly distributed across the urban landscape. Instead, there is a clear pattern of spatial clustering within the city. Consequently, this research underlines the complexity of the problem, emphasizing the indispensable role of urban design and planning strategies to harness the full potential of parks as cooling agents within cities.

Abstract In coastal alluvial plains, the variability of sedimentary inputs, tectonic and eustatism causes a complex subsurface geology which influences the position of fresh/saltwater interface. Furthermore, in these areas densely populated, the over-pumping of freshwater, coupled with the climate change events, promotes the landward migration of freshwater/saltwater boundary. This research illustrates the ability of geophysical tools to recognize the presence of salt/brackish water at Volturno Coastal Plain, Southern Italy. This area is characterized by a peculiar geological setting, due to the proximity at Somma–Vesuvio and Campi Flegrei volcanic areas, which profoundly influences the circulation of groundwater. The subsurface is mainly characterized by: (i) two denser layers located at − 10 m and − 20 m depth which in part prevents the vertical migration of groundwater, (ii) facies heteropy that facilitates the hydraulic connection between the different geological bodies, (iii) a discontinuous Campanian Ignimbrite deposits which favor the hydraulic connection between deeper and shallower aquifers. In this geological framework, 2D-ERT and 3D-ERT integrated with Downhole, Multichannel Analysis of Surface Waves and boreholes made possible to recognize the presence of two main zones with salt and brackish waters, respectively. The first zone, characterized by very low resistivity (≤ 1 Ωm) typical of salt water, stretches 1.5 km inland from the coast. The second zone, with a resistivity between 2 and 5 Ωm typical of brackish water, continues for other 3 km inland. This knowledge is useful for the engagement of all stakeholders (farmers, ranchers and policy makers) in the sustainable use of fresh water and for making water management plan operational tools.

Abstract Grottoes are a comprehensive art treasure trove that integrate architecture, sculpture, and murals. They showcase the historical spiritual civilization of humanity and provide a solid foundation for studying the dissemination and development of Buddhist culture. Gansu Province is an important node on the transmission route of Buddhist culture, constituting a relatively complete and rich history of Buddhist art and cultural history. This article uses GIS technology to systematically analyse the spatial distribution characteristics and spatiotemporal evolution patterns of grottoes in Gansu Province from the Wei Jin to the Ming and Qing dynasties and explores the main factors affecting their distribution. The results indicate the following: (1) the grottoes in Gansu Province exhibit clustering and uneven distribution characteristics, which form the core aggregation area of Qingyang Tianshui City and the secondary aggregation area of Wuwei and Zhangye City. (2) Spatiotemporal characteristics show significant changes in the number and focus of excavation and repair of grottoes in Gansu Province over the years. The Northern and Southern Dynasties, Sui and Tang Dynasties, and Ming and Qing Dynasties had more grottoes than the Wei, Jin, and Yuan Dynasties. The overall centre of gravity shifted from northwest to southeast. Natural factors such as topography, stratigraphy, and hydrology and cultural factors such as politics and transportation significantly impacted the spatial pattern of grotto heritage in Gansu Province. Exploring and studying the spatial layout of grotto heritage from the perspective of historical geography is beneficial for understanding the cultural development and historical changes in Buddhism and is of great significance for the development of landscape environmental protection and utilization of grotto heritage.

In the industrial corridor of Boyacá, Colombia, population growth is accompanied by anthropogenic activities such as industrial operations, vehicle exhaust fumes, mining, smelting, atmospheric deposition, and excessive use of chemical products to promote crop growth. These activities are known to have a significant impact on urban and rural soils, contributing significantly to elevated concentrations of potentially hazardous elements in the environment. This industrial corridor is an area of economic and social development that needs to provide reference information that will allow us to know the state of soil quality to preserve and manage the public and geoenvironmental health of this region. Anthropogenic activities have contributed to the accumulation of potentially hazardous elements in the environment, affecting various levels of life and creating risks with economic and social implications. However, igneous activity or detrital deposition also enriches soils and creates geochemical anomalies in specific locations. In these cases, the identification of potentially hazardous elements involves the determination of likely sources of contamination and their relationship to the geological setting. In this study, the concentrations of As, Cd, Pb, Mn, Fe, Zn, Hg, Cu and Ni were determined in eighty-one soil samples from the Boyacá industrial corridor (Colombia). The sequential trend of the concentrations of potentially hazardous elements was as follows: Fe > Mn > Zn > Ni > Cu> Pb > As > Cd > Hg. Furthermore, the application of spatial analysis criteria in GIS software with multivariate statistical tools and geochemical indices allowed the identification of anthropogenic and geogenic sources. Most of the potentially hazardous elements were found in soils exposed to industrial and agricultural activities, except for iron. This element showed low variability in all samples, regardless of the geological formations. Due to the lack of reference values for potentially hazardous elements in Colombia, the concentrations were compared with the environmental standards of the Environmental Protection Agency (EPA) and the Ecuadorian Ministry of Environment, Water and Ecological Transition (MAE). The results demonstrate the complexity of the soil and represent the first exploratory study of potentially hazardous elements in this industrial corridor. These results are the starting point for the establishment of geochemical background lines in Colombia and for inspection policies for areas where productive activities converge.

The Yellow River Basin is a complex spatial system integrating ecology, economy, culture and society. The research in this paper takes the innovation of cultural heritage in the basin as the fundamental orientation, and analyzes the influence mechanism of digitization on the innovative development of Yellow River culture through GIS. The inter-regional heterogeneity of the digital transformation of the Yellow River culture is examined through the use of the kernel density function. To examine the spatial correlation between the Yellow River basin and the development of cultural digitalization innovations, the gravity model is utilized. The Yellow River cultural industry’s innovation adaption capacity is measured through two indicators: innovation input capacity and innovation absorption capacity. Based on the analysis of the spatial distribution pattern and the trend of spatio-temporal change, it is tentative to observe that there is a possible spatial correlation between the two. The results show that the field energy variation of the Yellow River cultural memory space ranges from 0.0928 to 0.5384, and the distribution has significant spatial dependence. The logarithm of the digitization level of the Yellow River culture in 2019 is mainly concentrated around -2.2, and the overall digital development of cities along the Yellow River has not been polarized. A new framework and reference for protecting cultural heritage and promoting civilization innovation in the Yellow River basin is provided by this paper.

The article aims to look for a way to geographically delineate the notion of target culture in the language textbook “The World We Live in” by Ogasawara et al. (2013) published in Japan for Japanese students and teachers. Looking at the textbooks as cultural artefacts, we identified geographical space within the scope of the sample textbook and analysed the pedagogical context the place names appeared in. By doing that we attempt to find the spatial bias of the book, which is a manifestation of values there inscribed, often called the “hidden curriculum”. The elaborated method, following a seminal study by Risager (2018), is an attempt to adapt the proposed content analysis of the textbooks into GIS tools in order to capture the geographic dimension of the content. The method serves as a stepping stone towards the creation of a model to analyse and identify the attitudes toward the cultural content of educational materials. This will not only enable a more authentic classroom experience responding to the needs of particular groups of students and teachers but also look for ways to make the textbooks more inclusive.

LiDAR-derived digital elevation models (DEMs) have transformed the archaeological study of landscape features, broadened our technical capabilities, and enhanced the accuracy with which terrain relief is described. These models also place demands on how researchers and analysts interpret DEM content in the context of the modern landscape. LiDAR-based DEMs contain modern man-made structures that can significantly influence model properties. Although data are usually filtered and some of these artificial features are removed during bare-earth classification, many terrain interventions remain visible. This large-scale case study applies established methods to a freely available DEM of the Czech Republic in an attempt to evaluate differences between original and filtered DEMs. It applies a fully automated filtering procedure using vector topographic maps to avoid manual corrections that would make the procedure problematic when used on a macro scale. The results of our archaeological GIS analysis demonstrate that this procedure, despite its relative simplicity, can achieve a significantly better representation of a landscape compared to that offered by an unfiltered DEM. Finally, we propose a series of future steps with a view to developing a more comprehensive and accurate model and overcoming its limitations.

The article presents the experience of using GIS technologies to prepare spatial predictors for their further use in modeling and mapping the dynamics of forest ecosystem functions. The study was conducted on the territory of the Dankovsky district forestry, which is located in the south of the Moscow region. GIS analysis of spatial data containing information about the relief and the hydrographic network of the study area was performed. As a result, morphometric values describing the surface runoff and altitude zonality of the study area have been created. The article describes GIS tools that can be used to create thematic geospatial products: slope exposure, steepness and curvature; direction, distance and length of the flow line, total flow; average altitude above sea level and distance to the river. In addition, the boundaries of river catchment basins have been identified by using GIS analysis, within which it is also planned to model climate-regulating forest functions associated with the carbon cycle.

The complex environmental process of soil erosion is crucial to sustainable land management and conservation. This study uses the Universal Soil Loss Equation (USLE) model to understand the intricate interactions that cause soil erosion in Cluj County, Romania, a region susceptible to complex erosion and landslide phenomenon. The established analysis depicts erosion patterns from localised hotspots to regions of relative stability, providing valuable insights into this critical issue. Spatial distribution maps with color-coded gradients show soil erosion risk and identify vulnerable regions, with temporal investigations depicting how environmental changes affect soil erosion, making it relevant to soil conservation and land management. A careful analysis of the USLE model's parameters (Ls, Cs, C, S, K) shows their soil erosion contributions. The erosion rates were graded in five classes in accordance to general practices of USLE modelling, which range from very-low, low, moderate, high and very-high susceptibility to soil erosion. While a significant majority of the county’s surface is represented by very-low and low erosion risk, several hotspots were identified with intense erosion processes that highlights the critical need to implement soil conservation measures in the area. Identifying erosion hotspots and conservation solutions encourages stakeholders to protect soils, and can provide policymakers with useful information for developing improved guidelines for soil and water conservation.

Urbanization has profoundly reshaped the patterns and forms of modern urban landscapes. Understanding how urban transportation and mobility are affected by spatial planning is vital. Urban vibrancy, as a crucial metric for monitoring urban development, contributes to data-driven planning and sustainable growth. However, empirical studies on the relationship between urban vibrancy and the built environment in European cities remain limited, lacking consensus on the contribution of the built environment. This study employs Munich as a case study, utilizing night-time light, housing prices, social media, points of interest (POIs), and NDVI data to measure various aspects of urban vibrancy while constructing a comprehensive assessment framework. Firstly, the spatial distribution patterns and spatial correlation of various types of urban vibrancy are revealed. Concurrently, based on the 5Ds built environment indicator system, the multi-dimensional influence on urban vibrancy is investigated. Subsequently, the Geodetector model explores the heterogeneity between built environment indicators and comprehensive vibrancy along with its economic, social, cultural, and environmental dimensions, elucidating their influence mechanism. The results show the following: (1) The comprehensive vibrancy in Munich exhibits a pronounced uneven distribution, with a higher vibrancy in central and western areas and lower vibrancy in northern and western areas. High-vibrancy areas are concentrated along major roads and metro lines located in commercial and educational centers. (2) Among multiple models, the geographically weighted regression (GWR) model demonstrates the highest explanatory efficacy on the relationship between the built environment and vibrancy. (3) Economic, social, and comprehensive vibrancy are significantly influenced by the built environment, with substantial positive effects from the POI density, building density, and road intersection density, while mixed land use shows little impact. (4) Interactions among built environment factors significantly impact comprehensive vibrancy, with synergistic interactions among the population density, building density, and POI density generating positive effects. These findings provide valuable insights for optimizing the resource allocation and functional layout in Munich, emphasizing the complex spatiotemporal relationship between the built environment and urban vibrancy while offering crucial guidance for planning.

The development of marketing strategies based on temporal and spatial student’s distribution is extremely important in order to win a niche in the market of educational services. The object of the study is information about the place of origin of the Henan Institute of Science and Technology students in 2016 and 2020. The data used are provided by the Office of Academic Affairs of Henan Institute of Science and Technology, which selects identity data of students admitted and registered at the university in 2016 and 2020. The temporal and spatial distribution and spatial aggregation characteristics of the student enrolments are analyzed, as well as factors affecting the quality of the student flows, such as geographic location, total number of students per year, and publicity. The paper uses spatial data analysis (ESDA), which determines the spatial weight between districts. Global Moran’s I index was used for spatial analysis. The analysis carried out on the example of Henan province showed that the number of graduates in each city in a given year directly affects the number of university entrants (in 2020, the largest number of school graduates was recorded in the cities of Zhoukou and Nanyang, which had the highest number of university entrants). The spatial arrangement of colleges and universities is identified as the main factor influencing the recruitment of students of each educational institution. The choice of colleges and universities by applicants and their parents in China is also determined by proximity to large cities, convenient transportation, and employment opportunities. It has been established that advertising educational services of universities is also an additional factor in their popularization and attraction of students. The important achievements and characteristics of the school should be highly summarized to ensure that all the information on the school brand is spread in the whole domain in a comprehensive manner. Different media should be selected for different students from different places. Attention should be paid to the use of new media such as WeChat, Micro-blog, Tiktok etc. Also, a significant role should be given to interpersonal communication and mobilization of the enthusiasm of graduates to increase the popularity of a particular educational institution. Colleges and universities should reflect on themselves, correct in time, and actively establish a complete, effective, and dynamic evaluation mechanism for marketing, to improve marketing strategies, including through surveys of graduates, students, parents and other stakeholders of higher education.

This study was conducted to investigate the stream network formed in Hanyang and the topographic features of the surrounding areas for the purpose of identifying the impact of Hanyang’s stream network on its city formation. To this end, three substudies were conducted: (i) Topographic restoration of late Joseon using a digitized map including the stream network of the Joseon period and a cadastral map; (ii) Identification and explanations of the discrepancies between the digitally restored stream network and the real stream network by superposing the former upon the latter; (iii) Identification of the Hanyang’s stream network on its urban structure. The results of this study can be summarized as follows: First, the waterways derived by GIS analysis and those on the 1912 Cadastral Map were verified to general coincide with each other, but some changed waterways were observed. Second, the watershed and administrative boundaries general coincided.

Road accidents are among the most critical causes of fatality, personal injuries, and financial damage worldwide. Identifying accident hotspots and the causes of accidents and improving the condition of these hotspots is an economical way to improve road traffic safety. In this study, to identify the accident hotspots of “Dehbala” road located in Yazd province-Iran, statistical and non-statistical clustering methods were used. First, the weighting of the criteria was performed by an expert using the AHP method. Hence, the spatial correlation of slope and curvature was calculated by Global Moran’I. Anselin Local Moran index and Getis-Ord Gi* and Kernel Density Estimation were used to identify accident hotspots based on accident location due to the density of points. As a result, four accident hotspots were obtained by the Anselin Local Moran index, three accident hotspots by Getis-Ord Gi*and one accident-prone area were obtained by Kernel Density Estimation method. Three algorithms, k-means, k-medoids, and DBSCAN, were used to identify accident-prone areas or points using non-statistical methods. The dense cluster of each method was considered as an accident-prone cluster. Then the results of statistical and non- statistical methods were intersected with each other and the final accident-prone area was obtained. This study revealed the effect of geometric charcateristics of the road (slope and curvature) on the occurance of accidents.

The article presents the experience of using GIS technologies to prepare predictors of regression models of carbon stocks created using the random forest machine learning method. The study was conducted on the territory of the Dankovsky district forestry, located in the south of the Moscow region. GIS analysis of spatial data containing information about the relief and hydrographic network of the study area was performed. As a result, morphometric values describing the surface runoff and altitude zonality of the study area have been created, which will be considered as predictors of carbon stock modeling. The article describes GIS tools that allow you to create thematic geospatial products: exposure, slope steepness and curvature; direction, distance and length of the flow line, total flow; average altitude above sea level and distance to the river. In addition, the boundaries of river catchment basins have been identified by means of GIS analysis, within which it is also planned to perform carbon stock modeling.

The study of the evolution of regional typology of archaeological cultures is essential in understanding the trajectory of cultural evolution from a temporal and spatial perspective. In this paper, we focused on the Taihu Lake region, one of the six major regional typologies of Neolithic archaeological cultures in China. By utilizing archaeological site data from the Neolithic Era in this region, our study investigates the evolution of typologies in archaeological cultures at both regional and sub-regional scales. From a broad perspective, quantitative methods were used to explore the cultural evolution process in the Taihu Lake region. The degree of social integration and intercultural inheritance can be reflected through the size of the site and the superimposition of cultural layers. In addition, climate and environmental data were combined to investigate its driving factors. Moreover, GIS (Geographic Information System) analysis methods were used to cluster and partition the cultures in the Taihu Lake region. By identifying distinct groups of sites, it is possible to deconstruct and analyze the interior of the cultures to study their distribution patterns and to explore the exchanges and expansions within the cultures. By integrating both research approaches, our study provides a comprehensive analysis of the evolutionary characteristics of the regional typology of archaeological cultures within the Taihu Lake region. These findings contribute to the development of quantitative methods for studying the evolutionary trajectory of archaeological cultural systems.

The dataset of the Red Data Book vascular plants of Transbaikalia was created based on the latest editions of the Red Data Book of the Republic of Buryatia and the Red Data Book of the Zabaikalsky Krai (Russia). The dataset provides the most updated information regarding the distribution of 271 rare vascular plants (2920 distribution records). The distribution of the studied species was recorded during field surveys using GPS navigators, georeferenced from herbarium specimens, and digitised from printed distribution maps. Each entry in the dataset has various attributes, including belt zone, distribution, ecological, and life-form group features. Distribution patterns for various groups of rare and endangered species were analysed by means of QGIS 3.10 software. Our study has revealed a number of localities of vascular plants listed in the Red Data Book and clarified their distribution within the federal Protected Areas of Transbaikalia, among which Tunkinsky National Park has the highest diversity. Distribution of some rare and endangered species falls under federal protection, but some plants, including endemic species, require better protection. Analysis of various belt zones and distribution groups showed their distinct spread within the study region. Among the studied species, mesophytes and short rhizome perennial plants prevailed. It is also important to preserve vascular plants in the Red Data Book outside Protected Areas. Hence, information from our dataset can be useful for conservation monitoring programmes. Our study provides a basis for future conservation activities and can be applied in the establishment of new Protected Areas or Important Plant Areas in Transbaikalia.

The paper presents and discusses the landslide research procedure related to the topography before and after its occurrence, using the comparative analysis of two medium-resolution digital terrain models. The case study is the Jovac mega-landslide—the largest landslide to occur in Serbia in the last 100 years, active for three days in February 1977. The indicators used to determine the volume and movement mechanism were the spatial distribution of elevation differences within the two digital terrain models (DTM), and the analysis of geomorphological features before the landslide. The obtained elevation differences allowed the definition of the approximate landslide volume: 11.6 × 106 m3. All the data obtained indicate that the movement mechanism falls into the category of earthflow.

San Nicola Island, pertaining to the Tremiti Archipelago (Southern Adriatic Sea, Italy), is widely affected by cliff retreat and gravitational phenomena which severely threaten its monumental historical and natural value. In this study, geomorphological features of the area were derived following a stepwise approach, combining multitemporal stereoscopic aerial photo interpretations with morphometric analyses and detailed field surveys. A rockfall susceptibility map was created following a heuristic approach based on morphometric and geothematic parameters, accounting for slope, slope aspect, outcropping lithologies, structural discontinuities density, distance from landslide scarps, and presence of anthropic caves. Cliff sectors set on dolomitic limestones feature the highest susceptibility values, especially along the southeastern sector; medium values, instead, are found along the island flanks and along scarps located within the inner sectors; and the lowest values are detected on summit tabular surfaces. The achieved results were compared with historical maps and seismic data derived from local and national archives and catalogues, respectively. These analyses allowed us to define the role played by litho-structural and tectonic features on landslide occurrence and distribution, and their interplay in driving landscape evolution over centuries. Finally, this work represents a valuable scientific tool to support geomorphological studies for landslide hazard assessment and proper territorial planning in any other small insular areas, showing similar geological–geomorphological features and landscape values.

Deep-seated gravitational slope deformations (DsGSDs) are slope-scale phenomena which are widespread in mountainous regions. Despite interacting with human infrastructures and settlements, only a few cases are monitored with ground-based systems. Remote sensing technologies have recently become a consolidated instrument for monitoring and studying such widespread and slow processes. This paper proposes a three-step novel methodology to analyze the morpho-structural domain of DsGSDs by exploiting the advanced Differential Synthetic Aperture Radar Interferometry (A-DInSAR) technique through (i) the analysis of A-DInSAR measurement point density and distribution defining a coverage threshold; (ii) the assessment of the actual ground deformation with respect to the orientation of phenomena based on slope, aspect, and C-index; and (iii) ground deformation mapping with previously ranked velocity interpolation. The methodology was tested on two differently oriented phenomena: the mainly north–south-oriented Croix de Fana and the mainly east–west-oriented Valtournenche DsGSD, located in the Aosta Valley Region, northern Italy. The results show a variation in the kinematic behavior between the morpho-structural domains, while also considering any other superimposed surficial deformations. This work provides the lines for the implementation of a rapid and low-cost tool based on the use of A-DInSAR measurements which are suitable for assessing the impact of any type of DsGSD on the anthropic facilities and infrastructures in mountainous areas.

Abstract The Central Plains has a long history, rich culture, unique geographical advantages, and profound cultural heritage. The occurrence of ancient cities in the Central Plains marks the formation of Chinese state-level societies. The number, size, and distribution of ancient cities have changed greatly from the late Yangshao to the Xia and Shang Dynasties, which reflects the evolution of settlement and social organization. In this study, Geographic Information System (GIS) spatial database technology was used to establish a spatiotemporal database of ancient cities in the late Yangshao, Longshan, as well as Xia and Shang Dynasties in the Central Plains. This paper uses GIS spatial analysis technology to analyze the relationship between the ancient city distribution and the geographical environment, as well as the evolution of ancient city's shapes and sizes. Furthermore, by using the method of the nearest neighbor distance and gravity center analysis, this paper discusses the agglomeration characteristics and gravity center evolution of ancient cities. The results show that: (1) Most of the ancient cities were distributed in areas below 500 m and within 3 km from the river during the time interval from the late Yangshao to Xia and Shang Dynasties; (2) The shape of the ancient cities gradually changed from circles to squares in the Central Plains, which became a unified model for the later ancient city design; (3) The sizes of the 18 ancient cities in the Yangshao period shared high similarity, with an average area of 20 hectares. The sizes of 24 ancient cities in the Longshan period increased significantly, with an average of 39 hectares. During the Xia and Shang Dynasties, there were 22 ancient cities with an average size of 340 hectares, and the grade of sizes became obvious, marking the entrance into Chinese state-level societies; (4) Cities were scattered in the decentralized pattern during the late Yangshao and Longshan periods, whereas they became agglomerative in Xia and Shang Dynasties. This reflects the evolution of the spatial scopes and social organizational forms; and (5) From the late Yangshao to Xia and Shang Dynasties, the gravity center of ancient cities moved around the Songshan Mountain from the northwest to the southeast and again to the northeast.

The recent development of location detection systems allows to monitor, understand and predict the activity patterns of the city users. In this framework, the research focuses on the analysis of a sample of aggregated traffic data, based on the number of mobile devices detected through a network of 55 Wi-Fi Access Points in Milan. Data was collected over 7 months (January to July 2020), allowing for a study on the impact of the Covid-19 pandemic on activity patterns. Data analysis was based on merging: (i) time series analysis of trends, peak hours and mobility profiles; (ii) GIS-based spatial analysis of land data and Public Transport data. Results showed the effectiveness of Wi-Fi location data to monitor and characterize long-term trends about activity patterns in large scale urban scenarios. Results also showed a significant correlation between Wi-Fi data and the density distribution of residential buildings, service and transportation facilities, entertainment, financial amenities, department stores and bike-sharing docking stations. In this context, a Suitability Analysis Index is proposed, aiming at identifying the areas of Milan which could be exploited for more extensive data collection campaigns by means of the installation of additional Wi-Fi sensors. Future work is based on the development of Wi-Fi sensing applications for monitoring mobility data in real time.

In recent decades, rivers in Southern Italy experienced remarkable channel changes. Studies on this topic are relatively recent, and yet, far from defining a morpho-evolutionary trend that is common to all rivers of this area. The types and roles of the different controlling factors are still debated. In this study, we present preliminary results about the width channel changes of major rivers in the Campania region (Southern Italy) in the last 150 years. The aim is to provide new insights that are useful to define morpho-evolutionary trajectories at a regional scale and shed light on the roles played by controlling factors. To this aim, we carried out a GIS-aided geomorphological analysis of topographic maps and orthophotos. The results showed the existence of at least three main phases of channel width variations. Between the 1870s and 1930s (Phase 1), most of the rivers experienced widening. Between the 1930s and late 1990s (Phase 2), all of the rivers underwent dramatic narrowing at high rates. Finally, from the 1990s onwards, no dominant trend was found and variations were negligible. Land-use changes at the basin scale and rainfall changes at a decadal scale are likely the main controlling factors, while variations in human disturbances and local factors seem responsible for changes in general trends.

In Southern Italy, studies dealing with the analysis of multidecadal land-use/land-cover (LULC) changes at the basin scale are scarce. This is an important gap, considering the deep interrelationships between LULC, soil erosion, and river and coastal dynamics. This study provides a contribution in filling this gap by analyzing the LULC patterns and changes in an area of southern Italy, i.e., the Fortore River basin, which occurred between 1960 and 2018. To this end, we conducted a GIS-aided comparison and analysis of LULC data from 1960, 1990, and 2018, respectively. The LULC changes were analyzed at both the basin and the physiographic unit scale. The results showed that most of the LULC changes occurred between the 1960s and 1990s, while from the 1990s onward, great stability in LULC was evident in the basin. The obtained data were mostly coherent with national-, regional-, and basin-scale trends, although some scale-dependent discrepancies were noted. The river and shoreline dynamics fully reflected the duration and the amount of phases of the changes in LULC stability at the basin scale.

This paper points out the possibilities of better exploitation of marine traffic as well as its connection with other kinds of traffic. Special attention is given to the analysis of 1,081 harbors about their availability during the year. The methods and algorithms used in GIS are buffers, cluster, method of interpolations, and network analysis. The methods used for the purpose of conducting numerical analyses are algorithms that served for the analysis of the network, its transport features, and the connectivity with harbors in terms of geospace. The main results found in this research showed that harbors have good connectivity in the first place with road traffic and after that with air and railroad traffic. According to data from 2019, all traffic lines cover 4.1 × 1015 km, and the road traffic has the most significant potential in connection with the harbors. The most connected harbors and airports are in the east coast of North America, west coast, north Europe, southern Europe, south-east Australia, a central part of Oceania, and south-east Africa. The results in the modified Likert scale between airports and harbors showed medium results. The densest road network is located in the eastern part of USA, western and central part of Europe, and east coast of China. The number of possible connected lines between main road nodes and harbors is 0.8 × 109. This type of traffic showed excellent results and connection with harbors. The number of possible connected lines per month between railroads and harbors is 1.3 × 103. This type of traffic showed low connectivity with the harbors. In the end comparison of harbors with air, road and railroad networks were established. The geographical position of harbors was analyzed, and better understanding was performed on a global scale.

Objective: The World Health Organization formally announced the global COVID-19 pandemic on March 11, 2020 due to widespread infections. In this study, COVID-19 cases in India were critically analyzed during the pre-lockdown (PLD), lockdown (LD), and unlock (UL) phases. Method: Analyses were conducted using geospatial technology at district, state, and country levels, and comparisons were also made with other countries throughout the world that had the highest infection rates. India had the third highest infection rate in the world after the USA and Brazil during UL2.0–UL3.0 phases, the second highest after the USA during UL4.0–UL5.0 phases, and the highest among South Asian Association for Regional Cooperation (SAARC) countries in PLD–UL5.0 period. Results: The trend in the number of COVID-19 cases was associated with the population density where higher numbers tended to be record in the eastern, southern, and west–central parts of India. The death rate in India throughout the pandemic period under study was lower than the global average. Kerala reported the maximum number of infections during PLD whereas Maharashtra had the highest numbers during all LD and UL phases. Eighty percent of the cases in India were concentrated mainly in highly populous districts. Conclusion: The top 25 districts accounted for 70.99%, 69.38%, 54.87%, 44.23%, 40.48%, and 38.96% of the infections from the start of UL1.0 until the end of UL phases, respectively, and the top 26–50 districts accounted for 6.38%, 6.76%, 11.23%, 12.98%, 13.40%, and 13.61% of cases in these phase, thereby indicating that COVID-19 cases spread during the UL period. By October 31, 2020, Delhi had the highest number of infections, followed by Bengaluru Urban, Pune, Mumbai, Thane, and Chennai. No decline in the infection rate occurred, even in UL5.0, thereby indicating a highly alarming situation in India.

Dengue is one of the emerging major public health problems, and its incidence varies with climate conditions. It affects millions of people's lives owing to unusual socioeconomic conditions and epidemiological factors. This study was designed to build a web-based GIS alert system for dengue data management and analysis which would centralize information and make it accessible to all relevant stakeholders before, during, and after crises. Three geographical regions were selected in this study. The user interface of the dengue alert system was developed based upon MapGuide. Results indicate that risk level was mainly associated with Breteau Index. Karachi and Lahore were at their highest risk, i.e., level 4. Islamabad and Chakwal were also at the highest risk, i.e., level 4. Attock had high risk, i.e., level 3 followed by Haripur with minimal level 1. The high Breteau Index showed a direct relationship to high potential transmission of dengue outbreaks, a more significant peak of dengue was the result of monsoons, while smaller peaks were observed due to domestic water storage. Hence, it was concluded that monsoon is the best suitable season for the development of dengue. Web-Based GIS Alert System for dengue data management and analysis was developed, centralizing information and making it accessible to all relevant stakeholders before, during & after a crisis. This program creation will provide a more analytical forum for advising multiple levels of risk and an experimental method for measuring the effect of different factors on risk level distribution by adjusting the component's weighting.

Khulna City is extremely vulnerable to the effects of climate change. The city experiences frequent waterlogging during extreme rainfall events. This research prepared a drainage simulation model considering climate change issues for investigating the extent of waterlogging in the city. Watershed and precipitation were analyzed to examine the existing scenario of the study area. Finally, a Mike Urban-based hydrological simulation model was formulated to investigate the severity of waterlogging. As found by precipitation analysis, 180 mm, 346 mm, and 396 mm rainfall might occur for the 5-year, 50-year, and 100-year return period, respectively. This research identified that volume of overland flow might be affected by climate change-induced rainfall. According to the simulation, 62.52% of the study area was waterlogged with different inundation depths. It was found that traffic movements were severely disrupted and structures were hampered due to waterlogging. 45% paved, 77% brick soling, and 65% unpaved roads were inundated by different inundation levels. On the other hand, 61.1% of structures of the study area were affected by waterlogging. The findings of the research might help the concerned authority in decision-making, especially for the drainage and water-related issues, to solve the waterlogging.

The paper researches the landscape transformation of the surface mines of the Đurđevik coal basin (northeastern Bosnia region), where 35.24 Mt of brown coal were produced in the past 74 years, and 227.40 Mm3 of overburden was excavated and disposed of. This type of coal exploitation caused the formation concave and convex of anthropogenic relief forms which ultimately led to significant landscape transformation. These transformations were identified and geovisualized on the basis of field research and comparative GIS analysis of archival maps, satellite images, Digital Elevation Models and plans of this area. As a result of the research, especially comparative GIS analysis of two prepared terrain models of surface mines, the transformation of hypsometry, slope and aspect, hydrographic network, pedological as well as vegetation cover were determined. Obtained geospatial data are geo-visualized in QGIS, and as a result, thematic maps were created to provide insight into the essence of transformations. Therefore, established indicators of landscape transformation can serve as a significant factor in planning the revitalization and land re-cultivation of devastated areas in the Đurđevik coal basin.

Abstract Background By 2030, the German transport sector needs to achieve additional greenhouse gas savings of 67 million tonnes CO2-eq. and further progress requires swiftly implementable solutions. The fermentation of cereal straw is a promising option. Returning the digestate to the farmland can close agricultural cycles while simultaneously producing biomethane. The world's first large-scale, mono-digestion plant for straw is operational since 2014. The temporal and spatial biomass availability is a key issue when replicating this concept. No detailed calculations on this subject are available, and the strategic relevance of biomethane from straw in the transport sector cannot be sufficiently evaluated. Methods To assess the balance of straw supply and use, a total of 30 data sets are combined, taking into account the cultivation of the five most important cereal types and the straw required for ten animal species, two special crops and 12 industrial uses. The data are managed at district level and presented for the years 2010 to 2018. In combination with high-resolution geodata, the results are linked to actual arable fields, and the availability of straw throughout the country is evaluated using a GIS. Results During the analysis period and based on the assumption that in case of fermentation up to 70% of the straw can be utilised, the mobilisable technical biomass potential for future biomethane production is between 13.9–21.5 Tg fm a−1. The annual potential fluctuates considerably due to weather anomalies. The all-time maximum in 2014 and the minimum for the last 26 years in 2018 are separated by just 4 years and a difference of 7.6 Tg fm. However, large parts of the potential are concentrated only in a few regions and biomethane from straw could provide 57–145 PJ of a low-emission fuel, saving 3–12 Tg CO2-eq. in case of full exploitation. Conclusion Despite the strong fluctuations and high uncertainties, the potential is sufficient to supply numerous plants and to produce relevant quantities of biomethane even in weak years. To unlock the potential, the outcomes should be evaluated and discussed further with stakeholders in the identified priority regions.

This paper presents the results of a geoinformation analysis of the spread of rabies in Vinnytsia region during 2018. The material for the study was the offi cial data from the report of the region laboratory of veterinary medicine of the State Food and Consumer Service of Ukraine. GIS analysis was performed using Quantum GIS software version 3.4.10. The highest incidence of rabies among foxes was observed in the autumn-winter period, especially in November and December. Among cats and dogs, elevated rates were observed from October to May (with a predominance in January-March). Among farm animals, the disease progressed in summer and to a greater extent in early autumn (SeptemberOctober). Outbreaks of rabies in other wild animals were not synchronously associated with fox disease and were reported in winter only in January, during spring (mainly in May) and in early summer. Calculated using standard deviations ellipses, the spatial trends of rabies distribution among diff erent animal species show that the vast majority of rabies cases among foxes were localized in the centre of the region along the western border; among cats more compact, closer to the northern border; among dogs, cases of rabies were scattered throughout the territory and distributed along the northeastern border; among farm animals were localized only in the northern part of the region; among other wild animals were registered almost throughout the region. The identifi cation of "hot spots" allowed to establish zones of maximum rabies density with a rate of 27.8 cases of rabies per kmํ for all species of animals. For foxes, the zones of the highest density (17.9 cases per kmํ) were mainly localized in the areas near Khmelnytsky, Zhytomyr and Cherkasy regions. For cats (9.12 cases per kmํ) they covered the territories of the central and north-eastern districts. For dogs (9.12 cases per kmํ) only in the north-eastern regions. For farm animals (9 cases per kmํ) the location of the hotspots coincided with the areas for cats. Among other wild animals, the highest density (3.71 cases per kmํ) was recorded in the southern part of the regions. The prospect of further research is based on modeling the dynamics of rabies in the Vinnytsia regions.

The priorities of study the epizootic process of any zoonoses should conduct the analysis using new approaches and technologies in developed countries of the world. Since geographic information systems (GIS) are a tool for collecting data from many sources by various methods that, unlike to standard mapping, can organize, store, retrieve, analyze, model, present spatial data and generate forecasts, our goal was to analyze the epizootic situation of rabies in Ukraine using geo-information technologies. To achieve this goal, we needed to collect rabies incidence data, determine the longitude and latitude of geographic coordinates for each case, create a database of all rabies cases and adapt it to run QGIS software. GIS was used for dynamic models in which the spatial distribution of rabies cases for different animal species varied over successive time frames. The use of GIS, unlike classical mapping, allowed the establishment of the epizootic movement directions, species geolocation, dynamic visualization, seasonality dependence, and the identification of the areas with the highest and lowest degree of infected depending not only on the region, but also within the species of each district. In this case, the determination of the epizootic, movement directions showed a move in the east direction for the domestic animals and in the west direction for the wild animals. Identification of the areas with the highest and lowest infected of rabies made it possible to establish that the highest the concentration of rabies cases among wild animals were observed in the Khmelnytskyi and Vinnytsia regions and the lowest was in the Poltava region. Among domestic animals, the highest incidence of rabies occurred in the north-eastern part of the Vinnytsia region, especially on the border with the Kyiv region, as well as in the northeastern part of the Cherkasy and Kirovograd regions, and the lowest in the territory of the Transcarpathian and southern parts of the Odesa region. Thus, the establishment of zones of greatest infected with rabies, understanding the periods of ups and downs of epizootics, the establishment of species the specificity of each region will provide qualitative and effective planning and carrying out control measures in the territory of all regions of Ukraine.

From 2014 to 2016, the number of prevalence of Dengue Hemorrhagic Fever (DHF) and deaths associated with DHF in Indonesia increased. DHF fatal cases were also reported from three administrative units in the Special Region of Yogyakarta, namely Bantul Regency, Gunungkidul Regency, and Yogyakarta City. Two related deaths in Purwosari, a district in Gunungkidul, raised the status of DHF to an outbreak. This study was designed to characterize the spread pattern of DHF in its endemic areas in Purwosari District using the retrospective method, anamnesis, in-depth interviews, Geographic Information System (GIS), and environmental analysis. The kernel density estimation revealed that in 2011-2017, DHF was concentrated in four villages, namely Giriasih, Giricahyo, Giritirto, and Giripurwo. There was a correlation between DHF incidents and physical geographical features of these villages, including proximity to water sources, high vegetation density, elevation, humidity, and rainfall, which created habitats for mosquito growth. A high incidence of DHF has been observed in children (50.8%) and students (57.4%), with most cases (78.7%) showing typical symptoms of the disease. A few of the 61 cases in the district developed into dengue shock syndrome (DSS) and led to death (4.9%), mainly because the public was unable to recognize the warning signs of DHF early and had limited knowledge of required management therapy. Moreover, the preventive or precautionary measures known as the 3M-Plus were not fully implemented yet.

Recurring fires have a significant impact on the dynamics and functioning of forest ecosystems. The fire regime determines conditions of occurrence, spread and long-term consequences of forest fires. A significant change in the fire regime in the natural complex may indicate at possible loss risks of the key components of the ecosystem. This study presents current and historical fire regimes mapping results for the Pechora natural reserve and its surroundings — Kurinsky and Yakshinsky forest districts. The input dataset consists of fire historical fires records for the area taken from several sources: historical fires dataset of the Pechora natural reserve covering period from the second half of the XIX century till nowadays, which was received from both satellite images interpretation and reserve’s records archive analysis; hot spots detected by airborne-based and ground-based means covering period from 1987 to 2011 and the dendrochronological reconstruction of fires in the pine forests of the reserve’s surroundings for a 600-year period. We applied a methodology of mapping forest ecosystems fire regimes at local level for mapping both current and historical fire regimes. The methodology is based on the LANDFIRE classification, which accounts for fires frequency and fires severity. Results analysis of historical fire regimes indicate the dominance of “less than 200 years” fire return rate, associated with low-to-moderate fire severity for the most of the area. As an exception, the mountainous part of the Pechora natural reserve is characterized by a long period of fire return rate. The analysis of current fire regimes has revealed long periods of fire recurrence in both the reserve area and the forest districts area. We also showed a human impact on the increase in fire frequency. An assessment of the deviation of current fire regimes from their historical values showed that current fire regimes are within their normal historical range in most of the study area.

In this paper, a cost-oriented optimization model of station spacing is presented to analyze the influencing factors of station spacing and layout near Shanghai Pudong International Airport. The Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithm is used to cluster and analyze the high population density, and optimize the station layout in the southwest of Pudong International Airport. A spatial analysis of the land use and geological conditions in Pudong New Area is given. Combining the optimal station spacing, ideal location and spatial analysis, five routing schemes to Pudong International Airport are proposed. The DBSCAN and K-means algorithms are used to analyze the “PDIA-SL” dataset. The results show that the space complexity of the HDBSCAN is O(825), and the silhouette coefficient is 0.6043, which has obvious advantages over the results of DBSCAN and K-means. This paper combines urban rail transit planning with the HDBSCAN algorithm to present some suggestions and specific route plans for local governments to scientifically plan rail transit lines. Meanwhile, the research method of station layout, which integrates station spacing, ideal location and spatial analysis optimization, is pioneering and can provide a reference for developing rail transit in metropolises.

During the end of the Bronze Age, the territory of present-day eastern Romania was occupied by Noua communities, belonging to the Noua-Sabatinovka-Coslogeni (NSC) cultural complex. Although these communities have left us a large number of archaeological sites, this period is rather poorly known and understood, mostly because the investigation of Late Bronze Age (LBA) sites is very rare, usually consisting of small test trenches or fieldwalks. The main characteristic of these communities and the subject of our study is represented by the so-called ashmounds (grey, quasi-circular spots, visible on the soil surface, with small elevations and diameters of 25–30 m), present inside most settlements. Our paper aims at highlighting the spatial characteristics of these sites, using GIS (Geographic Information System) tools, as well as aerial photographs, LiDAR (Light Detection and Ranging) measurements, magnetometry and geo-electrical methods, in order to identify the relationship existing between Noua communities and the inhabited environment, in the area known as the Jijia River catchment. Thus, our approach was able to outline the way in which the geographical peculiarities determined the establishment of new settlements, revealing that the human groups from the end of the Bronze Age preferred low terrains with smooth slopes, located in the immediate vicinity of the most important watercourse of the inhabited micro-area. Additionally, our geophysical studies allowed us to confirm the lack of ash located within the ashmound, as well as to signal the possibility that these features have become visible on the soil surface only due to the irreversible damage caused by intensive agricultural processes. Despite the small number of excavations, to this day an important number of studies have been dedicated to the communities and features in question; however, no analysis has yet been performed that unites the tools specific to GIS software with the usage of non-invasive methods (such as aerial photographs, LiDAR measurements and geophysical techniques).

Risks from flooding and poor water quality are evident at a range of spatial scales and climate change will exacerbate these risks in the future. Natural infrastructure (NI), consisting of structural or perennial vegetation, measures that provide multiple ecosystem benefits have the potential to reduce flood and water quality risks. In this study, we intersected watershed-scale risks to flooding and nitrate export in the Mississippi-Atchafalaya River Basin (MARB) of the central U.S. with potential locations of seven NI practices (row crop conversion, water, and sediment control basins, depressional wetlands, nitrate-removal wetlands, riparian buffers, and floodplain levees and row crop change) to prioritize where NI can be most effective for combined risk reduction at watershed scales. Spatial data from a variety of publicly-available databases were analyzed at a 10 m grid cell to locate NI practices using a geographic information system (GIS). NI practices were presented at the regional basin scale and local Iowa-Cedar watershed in eastern Iowa to show individual practice locations. A prioritization scheme was developed to show the optimal watersheds for deploying NI practices to minimize flooding and water quality risks in the MARB. Among the 84 HUC4 basins in the MARB, 28 are located in the Upper Mississippi and Ohio Rivers basins. The Wabash and Iowa-Cedar basins (HUCs 0512 and 0708, respectively) within these basins were found to rank among the uppermost quintile for nearly all practices evaluated, indicating widespread opportunities for NI implementation. Study results are a launching point from which to improve the connections between watershed scale risks and the potential use of NI practices to reduce these risks.

The aim of the article is to present transport accessibility in rural areas in Poland, with a particular emphasis on the problem of transport exclusion. The following research methods were used in the study: literature review, statistical data analysis and GIS analysis. The article presents a transportation picture of rural areas and identifies the main problem issues related to the insufficient accessibility of public transport. The conducted analyses show a significant alienation of the study area which results from underdeveloped public transport and road infrastructure, including pedestrian and bicycle routes. Measures taken by local authorities in this regard show awareness of the problems of the local community, but those authorities do not take sufficient action. The transport exclusion of inhabitants of the analyzed area can be reduced by developing pedestrian and bicycle infrastructure connecting villages with the existing railway network, characterized by a high frequency of trains.

New Caledonia is one of the major biodiversity hotspots. The flea beetle genus Arsipoda (Coleoptera Chrysomelidae) is present with 21 species, all endemic. We investigated, using GIS analyses and ecological niche models, the habitat preferences of these species in terms of vegetation types, altitude, and climate, and assessed the adequacy of knowledge on the spatial parameters affecting the distribution of the genus in New Caledonia. Altitude and geology seem to play an important role in shaping species distribution. Volcanic substrate allows the growth of ultramafic vegetation, which includes most of their host plants. From a biogeographic and conservation perspective, our results report a deep link between Arsipoda species and their habitats, making them particularly sensitive to environmental modifications.

The use of remote sensing indices in order to obtain information for vegetation distributions, heath and patterns is a popular practice with applicability at different scales of detail. The present article presents an example of using the Normalized Difference Vegetation Index (NDVI) and Change Detection method to identify the spatio temporal evolution of forest area in Târgu Lăpuș city, northern Transylvania, Romania. NDVI method is applied at different NDVI threshold values such as 0.1, 0.15, 0.3, 0.45 and 0.6. For the analyzed area, an area of 1.56 km2 with forest gain and 3.59 km2 with forest loss was identified. The advantage of using this method is the large time gap for which it can be done, in our situation being an analysis for the period 1983-2020 so that we can identify the trend of evolution of areas occupied by forests in a city where spatially built it often extends uncontrollably, affecting the degree of compactness of the forests and implicitly their protection functions.