Analysis Of Spatial Distribution Research Articles

Spatial distribution and landscape impact analysis of quarrying in the highly fragmented ecosystem of Tandilia system (Province of Buenos Aires, Argentina)

Spatial distribution and landscape impact analysis of quarrying in the highly fragmented ecosystem of Tandilia system (Province of Buenos Aires, Argentina)

Spatial Distribution and Cluster Analysis of Road Traffic Accidents in Khon Kaen Municipality, Thailand

Spatial Distribution and Cluster Analysis of Road Traffic Accidents in Khon Kaen Municipality, Thailand

Spatial Distribution and Differentiation Analysis of Coastal Aquaculture in China Based on Remote Sensing Monitoring

Multiple datasets related to pond and marine aquaculture have been published using diverse remote sensing technologies, yet a comprehensive dataset detailing spatial distribution on both land and sea sides is lacking. Firstly, a meticulous comparison of datasets which we selected related to aquaculture ponds and marine, ensuring consistency in trends. Subsequently, the datasets published by our team were edited and integrated to illustrate aquaculture activities on both sides of China’s coastal zone. Finally, a spatial differentiation of coastal aquaculture in major provinces was analyzed. This analysis also utilizes the types of coastline and statistical data, guiding coordinated resource management efforts. The results unveil a distinctive spatial distribution pattern, concentrating aquaculture in the northern regions—Bohai Sea, Jiangsu, Fujian, and Pearl River coasts in Guangdong. The provinces rich in aquaculture resources, such as Shandong, Guangdong, and Liaoning, exhibit extensive coastlines. However, remote sensing monitoring suggests an underestimation of Liaoning’s marine aquaculture compared to statistical yearbook data. Furthermore, southern provinces like Guangdong and Fujian exhibit significantly higher aquaculture output than Liaoning. Zhejiang leads in fishing output. The paper outlines the future development direction of coastal aquaculture, emphasizing a strategic, integrated land–sea approach for sustainable development.

Spatial Distribution Analysis of Invasive Pheretimoid Earthworms in West Liberty University’s Campus Woods.

The United States is currently amidst a wave of invasion by East Asian pheretimoid earthworms. Multiple genera, genus Amynthas in particular, are widespread invaders with powerful ecosystem engineering capabilities and an expanding range. Invasive populations can reach extreme densities and fluctuate heavily on weekly-to-yearly timeframes compared to other earthworms. Despite their impacts, pheretimoid genera are poorly understood, under-researched, and uncontrolled. A deeper understanding of population dynamics and their mechanisms may allow effective management practices to be developed. The research was conducted in the summer of 2023 in a forest stand at West Liberty University, a known invaded site. Spatial Analysis by Distance Indices (SADIE) was used to analyze weekly distributions of pheretimoids, showing aggregated distributions in 5 of 7 weeks of surveying, 2 of which were statistically significant (P value < 0.05). Linear regression showed no recorded environmental variables were statistically significant (P value < 0.05) in more than 1 out of 7 weeks and were inconsistent in their impact. Population density was reduced during this survey compared to previous years, likely weakening significance due to sample size. Distributions still showed aggregation, suggesting clustering behavior is the norm for pheretimoid worms even at low population sizes. As regression couldn’t adequately explain clustering patterns, more environmental variables and new data analysis techniques may be needed for future work to determine the underlying mechanisms for pheretimoids.

Construction of the Chinese Route of Industrial Heritage Based on Spatial and Temporal Distribution Analysis

In the context of cultural routes, in order to achieve overall protection of industrial heritage, the European Route of Industrial Heritage (ERIH) was established to organize and promote the entire European industrial heritage. The conservation and utilization of Chinese industrial heritage are currently dominated by individual cases, which limits their potential to contribute to regional sustainable development. There is an urgent need of a conservation system at the regional or national level, to ensure that Chinese industrial heritage conservation effectively contributes to regional sustainable development. This study considers the industrial heritage of China built between 1840 and 1978 to establish the Chinese Industrial Heritage GIS Database (CIHGD). The analysis shows that the distribution of China’s industrial heritage is mainly concentrated in the eastern and southern coastal areas, and the industrial heritage has formed three key regions, 14 key cities, and important railway and water systems located in eastern China. The CRIH facilitates the holistic conservation of China’s industrial heritage and provides basic data for future research on China’s industrial heritage. The objective of this study is to promote the establishment of an information-based management system for industrial heritage in China, and to explore the value evaluation, protection system, and regional tourism of industrial heritage from a national perspective in China.

Multivariate Analysis of Rainfall Spatial Distribution and Its Effect on Stormwater Magnitudes

Multivariate Analysis of Rainfall Spatial Distribution and Its Effect on Stormwater Magnitudes

Contribution of regional versus trans-regional anthropogenic sources to the particulate matter over western India derived from high-resolution modeling

Elevated concentrations of particulate matter (PM) significantly deteriorate the air quality; however, the contributions from regional versus remote anthropogenic sources have remained uncertain over the western Indian region. In this regard, we have performed high-resolution regional modeling (WRF-Chem v3.9.1) to quantify the contribution of regional versus trans-regional anthropogenic sources to PM2.5 (fine PM) and PM2.5-10 (coarse PM) concentrations in contrasting seasons. Seasonal variability in spatial mean Aerosol Optical Depth (AOD) derived from the WRF-Chem model (0.21–0.42) agreed reasonably with MERRA-2 reanalysis (0.29–0.54) and MODIS satellite (0.23–0.51) over western India. Variability in surface PM2.5 and PM10 concentrations were also reproduced as per the benchmarks (|Fractional Bias| ≤ 60% and |Fractional Error| ≤ 75%) at most of the stations in this region. Results from sensitivity simulations reveal the dominant contribution of both regional and trans-regional anthropogenic sources to PM2.5 concentrations over western India in winter and post-monsoon, when PM2.5 concentrations are generally high. On the other hand, contribution from background levels (due to domain-wide natural emissions, fire emissions and pollutant transport from beyond domain boundaries) is highest during pre-monsoon and monsoon with a significant contribution of mineral dust especially to PM2.5-10 (coarse PM). Analysis of PM spatial distribution at ∼900hpa pressure level reveals greater relative contributions of trans-regional emissions and background levels compared to that near the surface. Our study highlights key roles of trans-regional anthropogenic emissions and mineral dust, besides the local and regional emissions, in air pollution over western India. The quantitative analyses presented here would be useful for designing measures to minimize health and environmental impacts in line with the objectives of the National Clean Air Programme (NCAP) in India.

Profile and Geospatial Analysis of Dog Bite Cases Attending the Antirabies Vaccine Outpatient Department at the Tertiary Level Hospital of Mumbai.

Dog bites pose a significant public health concern in India, necessitating an understanding of their epidemiological profile and spatial distribution. Adopting the One Health approach, which considers the interconnection of human, animal, and environmental health, is vital for developing effective interventions. The study aimed to assess the epidemiological profile and geospatial trends of dog bite cases in an urban area, focusing on the age and gender distribution of victims, severity of bites, and spatial distribution of cases to inform prevention strategies. A retrospective secondary data analysis was conducted on dog bite cases reported in 2022 at a tertiary care hospital in Mumbai. The epidemiological profile, including age, gender, and severity of bites, was examined. Quantum Geographic Information System (QGIS) was utilized for spatial distribution analysis, identifying hotspots within the urban area. Of the 3350 cases, 70.7% were below 40 years old, 81.6% were male, and 78.18% had Category III bites indicating severe injuries. Most cases (74%) were caused by stray dogs. QGIS analysis revealed five hotspots within the urban area. The study highlights the predominance of dog bites among younger males and the severity of injuries. Spatial analysis identified specific hotspots, underscoring the need for targeted interventions. Implementing a comprehensive surveillance system incorporating GIS technology and adopting a One Health approach can enhance the control and prevention of dog bite cases and reduce the risk of rabies outbreaks.

Epidamnus/Dyrrahchium (Durres) coins and hoard in the Mediterranean territories from 4th to 3rd centuries BC: A spatial distribution analysis

The study of the territorial distribution of Epidamnus/Dyrrahchium coins is a relevant topic in the context of the study of the history of Antiquity, because by studying the history of numismatics, a number of general historical conclusions can be made. The purpose of this article is to study and analyze the territorial distribution of Epidamnus/Dyrrahchium coins in the 4th-3rd centuries BC. In the course of conducting this research, a number of methods were used, in particular: analysis, synthesis, comparison, specification and generalization. As a result of the study, the history of the coinage of Epidamnus/Dyrrahchium was considered, and the characteristic features of the first coins were determined. All the finds of Epidamnus/Dyrrahchium coins were also framed and displayed on the map. It was determined that the coins of the 4th century BC were mostly spread on the coastal area of the Adriatic Sea, which is evidence of maritime trade, and also in Sicily, which is the result of military campaigns. In the 3rd century BC coins of Epidamnus/Dyrrahchium appear in the territory of modern Romania and Bulgaria, which indicates the development of overland trade routes. Many coins were also found in the territory of coastal cities, which indicates a stronger development of sea trade. This article is the first comprehensive study of the territorial distribution of Epidamnus/Dyrrahchium coins, and is useful for historians studying the economic and military aspects of Antiquity.

Numerical simulations of bubbly flows in a vertical periodic channel

In this study, numerical simulations of bubbly flows in an infinitely long vertical channel were performed. Generally, the upper and lower boundaries of such channels are simplified as periodic boundary conditions. Unlike horizontal channel flows, the presence of gravity in the streamwise direction complicates the establishment of periodic boundary conditions. Therefore, a specialized treatment is required to prevent fluid acceleration. Here, we developed a novel treatment for the imposition of periodic boundaries and proposed a new microbubble model to consider the surface tension effect of microbubbles. To detect each bubble in the flow field, we implemented a bubble identification algorithm, which facilitates a thorough statistical analysis of bubble number, size, and spatial distribution. Validation tests were conducted, and good agreement was achieved between our results and reference data. We also confirmed that the results obtained with periodic boundaries are consistent with those achieved without them. Finally, we simulated the evolution of rising bubble swarms in a quiescent liquid. The method presented here contributes to the numerical simulations of bubbly flows in industrial systems, including oil-gas transportation, bubble columns, and nuclear reactors.

Correlation Analysis of Urban Road Network Structure and Spatial Distribution of Tourism Service Facilities at Multi-Scales Based on Tourists’ Travel Preferences

Harbin, as a popular tourist city in China, and the host of the 2025 Asian Winter Games, boasts rich tourism resources and significant potential for further development. The structure of the urban road network is a crucial factor influencing the spatial distribution of tourism service facilities. However, the current research on the correlation between the two, analyzed at multiple scales based on tourists’ travel preferences, is not sufficient. First, utilizing the questionnaire survey method to analyze tourists’ travel preferences and combining it with the theory of 15-min life circle, we determine the study scales at 500 m, 1000 m, 3000 m, and 5000 m. Secondly, the integration value and choice value of roads in the main urban area of Harbin are analyzed based on the theory of spatial syntax. The spatial distribution characteristics of tourism service facilities are then revealed through kernel density analysis. Finally, the correlation between the road network structure and the distribution of various types of tourism service facilities in Harbin at different scales is determined through buffer analysis and Pearson bivariate correlation analysis. The results show that: (1) Integration value plays a significant positive role in promoting the clustering of tourism service facilities, especially tending to cluster in areas with high integration value formed at a scale of 500 m; (2) At the scale of 3000 m, the distribution of tourism service facilities exhibits a significant correlation with the choice value; (3) The correlation between dining, shopping, and entertainment facilities and the integration value decreases with the increase in scale, whereas the spatial distribution of accommodation and attraction facilities does not exhibit a regular pattern with changes in integration value. In addition, this paper also puts forward targeted suggestions for optimizing the urban road network structure, reasonably locating tourism service facilities, and implementing balanced regional development. The contribution of this study is that it will help improve tourists’ travel experience in the city and provide scientific support for promoting the overall sustainable development of tourism in Harbin.

Abstract 6098: Spatial single-cell immune microenvironment analysis reveals the transition from innate to adaptive immune response during early lung adenocarcinoma carcinogenesis

Abstract Introduction: Lung cancer remains the leading cause of cancer death worldwide. Although prevention holds the promise to reduce lung cancer mortality, the results from randomized trials have been disappointing, likely due to our rudimentary knowledge of early lung cancer carcinogenesis. Cancer initiation and progression involve complex processes dependent on the dynamic interplay of individual cells within the tumor microenvironment (TME). Our understanding of the multicellular composition, interaction, spatial distribution, and functional dynamics during the early evolution from precancer to invasive LUAD is limited. Methods: We performed spatial single cell immune microenvironment analysis of 10 normal, 40 AAH, 22 AIS, 18 MIA, and 34 IAC by Imaging Mass Cytometry (IMC) and analyzed high-dimensional images of 1,618 regions-of-interest (ROIs) using a 34-plex marker. Using machine learning approaches, we classified 4,828,879 cells into 14 major cell types, which were subjected to further analysis for multicellular composition, interaction, spatial distribution, and functional dynamics in LUAD precursors of different stages. Results: From AAH to AIS, MIA, and IAC, we observed a gradual escalation in the density (number of cells/mm2) of all immune subsets. Proportionally, adaptive immune cells exhibited a progressive increase, whereas innate immune cells demonstrated a concurrent decrease with the neoplastic progression from normal lung to AAH, AIS, MIA, and ADC. Notably, macrophages emerged as the predominant immune cells within the immune microenvironment of these LUAD precursors. Upon closer examination of subtypes, protumor M2 macrophages showed a gradual increase from AAH to AIS, MIA, and IAC, whereas anti-tumor M1 macrophages increased from normal to AIH, AIS and subsequently decreased in AIS, MIA, and IAC stages. These alterations resulted in a progressive increase in M2/M1 ratios from AAH to IAC stages. Furthermore, M2 macrophages exhibited higher heterotypic interactions with epithelial cells than M1 across LUAD precursors of different stages, especially in the later stages. Co-expression analysis revealed 5 modules that distinguishes each histological stage. Tim-3 module was significantly enriched in AAH lesions, while NK cell-related features were enriched at AIS stage, B cell-related features enriched at MIA stage and Ki-67-related adaptive immune features enriched in IAC stage. Conclusion: The spatial single cell immune microenvironment analysis revealed a transition from innate to adaptive immunity during initiation and early progression of LUAD progression and innate immunity may play critical roles during early LUAD development. Therefore, reprograming innate immunity such as repolarization of M2/M1 may provide avenues to intercept LUAD precursors to prevent invasive LUAD. Citation Format: Bo Zhu, Pingjun Chen, Muhammad Aminu, Junya Fujimoto, Lingzhi Hong, Andre L. Moreira, Jian-Rong Li, Yanhua Tian, Luisa M. Solis Soto, Parra Cuentas Edwin Roger, Ou Shi, Hong Chen, Frank R. Rojas, Eduardo Vilar, Anirban Maitra, Ken Chen, Nicolas Navin, Cara L. Haymacker, Vamsidhar Velcheti, Daniel H. Sterman, P Andrew Futreal, Don L. Gibbons, Ignacio I. Wistuba, John V. Heymach, Chao Cheng, Harvey I. Pass, Jia Wu, Jianjun Zhang. Spatial single-cell immune microenvironment analysis reveals the transition from innate to adaptive immune response during early lung adenocarcinoma carcinogenesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6098.

Abstract 913: Automated reasoning artificial intelligence (AI) to model the cell-cell biochemical and cellular interactions in the tumor microenvironment (TME) of oral cancer (OC)

Abstract Our goal was to study the spatial complexity of HPV negative OC by integrating scRNAseq and spatial transcriptomics from 11 samples including 5 from never smokers never drinkers (NSND). We used Turing Biosystems proprietary graph database engine and automated reasoning AI to analyze and model the cell-cell biochemical and cellular interactions in the TME. The tumors H&E images, Visium 10X, and single cell 10X data were pre-processed using standard methods. QC-based genes and cells filtering, gene expression normalization, dimensionality reduction, clustering of Visium spots, and identification of spatially variable genes were performed. We generated multiple networks from tumor data and prior biological knowledge to integrate different layers of information: single-cell and spatial transcriptomics data, cell-cell interactions networks, cell neighboring, spatial correlation networks. We first used a novel network-based technique to identify the spatial distribution of any cell subtypes (e.g. CAF, T cells), by integrating differentially expressed genes from scRNAseq, prior knowledge and prior data (e.g. TCGA). We used a multilayer network approach to integrate the different networks of data and an automated reasoning AI analysis which allows to interpret the results based on a reasoning on biological and clinical knowledge in opposition to machine learning methods based on statistical patterns. We identified CAFs/T cells/IFN-g to be strongly correlated within the tumor islets interacting with the stroma in NSND while they were more correlated within the stromal regions in smokers. We also identified 2 or 3 subtypes of tumor islets areas based on their functional states (e.g., immune pathways activated or metabolic differences), allowing us to unravel a more detailed map of the intratumoral heterogeneity when compared to histopathology annotations. In order to get some insights into the functional impact of the spatial distribution of cells, the tumors were then represented as multilayer networks to identify all possible cell-cell interactions in the TME. This was followed by a spatial simulation of these interactions using logic (e.g., inhibition, activation) and correlative (e.g., gene expression, imaging features correlations) interactions in the networks to identify spatial interactions. From that we analysed all the possible known protein-protein and metabolite-protein interactions between the cell types analysed and mapped the tumors with the gene expressions corresponding to the pairs of interacting proteins (or enzymes linked to metabolites). We found an interaction between CAF and Tregs via CXCL12 (CAFs) and CXCR4 (Tregs). In conclusion, automated reasoning AI integrating scRNAseq and spatial transcriptomics allows an in-depth analysis of cells spatial distribution and its functional impact in OC. Citation Format: Karène Mahtouk, Maxime Vincent, Yannick Le Meitour, Béatrice Vanbervliet-Defrance, Sonia Canjura, Cyril Degletagne, Laurie Tonon, Lucas Michon, Jebrane Bouaoud, Aude Excoffier, Philippe Zrounba, Rémy Boutonnet, Adam Amara, Pierre Saintigny. Automated reasoning artificial intelligence (AI) to model the cell-cell biochemical and cellular interactions in the tumor microenvironment (TME) of oral cancer (OC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 913.

Characterization and function of particulate organic matter: Evidence from lakes undergoing ecological restoration

Particulate organic matter (POM) plays a crucial role in the organic composition of lakes; however, its characteristics remain poorly understood. This study aimed to characterize the structure and composition of POM in Lake Baiyangdian using many kinds of techniques and investigate the effects of different extracted forms of POM on water quality. The suspended particulate matter in the lake had complex compositions, with its components primarily derived from aquatic plants and their detritus. The organic matter content of the suspended particulate matter was relatively high (organic carbon content 27.29–145.94 g/kg) for the sum of three extractable states (water-extracted organic matter [WEOM], humic acid, and fulvic acid) and one stable bound state (humin). Spatial distribution analysis revealed that the POM content in the water increased from west to east, which was consistent with the water flow pattern influenced by the Baiyangdian water diversion project. Fluorescence spectroscopy analysis of the WEOM showed three prominent peaks with excitation/emission wavelengths similar to those of dissolved organic matter peaks. These peaks were potentially initial products of POM conversion into dissolved organic matter. Furthermore, the intensity of the WEOM fluorescence peak (total fluorescence peak intensity) was negatively correlated with the inorganic nitrogen concentration in water (p < 0.01), while the intensity of the HA fluorescence peak showed a positive correlation with the inorganic nitrogen concentration (p < 0.01). This suggested that exogenous organic matter inputs led to the diffusion of alkaline dissolved nitrogen from sediment into water, while degradation processes of aquatic plant debris contributed to the decrease in inorganic nitrogen concentrations in the water column. These findings enhance our understanding of POM characteristics in shallow lakes and the role of POM in shallow lake ecosystems.

Local electric field enhancement in the vicinity of aggregates of Ag, Au, Rb containing nanoparticles in oxide glasses

Local electric field (LEF) distribution near Ag, Au, AgAu NPs synthesized by UV laser or temperature treatments, and near simulated Rb, AgRb, AuRb NPs in oxide glasses, was studied considering aggregates of 10–15 particles - necessary condition for description of optical extinction spectra. For efficient analysis of LEF spatial distributions under different sizes, components, agglomerations of NPs in these aggregates, approach was proposed that enables to obtain dependence of averaged LEF enhancement upon the distance from the nearest particles in aggregate. This approach reproduced enhancement of Er3+ luminescence intensity in zinc-tellurite glass after formation of Ag NPs and showed that average LEF enhancement per hypothetical Rare Earth ion (REI) is largest for aggregates of Ag, less for Rb, lowest for Au NPs. The optimal Ag NPs aggregate was estimated for best LEF enhancement per hypothetical REI. Simulated aggregates of Rb containing NPs demonstrated strong LEF, shifted in a wide range.

Long-term spatiotemporal variations of ammonia in the Yangtze River Delta region of China and its driving factors

This study focuses on the spatiotemporal distribution, urban-rural variations, and driving factors of ammonia Vertical Column Densities (VCDs) in China's Yangtze River Delta region (YRD) from 2008 to 2020. Utilizing data from the Infrared Atmospheric Sounding Interferometer (IASI), Generalized Additive Models (GAM), and the GEOS-Chem chemical transport model, we observed a significant increase of NH3 VCDs in the YRD between 2014 and 2020. The spatial distribution analysis revealed higher NH3 concentrations in the northern part of the YRD region, primarily due to lower precipitation, alkaline soil, and intensive agricultural activities. NH3 VCDs in the YRD region increased significantly (65.18%) from 2008 to 2020. The highest growth rate occurs in the summer, with an annual average growth rate of 7.2% during the period from 2014 to 2020. Agricultural emissions dominated NH3 VCDs during spring and summer, with high concentrations primarily located in the agricultural areas adjacent to densely populated urban zones. Regions within several large urban areas have been discovered to exhibit relatively stable variations in NH3 VCDs. The rise in NH3 VCDs within the YRD region was primarily driven by the reduction of acidic gases like SO2, as emphasized by GAM modeling and sensitivity tests using the GEOS-Chem model. The concentration changes of acidic gases contribute to over 80% of the interannual variations in NH3 VCDs. This emphasizes the crucial role of environmental policies targeting the reduction of these acidic gases. Effective emission control is urgent to mitigate environmental hazards and secondary particulate matter, especially in the northern YRD.

Remote sensing perspective in exploring the spatiotemporal variation characteristics and post-disaster recovery of ecological environment quality, a case study of the 2010 Ms7.1 Yushu earthquake

Natural hazards usually cause heavy casualties and vast economic losses, as well as severe damage to the ecological environment. Quantitative and scientific evaluations of the ecological environment quality (EEQ) and its recovery trend after hazards can provide valuable insights for disaster risk reductions. This study takes the 2010 Ms7.1 Yushu earthquake as an example to explore the spatiotemporal changes and driving mechanisms of EEQ before and after the earthquake using remote sensing and GIScience. First, the Moderate-resolution Imaging Spectroradiometer (MODIS) data was selected to establish the remote sensing based ecological index (RSEI). Then, we analyzed the spatiotemporal characteristics of Yushu’s EEQ from 2001 to 2020 and explored spatial autocorrelation relationships. Last, the driving mechanism of EEQ recovery in Yushu was analyzed using the GeoDetector model. The main conclusions are as follows: (1) From the perspective of the RSEI time series, the EEQ in Yushu County was strongly negatively affected during the earthquake and recovered well after the earthquake. (2) Based on a spatial distribution analysis, it can be observed that the regions in Yushu with relatively high EEQ are primarily concentrated in the central and southern areas. Conversely, the northwestern and southeastern areas display relatively lower quality. Moreover, the EEQ in Yushu County has a strong correlation and clustering, as evidenced by Moran’s I value exceeding 0.7 over the years. (3) Based on the GeoDetector results, elevation and population were found to be the key driving factors affecting changes in post-disaster EEQ. The interaction between elevation and slope plays the most critical role in the process of ecological recovery. This study provides a theoretical basis for the evolution of the post-disaster ecological environment in Yushu County and helps decision-makers better balance the relationship between social development and environmental protection in disaster management and urban planning. It also provides useful reference and guidance for future ecological protection and recovery under similar disasters.

DEM-based topographic change detection considering the spatial distribution of errors

ABSTRACT Digital Elevation Model (DEM) errors tend to be spatially correlated, inevitably affecting DEM-based topographic change detection. Traditional topographic change detection methods often ignore the spatial distribution of the DEM error. This paper aims to develop a workflow that considers the spatial autocorrelation of the error in topographic change detection. Firstly, the DEM of Difference (DoD) is obtained from two-period DEMs, and the Monte Carlo method is employed to evaluate the Spatially Distributed Errors (SDE) in DEMs. Secondly, DoD errors are calculated by propagation based on spatially distributed DEM errors. At the same time, its spatial distribution is quantified using the semi-variance function. Finally, topographic changes (erosion, deposition, and net changes) are calculated based on the spatial distribution analysis and significance detection. The results in two small catchments indicate that DEM errors are spatially correlated, increasing the volume calculation errors. However, using Standard Deviation of Errors (SDE) instead of Root Mean Square Error (RMSE) can effectively reduce the sensitivity of the detection results in the significance threshold. When the significance threshold increases from 68% to 95%, the observations loss using the spatially distributed error is 4.67% −6.92% lower than that using the RMSE. The level of detection has little impact on the net topographic change and significantly influences gross erosion and deposition. In particular, the use of level of detection can effectively reduce the misclassification of erosion or deposition in stable topography areas. The proposed method can be effectively utilized in various applications like surface deformation monitoring, erosion monitoring, and sediment transport assessment.

Absorption and translocation of selected pharmaceuticals in Pistia stratiotes: Spatial distribution analysis using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Phytoremediation can eliminate pharmaceuticals from aquatic environments through absorption; however, understanding of absorption and transport processes in plants remains limited. In this study, a matrix-assisted laser desorption/ionization time-of-flight mass spectrometry imaging (MALDI-MSI) method was developed to explore the absorption and translocation mechanisms of seven common pharmaceuticals in Pistia stratiotes. Results showed that 2,3-dicyanohydroquinone, an infrequently used matrix, exhibited outstanding performance in MALDI-MSI analysis, producing the highest signal intensity for four of the seven pharmaceuticals. Region of Interest (ROI) analysis revealed that charge speciation of pharmaceuticals significantly influenced their ability to enter vascular bundle. Neutral and positively charged pharmaceuticals easily entered vascular bundle, while negatively charged pharmaceuticals faced difficulty. ROI results for neutral and negatively charged pharmaceuticals exhibited positive correlation with their transfer factor values, indicating that their translocation ability from root to shoot was related to their capacity to enter vascular bundle. However, no correlation was observed for positively charged pharmaceuticals, suggesting that these compounds, upon entering vascular bundle, encountered difficulties in upward translocation through the xylem. This study introduces an innovative approach and offers novel insights into the retention and migration of pharmaceuticals in plant tissues, aiming to enhance the understanding of pharmaceutical accumulation in plants. Environmental implicationPharmaceuticals in aquatic environment can inflict detrimental effects on both human health and ecosystem. Phytoremediation can remove pharmaceuticals from aquatic environments through absorption. However, our understanding of absorption and transportation of pharmaceuticals in plants remains limited. This study developed a matrix-assisted laser desorption/ionization time-of-flight mass spectrometry imaging (MALDI-MSI) method for pharmaceuticals in plant roots, and to explore the absorption and translocation mechanisms of pharmaceuticals. The study offers direct evidence of differences in accumulation behavior of pharmaceuticals in plants, providing valuable insights for targeted and effective strategies in using plants for remediating the aquatic ecosystem from pharmaceuticals.

Three‐dimensional Modeling of Ore‐forming Elements and Mineralization Prognosis for the Yechangping Mo Deposit, Henan Province, China

AbstractThree‐dimensional geochemical modeling of ore‐forming elements is crucial for predicting deep mineralization. This approach provides key information for the quantitative prediction of deep mineral localization, three‐dimensional fine interpolation, analysis of spatial distribution patterns, and extraction of quantitative mineral‐seeking markers. The Yechangping molybdenum (Mo) deposit is a significant and extensive porphyry‐skarn deposit in the East Qinling–Dabie Mo polymetallic metallogenic belt at the southern margin of the North China Block. Abundant borehole data on ore‐forming elements underpin deep geochemical predictions. The methodology includes the following steps: (1) Three‐dimensional geological modeling of the deposit was established. (2) Correlation, cluster, and factor analyses post delineation of mineralization stages and determination of mineral generation sequence to identify (Cu, Pb, Zn, Ag) and (Mo, W, mfe) assemblages. (3) A three‐dimensional geochemical block model was constructed for Mo, W, mfe, Cu, Zn, Pb, and Ag using the ordinary kriging method, and the variational function was developed. (4) Spatial distribution and enrichment characteristics analysis of ore‐forming elements are performed to extract geological information, employing the variogram and w(Cu + Pb + Zn + Ag)/w(Mo + W) as predictive indicators. (5) Identifying the western, northwestern, and southwestern areas of the mine with limited mineralization potential, contrasted by the northeastern and southeastern areas favorable for mineral exploration.