Spatial Analysis Research Articles

Spatial distribution and environmental correlations of Culex pipiens pallens (Diptera: Culicidae)in Haidian district, Beijing.

Culex pipiens pallens Coquillett, 1898(Diptera: Culicidae)was the dominant health threat to mosquito species in Beijing, and it is important to unravel the spatial distribution and environmental correlations of Cx. pipiens pallens in Beijing. 3S technology methods and spatial statistics were used to clarify the distribution pattern. Subsequently, linear and spatial regression were performed to detect the environmental factors linked with the density of Cx. pipiens pallens. The same "middle peak" spatial distribution pattern was observed for Cx. pipiens pallens density at the community, subdistrict, and loop area levels in our study area. In addition, there were various correlated environmental factors at the community and subdistrict scales. At the community scale, the summary values of the Modified Normalized Difference Water Index (MNDWI) in 2 km buffer zone (MNDWI_2K) were negatively correlated, and the summary values of Normalized Difference Built-up Index (NDBI) in 800 m buffer zone (NDBI_800) was positively correlated to the Cx. pipiens pallens density. However, the summary values of Normalized Difference Vegetation Index and Nighttime Light Index significantly affected Cx. pipiens pallens density at the subdistrict scale. Our findings provide insight into the spatial distribution pattern of Cx. pipiens pallens density and its associated environmental risk factors at different spatial scales in the Haidian district of Beijing for the first time. The results could be used to predict the Cx. pipiens pallens density as well as the risk of lymphatic filariasis (LF) infection, which would help implement prevention and control measures to prevent future risks of biting and LF transmission in Beijing.

Programming-free Image-Analysis Workflows for IHC, IF and Spatial Proteomics: More than just Cell Counting

Quantitative analysis of cells using a specific protein marker is one of the most frequently performed tasks in both preclinical and clinical histopathology. The primary alternatives include immunohistochemistry and immunofluorescence. This article will briefly shed some light on the pros and cons of both methods, the main ones being that immunohistochemistry is widely available, but in many laboratories, it is limited to only one marker per image. Utilizing more than one marker can be achieved through methods such as establishing duplex or triplex stains, serial sections, or re-staining. However, immunofluorescence excels where a deep multi-marker characterization of single cells is required. Spatial proteomics systems have recently increased the plexity to as many as 100 parallel markers, allowing advanced co-expression, rare cells, and spatial neighbourhood analyses. Bioinformatic analysis aspects for both modalities are discussed, outlining two generic workflows as they are realised in a professional image analysis software used by biomedical researchers. While cell segmentation and typing are at the core, a number of pre- and post-processing steps, such as tissue detection, comparison of ROIs, hotspot search, spatial clustering or neighbourhood analysis should be performed to provide more comprehensive read-outs.

The COVID-19 pandemic impacted the activities of the Schistosomiasis Control Program in Brazil: is the goal of controlling the disease by 2030 at risk?

Schistosomiasis continues to represent a serious public health problem in Brazil. With the coronavirus disease 2019 (COVID-19) pandemic, several control strategies were suspended, probably compromising the goals of eradicating the disease in the country. We aimed to assess the impact of the COVID-19 pandemic on Schistosomiasis Control Program (PCE) actions in all endemic states of Brazil. We performed an ecological study using spatial analysis techniques. The PCE variables assessed were the population surveyed, the number of Kato-Katz tests, positive cases of schistosomiasis and the percentage of cases treated between 2015 and 2021. The percent change was calculated to verify if there was an increase or decrease in 2020 and 2021, along with time trend analyses provided by the Joinpoint model. Spatial distribution maps were elaborated considering the percent change. The surveyed population decreased in 2020 (-65.38%) and 2021 (-37.94%) across Brazil. There was a proportional reduction in the number of Kato-Katz tests (2020, -67.48%; 2021, -40.52%), a decrease in the percentage of positive cases (2020, -71.16%; 2021, -40.5%) and a reduction in the percentage of treated cases (2020, -72.09%; 2021, -41.67%). Time trend analyses showed a decreasing trend in most PCE variables. The PCE activities were impacted by the COVID-19 pandemic in Brazil and PCE strategies must be urgently reviewed, focusing on investments in all endemic areas.

Elucidating the Functional Mechanism of PTK7 in Cancer Development through Spatial Assembly Analysis Using Super Resolution Imaging.

Protein tyrosine kinase-7 (PTK7) has been reported as a vital participant in the Wnt signaling pathway, influencing tumorigenesis and metastasis. However, their specific roles in the mechanisms underlying cancer development and progression remain elusive. Here, using direct stochastic optical reconstruction microscopy (dSTORM) with aptamer-probe labeling, we first revealed that a weakening clustering distribution of PTK7 on the basal membranes happened as cellular migration increased during cancer progression. This correspondence was further supported by a diminished aggregated state of PTK7 caused by direct enhancement of cell migration. By comparing the alterations in PTK7 distribution with activation or inhibition of specific Wnt signaling pathway, we speculated that PTK7 could modulate cell migration by participating in the interplay between canonical Wnt (in MCF7 cells) and noncanonical Wnt signals (in MDA-MB-231 cells). Furthermore, we discovered that the spatial distribution morphology of PTK7 was also subject to the hydrolysis ability and activation state of the related hydrolase Matrix metallopeptidase14 (MMP14). This function-related specific assembly of PTK7 reveals a clear relationship between PTK7 and cancer. Meanwhile, potential molecular interactions predicted by the apparent assembly morphology can promote a deep understanding of the functional mechanism of PTK7 in cancer progress.

Fiscal decentralization, leader localization, and reduction of pollution and carbon emissions —empirical evidence from China's fiscal “province-managing-county” reform

The fiscal system plays an important role in the government's environmental governance efforts. There is currently no consensus on how fiscal structure adjustments impact pollution and carbon reduction. This paper uses China's fiscal “province-managing-county” reform (FPMCR) implemented in 2004 as a quasi-natural experiment, utilizing panel data from 1670 counties in China from 2000 to 2020 to investigate the impact of fiscal decentralization on reduction pollution and carbon emissions (RPCE), as well as its underlying mechanisms. The results show that (1) from 2000 to 2020, China's RPCE shows an overall trend of fluctuating increase, with its value turning positive after 2013. China's RPCE exhibits a spatial pattern characterized by “lower in the north, higher in the south; higher in the east, lower in the west”. (2) After implementing FPMCR, the RPCE levels in reformed counties decreased by −1.44%, showing that reformed county-level governments prioritize economic development over environmental protection. (3) The mechanism analysis found that after implementing FPMCR, reformed counties experienced a 9.16% increase in nighttime light intensity (NLI), and a 3.99% and 4.34% increase in the number of large-scale industrial enterprises (NLIE) and industrial agglomeration (IA), respectively. This suggests that FPMCR leads to radical urbanization and rapid industrialization in counties, which is detrimental to the improvement of RPCE levels. (4) The spatial heterogeneity analysis found that FPMCR's impact coefficient on RPCE levels in the eastern regions is −1.96%, while in the western regions it is −1.16%. This indicates that reformed counties in the eastern regions are more likely to invest expanded fiscal resources in economic development projects, leading to a decrease in RPCE levels. (5) The temporal heterogeneity analysis found that after the promulgation of the “Three-Year Action Plan to Win the Blue Sky Defense Battle” in 2018, the adverse impact of FPMCR on RPCE is completely reversed, leading to a 1.76% increase in RPCE levels. (6) Further analysis reveals that localizing leaders can slow down the promotion of county-level urbanization and industrialization by the FPMCR, benefiting the improvement of RPCE levels. In other words, “the outsider monk will not recite scriptures as well as a local one”. This study has clarified the causal relationship and underlying mechanisms between fiscal decentralization and environmental governance, providing reliable theoretical support for optimizing grassroots fiscal systems and reducing environmental pollution in other transitional economies. It enriches the field of environmental economics related to fiscal decentralization.

Geopatial Technologies in Civil Engineering : A Critical Literature

This study investigates the role of geospatial technologies in enhancing the efficiency and effectiveness of civil engineering projects. Geospatial technologies, including Geographic Information Systems (GIS), remote sensing, and spatial analysis, have revolutionized the field of civil engineering by providing critical tools for planning, design, construction, and management of infrastructure projects. The integration of these technologies enables accurate terrain mapping, real-time monitoring, and data-driven decision-making, which are crucial for ensuring the safety, sustainability, and resilience of modern infrastructure. This research aims to explore the applications of geospatial technologies in various civil engineering projects, including highway planning, urban development, and environmental monitoring. The study also examines the potential benefits and limitations of these technologies and provides recommendations for their effective integration into civil engineering practices. By understanding the impact of geospatial technologies on civil engineering projects, this research aims to contribute to the development of more efficient, sustainable, and resilient infrastructure that supports the needs of modern society.

Epidemiology of cutaneous leishmaniasis in children of Khyber Pakhtunkhwa, Pakistan.

In Pakistan, cutaneous leishmaniasis is an emerging tropical disease and a very high number (>70%) of children are afflicted by this marring infection. This study aimed to scrutinise the prevalence, spatial distribution and socio-demographic and behavioural risk factors associated with cutaneous leishmaniasis in children aged <5-15 years in Khyber Pakhtunkhwa. A total of 1, 559 clinically confirmed records of children diagnosed with cutaneous leishmaniasis (January-December) from 2020 and 2022 were obtained from selected district hospitals. In addition, a risk factors-related questionnaire was administered to 1, 011 households (400 in 2020 and 611 in 2022) in nine districts during a household survey. The maximum number of cutaneous leishmaniasis cases was recorded in 2022 (n = 877, 56.25%) as compared to 2020 (n = 682, 43.75%). The hospital records showed a greater number of male patients in the 2022 cohort (n = 603, 68.76%). The highest number of cases were observed in children aged 5-9 years in 2022 (n = 282, 32.16%) and 2020 (n = 255, 37.39%). In 2020 and 2022, cutaneous leishmaniasis cases showed peak aggregation in March (n = 118, 17.3%) and January (n = 322, 36.72%). From a spatial analysis, the maximum number of cutaneous leishmaniasis cases was recorded at 59-1700 m elevation in various land-use/land-cover and climatic regions with quaternary alluvium rock formations. A multivariate logistic regression model analysis of risk factors from the households survey suggested that age group, socio-economic status, construction materials of the house, use of insect repellents, Afghan refugee camps in the village/district, knowledge and biting times of sand flies, frequent use of mosquito bed nets, presence of domestic animals in the house, knowledge of the transmission period and peak month of leishmaniasis infection increased the risk of acquiring cutaneous leishmaniasis (p value < 0.05). Our analysis demonstrated that cutaneous leishmaniasis in children is influenced by a variety of environmental, socio-demographic and behavioural risk factors in Khyber Pakhtunkhwa. The increase in recorded cases of cutaneous leishmaniasis in children in 2022 compared to 2020 suggests that the infection likely extended to new foci in the province.

Carbonate mounds formed by mud volcanism at the Cretaceous-Paleogene boundary, Saudi Arabia

More than 1000 mound structures have been mapped in shallow marine sediments at the Cretaceous-Paleogene boundary in the Rub’ Al-Khali of Saudi Arabia. Mapping used 3D reflection seismic data in a 37,000 km2 study area. No wells penetrate the mounds themselves. The mounds are at a present-day subsurface depth of approximately 1 km, and they are convex-up with diameters of 200–400 m and elevation of 10–15 m. The mounds display spatial self-organization with a mean separation of approximately 3.75 km. Comparison with mound populations in other study areas with known spatial distribution statistics and modes of origin indicates that the mound population in this study has the characteristics of fluid escape structures, and they are interpreted here as mud volcanoes. The observation that the mounds occur at the Cretaceous-Paleogene boundary demands a singular trigger at that moment in time. We develop a model of seismic energy-related mud volcanism mechanism including the Chicxulub asteroid impact as the energy source that accounts for the timing of the mound structures and a drainage cell model based on producing water wells that provides a mechanism for spatial self-organization into a regular pattern.

Uneven primary healthcare supply of rural doctors and medical equipment in remote China: community impact and the moderating effect of policy intervention

BackgroundUnequal access to primary healthcare (PHC) has become a critical issue in global health inequalities, requiring governments to implement policies tailored to communities’ needs and abilities. However, the place-based facility dimension of PHCs is oversimplified in current healthcare literature, and formulating the equity-oriented PHC spatial planning remains challenging without understanding the multiple impacts of community socio-spatial dynamics, particularly in remote areas. This study aims to push the boundary of PHC studies one step further by presenting a nuanced and dynamic understanding of the impact of community environments on the uneven primary healthcare supply.MethodsFocusing on Shuicheng, a remote rural area in southwestern China, multiple data are included in this village-based study, i.e., the facility-level healthcare statistics data (2016–2019), the statistical yearbooks, WorldPop, and Chinese GDP’s spatial distribution data. We evaluate villages’ PHC service capacity using the number of doctors and essential equipment per capita, which are the major components of China’s PHC delivery. The indicators describing community environments are selected based on extant literature and China’s planning paradigms, including town- and village-level factors. Gini coefficients and local spatial autocorrelation analysis are used to present the divergences of PHC capacity, and multilevel regression model and (heterogeneous) difference in difference model are used to examine the driving role of community environments and the dynamics under the policy intervention.ResultsDespite the general improvement, PHC inequalities remain significant in remote rural areas. The village’s location, aging, topography, ethnic autonomy, and economic conditions significantly influence village-level PHC capacity, while demographic characteristics and healthcare delivery at the town level are also important. Although it may improve the hardware setting in village clinics (coef. = 0.350), the recent equity-oriented policy attempts may accelerate the loss of rural doctors (coef. = − 0.517). Notably, the associations between PHC and community environments are affected inconsistently by this round of policy intervention. The town healthcare centers with higher inpatient service capacity (coef. = − 0.514) and more licensed doctors (coef. = − 0.587) and nurses (coef. = − 0.344) may indicate more detrimental policy effects that reduced the number of rural doctors, while the centers with more professional equipment (coef. = 0.504) and nurses (coef. = 0.184) are beneficial for the improvement of hardware setting in clinics.ConclusionsThe findings suggest that the PHC inequalities are increasingly a result of joint social, economic, and institutional forces in recent years, underlining the increased complexity of the PHC resource allocation mechanism. Therefore, we claim the necessity to incorporate a broader understanding of community orientation in PHC delivery, particularly the interdisciplinary knowledge of the spatial lens of community, to support its sustainable development. Our findings also provide timely policy insights for ongoing primary healthcare reform in China.

A closure mechanism for screech coupling in rectangular twin jets

The twin-jet configuration allows two different scenarios to close the screech feedback. For each jet, there is one loop involving disturbances which originate in that jet and arrive at its own receptivity point in phase (self-excitation). The other loop is associated with free-stream acoustic waves that radiate from the other jet, reinforcing the self-excited screech (cross-excitation). In this work, the role of the free-stream acoustic mode and the guided-jet mode as a closure mechanism for twin rectangular jet screech is explored by identifying eligible points of return for each path, where upstream waves propagating from such a point arrive at the receptivity location with an appropriate phase relation. Screech tones generated by these jets are found to be intermittent with an out-of-phase coupling as a dominant coupling mode. The instantaneous phase difference between the twin jets computed by the Hilbert transform suggests that a competition between out-of-phase and in-phase coupling is responsible for the intermittency. To model wave components of the screech feedback while ensuring perfect phase locking, an ensemble average of leading spectral proper orthogonal decomposition modes is obtained from several segments of large-eddy simulation data that correspond to periods of invariant phase difference between the two jets. Each mode is then extracted by retaining relevant wavenumber components produced via a streamwise Fourier transform. Spatial cross-correlation analysis of the resulting modes shows that most of the identified points of return for the cross-excitation are synchronised with the guided jet mode self-excitation, supporting that it is preferred in closing rectangular twin-jet screech coupling.

A pathway to urban resilience: investigating green open space priority areas to mitigate the urban heat island phenomenon in Samarinda City, Indonesia

Purpose The potential for massive economic growth exists in Samarinda City due to the intensification of activities in built-up areas. This suggests the potential for increased urban disease in the relocation of Indonesia’s new capital city to a location adjacent to Samarinda. One of the most striking impacts is the urban heat island (UHI). The increase in this phenomenon can be addressed effectively and efficiently through the provision and arrangement of appropriate vegetation-based actions. Therefore, this study aims to identify priority areas of green open space (GOS) based on UHI levels. In addition, this study also aims to present alternative mitigation measures to reduce the risk of disasters due to UHI. Design/methodology/approach A mixed-method approach was used in this research, involving an initial land surface temperature analysis to identify the UHI class. This analysis was complemented by quantitative spatial analyses, such as scoring, overlay and intersect methods, to determine the priority level class and the typology of GOS priority. A qualitative analysis was also conducted through data triangulation or comparison methods, such as examining existing land use, GOS priority maps and spatial plan policies. Findings The findings show that the total UHI area in Samarinda City was 6,936.4 ha in 2019 and is divided into three classifications. In Class 1, the UHI area is very dominant, reaching 87% of the total area. Meanwhile, the main results identified two priority classes of GOS in Samarinda, namely, the medium and high categories with an area of 960.43 ha and 113.57 ha, respectively. The results also showed that there were 17 typologies associated with five alternative mitigation measures: green industry, greening parking lots, improving urban green infrastructure and buildings, urban greening and mining restoration. Research limitations/implications Specific to assessing UHI, image data were available only in medium spatial resolution, leading to a consequence of detailed accuracy. In addition, since the determination of mitigation considered local policies, the method should be used in other locations requiring adjustments to existing regulations, specifically those related to spatial planning. Originality/value This study makes a significant contribution to the understanding of the UHI phenomenon in Indonesia, especially in the urban areas of Kalimantan Island. In addition, the study presents new insights into alternative mitigation actions to reduce the risk of UHI. Innovatively, this study introduces a typology of regions associated with appropriate alternative mitigation actions, making it an important achievement for the first time in the context of this study.

Spatiotemporal characteristics of deep convection initiation in the Central United States

AbstractThis research examines the spatiotemporal characteristics of deep convection initiation (DCI) using a dataset of approximately 182,000 instances of DCI occurring over an 11‐year period in the Central United States. Spatial statistical analysis reveals differences in the frequency of DCI occurrence across the study area. Favoured areas of DCI are most common across areas of higher terrain and in proximity to the Gulf Coast, while DCI occurs less frequently over the northern Great Plains. Spatial differences in the degree of interannual variability of DCI are also noted, with higher (lower) interannual variability generally noted in areas of less (more) frequent DCI occurrence. Unsupervised machine learning is utilized to identify spatial variability in the diurnal cycle of DCI. The data and methods in this study are able to reliably identify more obvious differences in diurnal time series of DCI occurrence, while more subtle differences such as those resulting from localized or weaker mechanisms are identified less reliably. However, from these results it is obvious that spatial variability in the diurnal time series of DCI exists.

Mapping dynamic molecular changes in hippocampal subregions after traumatic brain injury through spatial proteomics

BackgroundTraumatic brain injury (TBI) often results in diverse molecular responses, challenging traditional proteomic studies that measure average changes at tissue levels and fail to capture the complexity and heterogeneity of the affected tissues. Spatial proteomics offers a solution by providing insights into sub-region-specific alterations within tissues. This study focuses on the hippocampal sub-regions, analyzing proteomic expression profiles in mice at the acute (1 day) and subacute (7 days) phases of post-TBI to understand subregion-specific vulnerabilities and long-term consequences.MethodsThree mice brains were collected from each group, including Sham, 1-day post-TBI and 7-day post-TBI. Hippocampal subregions were extracted using Laser Microdissection (LMD) and subsequently analyzed by label-free quantitative proteomics.ResultsThe spatial analysis reveals region-specific protein abundance changes, highlighting the elevation of FN1, LGALS3BP, HP, and MUG-1 in the stratum moleculare (SM), suggesting potential immune cell enrichment post-TBI. Notably, established markers of chronic traumatic encephalopathy, IGHM and B2M, exhibit specific upregulation in the dentate gyrus bottom (DG2) independent of direct mechanical injury. Metabolic pathway analysis identifies disturbances in glucose and lipid metabolism, coupled with activated cholesterol synthesis pathways enriched in SM at 7-Day post-TBI and subsequently in deeper DG1 and DG2 suggesting a role in neurogenesis and the onset of recovery. Coordinated activation of neuroglia and microtubule dynamics in DG2 suggest recovery mechanisms in less affected regions. Cluster analysis revealed spatial variations post-TBI, indicative of dysregulated neuronal plasticity and neurogenesis and further predisposition to neurological disorders. TBI-induced protein upregulation (MUG-1, PZP, GFAP, TJP, STAT-1, and CD44) across hippocampal sub-regions indicates shared molecular responses and links to neurological disorders. Spatial variations were demonstrated by proteins dysregulated in both or either of the time-points exclusively in each subregion (ELAVL2, CLIC1 in PL, CD44 and MUG-1 in SM, and SHOC2, LGALS3 in DG).ConclusionsUtilizing advanced spatial proteomics techniques, the study unveils the dynamic molecular responses in distinct hippocampal subregions post-TBI. It uncovers region-specific vulnerabilities and dysregulated neuronal processes, and potential recovery-related pathways that contribute to our understanding of TBI’s neurological consequences and provides valuable insights for biomarker discovery and therapeutic targets.

Climate model selection via conformal clustering of spatial functional data

AbstractClimate model selection stands as a critical process in climate science and research. It involves choosing the most appropriate climate models to address specific research questions, simulating climate behaviour, or making projections about future climate conditions. This paper proposes a new approach, using spatial functional data analysis, to asses which of the 18 EURO CORDEX simulation models work better for predicting average temperatures in the Campania region (Italy). The method involves two key steps: first, using functional data analysis to process climate variables and select optimal models by a hierarchical clustering procedure; second, validating the chosen models by proposing a new conformal prediction approach to the anomalies associated to each cluster.

Identification of Counterfeit Videos using Deep Learning Methodology

The rise of deep learning has ushered in a proliferation of deep fake videos, posing significant challenges to the credibility of visual content. Our research introduces a groundbreaking approach by merging Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to enhance the accuracy of deepfake prediction. This unique integration, which has not been previously implemented, significantly boosts the model's capability to discern deepfakes. The synergy of CNNs and RNNs in our methodology represents an advancement, contributing to increased accuracy in detecting synthetic content. We leverage CNNs and RNNs for an efficient solution. First, we employ a Res-Next CNN to extract distinctive features from individual video frames, effectively encoding spatial information. These features are then used in the subsequent phase, where a LSTM-RNN models temporal dynamics within the videodata.The temporal aspect is crucial in differentiating deep fake videos due to subtle inconsistencies over time. The LSTM RNN processes the feature sequence, enabling the model to identify temporal patterns unique to deep fakes. This holistic approach, combining spatial and temporal analysis, enhances the model's ability to detect even highly convincing synthetic content. Our model is trained on a comprehensive dataset with rigorous evaluations, demonstrating competitive performance through standard metrics such as accuracy, precision. Practically, our model offers real- time video analysis, automatically identifying deep fake content and mitigating potential risks. Importantly, our approach is simple and robust, suitable for deployment across diverse scenarios. In summary, our research provides an effective solution to the critical issue of deepfake detection. By synergizing CNNs and LSTM-based RNNs, we offer a practical means to uphold the integrity of visual content in an era where digital information authenticity is paramount. Keywords— Deep Learning, CNN, RNN, Deepfake, LSTM, accuracy, precision, visual content, digital information

Geostatistical Analysis of Lineament Domains: The Study Case of the Apennine Seismic Province of Italy

Regional-scale swarms of subparallel linear topographic features, known as lineament domains, are a common feature of planetary surfaces. Lineament domains are superficial manifestations of the crustal stress field trajectory. Notably, one of the effects of active tectonics is seismicity. Italy is one of the most seismically active regions in the Mediterranean, with many destructive earthquakes that have occurred in past centuries. Here, we assess the seismic meaning of the main lineament domain in the tectonically active region of Central Italy. We describe the use of an automated analysis of satellite imagery coupled with spatial grid analysis to identify three lineament domains of the Central Apennines. Spatial and azimuthal comparisons of the main lineament domain (i.e., the Apennine Domain), with the known locations of earthquakes (moment magnitude of Mw &gt; 5.5) that occurred during the past century, revealed the most seismically active tectonic areas and their spatial distributions. Further, we present a conceptual seismo-geodynamic model for the Central Apennines, which is characterized by regional arching and explains the presence of an extensional tectonic regime in the upper crustal layer of the active Apennines fold-and-thrust belt.

Spatial and temporal change of hydrological connectivity in the Wusuli River Basin

Study regionThe study region of this paper is the Wusuli River basin, which is comprised of nine sub-basins. The basin is located on the border between China and Russia. Study focusWe investigated the hydrological connectivity of the Wusuli River basin, an international boundary river that has received little attention. The spatial and temporal evolution of hydrological connectivity over the last 38 years was characterized using a geostatistical connectivity function combined with the remote sensing technique. In particular, some key sub-basins were identified to help strengthen China-Russian cooperation on ecological protection of the basin. New hydrological insights for the regionThe results show that the hydrological connectivity in the northwestern region of the Wusuli River basin was unstable with several surges from 1984 to 2021. Analyzed from a temporal perspective, the effective range of hydrological connectivity is expanding and connectivity is showing an overall upward trend due to increased fluctuations in rainfall. Analyzed from a spatial perspective, the connectivity of the right bank of the Wusuli River is better than that of the left bank due to the influence of topography. Stable connectivity pathways are a must for efficient hydrological connectivity within a watershed. Another finding is that the capacity of the Wusuli River basin to resist extreme rainfall is weakening.

Biological response to Przewalski’s horse reintroduction in native desert grasslands: a case study on the spatial analysis of ticks

BackgroundReintroduction represents an effective strategy for the conservation of endangered wildlife, yet it might inadvertently impact the native ecosystems. This investigation assesses the impact of reintroducing endangered Przewalski's horses into the desert grassland ecosystem of the Kalamaili Nature Reserve (KNR), particularly its effect on the spatial distribution of ticks. In a 25 km2 core area of Przewalski's horse distribution, we set up 441 tick sampling sites across diverse habitats, including water sources, donkey trails, and grasslands, recording horse feces and characteristics to analyze the occurrence rate of ticks. Additionally, we gathered the data of 669 fresh feces of horses. To evaluate the spatial dynamics between these feces and ticks, we used methods such as Fixed Kernel Estimation (FKE), Moran’s I spatial autocorrelation index, and Generalized Linear Models (GLM).ResultsThe dominant species of ticks collected in the core area were adult Hyalomma asiaticum (91.36%). Their occurrence rate was higher near donkey trails (65.99%) and water sources (55.81%), particularly in areas with the fresh feces of Przewalski's horses. The ticks’ three risk areas, as defined by FKE, showed significant overlap and positive correlation with the distribution of Przewalski's horses, with respective overlap rates being 90.25% in high risk, 33.79% in medium risk, and 23.09% in low risk areas. Moran's I analysis revealed a clustering trend of the fresh feces of Przewalski's horses in these areas. The GLM confirmed a positive correlation between the distribution of H. asiaticum and the presence of horse fresh feces, alongside a negative correlation with the proximity to water sources and donkey trails.ConclusionsThis study reveals the strong spatial correlation between Przewalski's horses and H. asiaticum in desert grasslands, underlining the need to consider interspecific interactions in wildlife reintroductions. The findings are crucial for shaping effective strategies of wildlife conservation and maintaining ecological balance.

Architectural and Urban Changes in a Residential Environment—Implications for Design Science

Current spatial changes involving broad urban landscapes affect people’s perceptions of their surroundings, sense of place, and attachment to a place, constituting a disruption to these. As a result, on a social scale, they translate into people’s well-being. The following study of the impact of large-scale architectural and urban developments on the place of residence is based on the assumption that physical space determines the quality of life in the living place and the changes in the process condition residents to adapt to their new surroundings—based on the three pillars of place, people, and process (3Ps). The article consists of two parts. The first is theoretical, which conceptualises spatial change based on the theory of human dependence on place. The second part–an empirical study—discusses the transformation of the post-industrial area of Bicocca (Milan), which, 40 years after the intervention, has led to conclusions and recommendations for urban planning. The results demonstrate the different sensitivities of the urban areas to the process of functional–spatial change, the essence of the accessibility of public space, public facilities, and transport infrastructure. The planning process can positively influence social adaptation to spatial change mitigation. Residential areas may be subject to additional protection procedures. The study is relevant to a sustainable planning process in the inevitable transformation of urban areas. The interdisciplinary nature of the issue prompts the integration of research findings and knowledge transfer in the socio-technological subsystem (STS).

Quantitative monitoring of pollution in Mitrovica Lake using empirical model and geographic information science & systems

ABSTRACT Continuous monitoring of water is crucial for assessing its quality. This paper aims to evaluate water quality in the Artificial Lake of Mitrovica, an area known for heavy metal pollution due to nearby industrial activities. To achieve this, we conducted a comprehensive year-long investigation of the lake, involving the assessment of water quality, spatial analysis, and pollutant evaluation at six different sampling locations, collected in April, June, and September to ensure consistent monitoring. We utilised atomic absorption spectroscopy (AAS) to measure concentrations of arsenic, chromium, copper, nickel, lead, zinc, and cadmium. Indices such as the Heavy Metal Pollution Index (HPI) and Metal Index (MI) were used to assess water quality. Additionally, spatial analysis was conducted using QGIS and Ordinary Kriging to visualise contamination levels across the study area. While many water parameters met international standards, certain sites, particularly those with lead concentrations (Pb2+), exceeded permissible limits, indicating areas of potential concern. This study offers valuable insights for policymaking at both local levels in Mitrovica as well as nationally in Kosova. The study overall emphasises the importance of addressing heavy metal pollution in the region.