Spatial Analysis Research Articles

Refining Long-Time Series of Urban Built-Up-Area Extraction Based on Night-Time Light—A Case Study of the Dongting Lake Area in China

By studying the development law of urbanization, the problems of disorderly expansion and resource wastage in urban built-up areas can be effectively avoided, which is crucial for the long-term sustainable development of cities. This study proposes a high-precision urban built-up-area extraction method for county-level cities for small and medium-sized towns in county-level regions. Our process is based on the Defense Meteorological Satellite/Operational Linescan System (DMSP/OLS) and the NASA/NOAA Visible Infrared Imaging Radiometer Suite (VIIRS), which develops long-term series of coordinated night-time light (NTL) datasets. We then combined this with the Normalized Vegetation Index (NDVI) to calculate the Vegetation-Adjusted NTL Urban Index (VANUI). We combine land use data and a support vector machine (SVM) for semi-supervised classification learning to propose a high-precision urban built-up-area extraction method for county-level cities. We achieved the following results: (1) we fit binary polynomials to the DMSP/OLS and VIIRS NTL datasets based on the correspondence of the mean values to construct a consistent time series of NTL data. (2) Our method effectively improves the accuracy of urban built-up-area extraction, especially for county-level cities, with an overall accuracy of 91.84% and a Kappa coefficient of 0.83. (3) Our method can perform a long-time series of urban built-up-area extraction, and, by studying the spatial and temporal changes in urban built-up areas, it can provide valuable information for sustainable urban development and urban planning.

Refining Long-Time Series of Urban Built-Up-Area Extraction Based on Night-Time Light—A Case Study of the Dongting Lake Area in China

By studying the development law of urbanization, the problems of disorderly expansion and resource wastage in urban built-up areas can be effectively avoided, which is crucial for the long-term sustainable development of cities. This study proposes a high-precision urban built-up-area extraction method for county-level cities for small and medium-sized towns in county-level regions. Our process is based on the Defense Meteorological Satellite/Operational Linescan System (DMSP/OLS) and the NASA/NOAA Visible Infrared Imaging Radiometer Suite (VIIRS), which develops long-term series of coordinated night-time light (NTL) datasets. We then combined this with the Normalized Vegetation Index (NDVI) to calculate the Vegetation-Adjusted NTL Urban Index (VANUI). We combine land use data and a support vector machine (SVM) for semi-supervised classification learning to propose a high-precision urban built-up-area extraction method for county-level cities. We achieved the following results: (1) we fit binary polynomials to the DMSP/OLS and VIIRS NTL datasets based on the correspondence of the mean values to construct a consistent time series of NTL data. (2) Our method effectively improves the accuracy of urban built-up-area extraction, especially for county-level cities, with an overall accuracy of 91.84% and a Kappa coefficient of 0.83. (3) Our method can perform a long-time series of urban built-up-area extraction, and, by studying the spatial and temporal changes in urban built-up areas, it can provide valuable information for sustainable urban development and urban planning.

Diffusion Basis Spectrum Imaging of White Matter in Schizophrenia and Bipolar Disorder.

Multiple studies point to the role of neuroinflammation in the pathophysiology of schizophrenia (SCZ), however, there have been few in vivo tools for imaging brain inflammation. Diffusion basis spectrum imaging (DBSI) is an advanced diffusion-based MRI method developed to quantitatively assess microstructural alternations relating to neuroinflammation, axonal fiber, and other white matter (WM) pathologies. We acquired one-hour-long high-directional diffusion MRI data from young control (CON, n =27), schizophrenia (SCZ, n =21), and bipolar disorder (BPD, n =21) participants aged 18-30. We applied Tract-based Spatial Statistics (TBSS) to allow whole-brain WM analyses and compare DBSI-derived isotropic and anisotropic diffusion measures between groups. Clinical relationships of DBSI metrics with clinical symptoms were assessed across SCZ and control participants. In SCZ participants, we found a generalized increase in DBSI-derived cellularity (a putative marker of neuroinflammation), a decrease in restricted fiber fraction (a putative marker of apparent axonal density), and an increase in extra-axonal water (a putative marker of vasogenic edema) across several WM tracts. There were only minimal WM abnormalities noted in BPD, mainly in regions of the corpus callosum (increase in DTI-derived RD and extra-axonal water). DBSI metrics showed significant partial correlations with psychosis and mood symptoms across groups. Our findings suggest that SCZ involves generalized white matter neuroinflammation, decreased fiber density, and demyelination, which is not seen in bipolar disorder. Larger studies are needed to identify medication-related effects. DBSI metrics could help identify high-risk groups requiring early interventions to prevent the onset of psychosis and improve outcomes.

Advancing battery safety: Integrating multiphysics and machine learning for thermal runaway prediction in lithium-ion battery module

The safety concerns associated with lithium-ion batteries (LIBs) have led to the development of a novel framework combining advanced machine learning (ML) techniques with multiphysics modeling. Herein, we report an ML framework aiming to predict the occurrence of thermal runaway (TR) in the LIB module by employing a multiphysics model that incorporates thermal, electrochemical, and degradation sub-models. The focus of this research lies in understanding the degradation phenomenon associated with the breakdown of the solid electrolyte interface (SEI) on the negative electrode, which can trigger TR. The developed multiphysics model enables the investigation of electrochemical and degradation processes within batteries under various conditions, including constant charge/discharge and driving cycles. To capture the spatio-temporal temperature change, a graph neural network (GNN) for spatial change is coupled with a Long Short-Term Memory (LSTM) network for temporal evolution to form an integrated framework. The results demonstrate the high accuracy of the ML model in predicting battery temperatures in a module based on spatial and temporal temperature data obtained from temperature sensors attached to the batteries, hence, offering a means to detect TR before it occurs by identifying potential thermal hotspots.

Spatial analysis of gold occurrences in the Zuru Schist Belt, northwest Nigeria

ABSTRACT The Zuru Schist Belt in Northwest Nigeria is one of the auriferous schist belts occurring in the western half of Nigeria. The gold mineralization largely hosted within Neoproterozoic metasedimentary rocks is considered orogenic. In an attempt to understand the pattern of occurrence of gold mineralization, their spatial distribution and association with regional structures, spatial analysis including point pattern, fractal, Fry, and distance distribution analyses were carried out to determine and quantify spatial pattern, spatial association, and regional structural control. Point pattern analysis reveals that the gold occurrences in the Zuru Schist Belt have a clustered pattern. Fractal analysis shows that the structures that controlled the distribution of gold occurrences can be divided into two categories: those that operated at a spatial scale of below 8 km, and those that operated at around 8 km and more. Fry analysis shows that the gold occurrences in the Zuru Schist Belt are aligned in a NNE-NE direction. This is parallel with the NNE-NE striking faults, establishing these faults as the main controlling structures. Fry plot of orientations of translated pairs within an 8 km distance shows that in addition to NNE-NE striking faults, folds with ESE trending axial trace and NW striking faults also exert some control on these known gold occurrences. The influence of these structures on the gold occurrences is further established by the result of distance distribution analysis. The results of spatial analysis using point pattern, fractal, Fry, and distance distribution analyses established the NNE-NE striking faults as the major structures that controlled the distribution of gold occurrences in the belt, and NW striking faults as important structures at a local scale. In addition to NW striking faults, this study further identified folds with axial trace oriented in ESE as additional secondary control structures for gold mineralization in the Zuru Schist Belt.

Research on the Manifestation and Formation Mechanism of New Characteristics of Land Disputes: Evidence from the Yangtze River Economic Belt, China

Land disputes have significantly disrupted legal order, production, and social harmony, and has been regarded as a quintessential challenge in public governance, attracting worldwide attentions from scholars. As an emblematic feature of China’s latest reform and opening-up strategy, the Yangtze River Economic Belt (YREB) in China has experienced rapid development after entering the new era (2012–2021) alongside substantial risks and challenges, particularly regarding land disputes. Better understanding of the manifestation and formation mechanism of new characteristics of land disputes is beneficial for contemporary public governance and for achieving a high-quality development of the YREB, whose Gross Domestic Product (GDP) accounted for 46.3% of the national GDP in 2023. A total of 325,105 land dispute cases in 11 provinces or municipalities of the YREB from 2012 to 2021 were collected and analyzed. On this basis, an evaluation index system of the new characteristics of land disputes, named the overall land dispute (OLD) index, was constructed according to measurement theory by coupling the interactions of quantity, claim amounts, duration periods, and the appeal rate of land dispute. Then, the OLD index was evaluated by descriptive statistical methods, a geographic information system (GIS) spatial analysis, a center of gravity model, kernel density estimation, and Theil index methods, to reveal the new characteristics and formation mechanisms of land disputes in the YREB from 2012 to 2021. The results indicated that: (1) The OLD index exhibited a trend of an initial increase followed by a decline, indicating that land disputes in the YREB showed signs of alleviation. (2) The government’s capacity for resolving land disputes was significantly improved, as evidenced by the decline in the OLD index from 0.59 in 2018 to 0.51 in 2021. This improvement could be attributed to the effectiveness of enhanced governmental working mechanisms, regulatory standards, and the integration of digital technologies. (3) The analysis of the center of gravity model indicated that the focus of land disputes shifted westward, propelled by national policy support for upstream regions of the YREB and the need for land ecological protection. (4) The analysis of kernel density estimation indicated that regional disparities in land disputes within the YREB had declined, driven by a positive trend toward balanced regional development and rural governance. This study provides scientific insights into the new characteristics of land disputes in the YREB and guidance for policy decision making on effective land dispute management.

Research on the Manifestation and Formation Mechanism of New Characteristics of Land Disputes: Evidence from the Yangtze River Economic Belt, China

Land disputes have significantly disrupted legal order, production, and social harmony, and has been regarded as a quintessential challenge in public governance, attracting worldwide attentions from scholars. As an emblematic feature of China’s latest reform and opening-up strategy, the Yangtze River Economic Belt (YREB) in China has experienced rapid development after entering the new era (2012–2021) alongside substantial risks and challenges, particularly regarding land disputes. Better understanding of the manifestation and formation mechanism of new characteristics of land disputes is beneficial for contemporary public governance and for achieving a high-quality development of the YREB, whose Gross Domestic Product (GDP) accounted for 46.3% of the national GDP in 2023. A total of 325,105 land dispute cases in 11 provinces or municipalities of the YREB from 2012 to 2021 were collected and analyzed. On this basis, an evaluation index system of the new characteristics of land disputes, named the overall land dispute (OLD) index, was constructed according to measurement theory by coupling the interactions of quantity, claim amounts, duration periods, and the appeal rate of land dispute. Then, the OLD index was evaluated by descriptive statistical methods, a geographic information system (GIS) spatial analysis, a center of gravity model, kernel density estimation, and Theil index methods, to reveal the new characteristics and formation mechanisms of land disputes in the YREB from 2012 to 2021. The results indicated that: (1) The OLD index exhibited a trend of an initial increase followed by a decline, indicating that land disputes in the YREB showed signs of alleviation. (2) The government’s capacity for resolving land disputes was significantly improved, as evidenced by the decline in the OLD index from 0.59 in 2018 to 0.51 in 2021. This improvement could be attributed to the effectiveness of enhanced governmental working mechanisms, regulatory standards, and the integration of digital technologies. (3) The analysis of the center of gravity model indicated that the focus of land disputes shifted westward, propelled by national policy support for upstream regions of the YREB and the need for land ecological protection. (4) The analysis of kernel density estimation indicated that regional disparities in land disputes within the YREB had declined, driven by a positive trend toward balanced regional development and rural governance. This study provides scientific insights into the new characteristics of land disputes in the YREB and guidance for policy decision making on effective land dispute management.

Cross-sectional and spatial panel data analysis of territorial economic cohesion in the European Union regions based on convergence approach: From 2 to 8 per cent?

From an economic, political and social standpoint, one of the most evident and visible features of today's European Union as a supranational regional organization is its heterogeneity, where disparity seems to be the common denominator. This leads to the interest for measuring the territorial economic cohesion of the EU. From an eminently economic perspective, and working with the GDP per capita of the EU NUTS-2 regions for the period 2003–2021, this paper aims to provide evidence of a lack of territorial economic cohesion through a beta and sigma convergence methodology by applying cross-sectional and spatial panel data analysis.The findings show that the speed of convergence depends mainly on the level of economic development, its cycles and the heterogeneity of the, which implies conditional convergence. Less developed regions show higher convergence speeds, which are also accentuated during recession periods. Greater heterogeneity among the regions also increases the convergence speed, while accentuating in the less developed regions. In general terms, the results reveal convergence speeds of the entire NUTS-2 regions between 7 and 11 per cent (much higher than 2 per cent under absolute convergence). Likewise, when considering spatial dependence, a reduction in convergence speeds between approximately 3 and 8 per cent is detected. Finally, the 29 vulnerable regions have been identified, with economic development and growth below the EU average mean, emphasizing the need to take the concerns of territorial economic cohesion into account.

Clustering olive oil mills through a spatial and economic GIS-based approach

Sicily ranks as the third-largest region in Italy for olive growing and olive oil production, holding the second position nationally regarding the number of active olive oil mills. This pioneering study integrates spatial and economic analyses to examine the geographical distribution of olive oil mills in Sicily and their relationship with the localization of olive groves. Using Local Indicators of Spatial Association (LISA), we conducted an advanced analysis of spatial patterns of olive oil mills, considering travel time on the road network. The adopted methodology addresses issues related to overestimation based on straight-line assumptions and the neglect of travel speed. Unlike traditional Euclidean distance approaches, our methodology provides a detailed understanding of the spatial relationships between olive oil mills and olive groves, revealing distinct patterns linked to elevation and proximity to olive groves. By linking profitability indicators with spatial clusters, we identify different thresholds of economic sustainability. Consequently, these findings contribute to a more comprehensive understanding of the olive oil industry, suggesting more environmentally sustainable practices. Policymakers, researchers, and industry stakeholders can leverage this knowledge to make informed decisions that foster the long-term sustainability of the olive oil sector.

Parallel EEG assessment of different sound predictability levels in tinnitus

Tinnitus denotes the perception of a non-environmental sound and might result from aberrant auditory prediction. Successful prediction of formal (e.g., type) and temporal sound characteristics facilitates the filtering of irrelevant information, also labelled as ‘sensory gating’ (SG). Here, we explored if and how parallel manipulations of formal prediction violations and temporal predictability affect SG in persons with and without tinnitus. Age-, education- and sex-matched persons with and without tinnitus (N = 52) participated and listened to paired-tone oddball sequences, varying in formal (standard vs. deviant pitch) and temporal predictability (isochronous vs. random timing). EEG was recorded from 128 channels and data were analyzed by means of temporal spatial principal component analysis (tsPCA). SG was assessed by amplitude suppression for the 2nd tone in a pair and was observed in P50-like activity in both timing conditions and groups. Correspondingly, deviants elicited overall larger amplitudes than standards. However, only persons without tinnitus displayed a larger N100-like deviance response in the isochronous compared to the random timing condition. This result might imply that persons with tinnitus do not benefit similarly as persons without tinnitus from temporal predictability in deviance processing. Thus, persons with tinnitus might display less temporal sensitivity in auditory processing than persons without tinnitus.

Quantifying heterogeneous impacts of 2D/3D built environment on carbon emissions across urban functional zones: A case study in Beijing, China

Rapid urbanization has led to a significant increase in carbon emissions (CES), adversely affecting the urban ecological environment. As fundamental units in urban planning and management, urban functional zones (UFZs) exhibit similar energy consumption patterns. Previous studies on urban CES have often focused on large-scale regions, lacking research on CES differentials at the scale of UFZs. This study, using Beijing as a case study, employed multi-source geospatial data to estimate CES and analyze influencing factors at the UFZ scale. First, a multi-scale semantic segmentation network was constructed to produce UFZ map using high-resolution remote sensing images and OpenStreetMap road data. Second, a top-down approach was employed, incorporating nighttime light data to calculate the UFZ-scale CES to analyze differences in CES among various UFZs. Finally, factors influencing urban CES, including socioeconomic factors and two-dimensional (2D) and three-dimensional (3D) urban built environment, were analyzed using Pearson analysis and GeoDetector analysis. Results indicate that: 1) Among the 2813 UFZs in Beijing, the majority belong to residential zones (34.23 %), followed by institutional zones (20.33 %); 2) The total CES in study area amount to 4.07 × 107 tons. Commercial zones contribute significantly higher CES than other UFZs, followed by residential zones. 3) For different types of UFZs, the impact of various factors on CES differs significantly. Population density, the highest building height, base area, and average building volume are the main correlation factors. Spatial analysis of CES at the UFZ scale contributes to the management of low-carbon cities, energy allocation, and optimization of urban planning implementation.

Epidemiological survey and risk factors associated with Sarcoptes scabiei in wild lagomorphs in Spanish Mediterranean ecosystems

Although mortality caused by Sarcoptes scabiei has been reported in European wild rabbit (Oryctolagus cuniculus) and Iberian hare (Lepus granatensis), there is a lack of detailed information regarding the exposure of wild lagomorph species to this parasite. Here, we aimed to determine the seroprevalence and potential risk factors associated with S. scabiei exposure in European wild rabbits and Iberian hares in Mediterranean ecosystems of southern Spain. Between 2018/2019 and 2021/2022 hunting seasons, serum samples from 464 wild rabbits and 132 Iberian hares were collected from 100 hunting grounds in Andalusia (southern Spain). Sera were tested using an in-house indirect ELISA to detect specific anti-S. scabiei antibodies based on the immunodominant protein Ssλ20ΔB3. The overall apparent individual seroprevalence was 15.9% (95/596; 95%CI: 13.0–18.9). Antibodies against S. scabiei were detected in 11.6% (54/464; 95%CI: 8.7–14.5) of the European wild rabbits and 31.1% (41/132; 95%CI: 23.2–39.0) of the Iberian hares. Species (Iberian hare), age (adults) and geographical area (western Andalusia) were identified as risk factors potentially associated with S. scabiei exposure using generalized estimating equation analysis. By applying spatial analysis, two significant cluster of high seropositivity were detected in western and central Andalusia, respectively. The seroprevalence values obtained provide evidence of endemic, widespread and heterogeneous exposure to S. scabiei among wild lagomorph populations in Spanish Mediterranean ecosystems. Our findings underscore the importance of implementing integrated surveillance programs for sarcoptic mange in wild lagomorphs as well as in other sympatric species.

Evaluation of Rice–Crayfish Field Fragmentation Based on Landscape Indices: A Case Study of Qianjiang City, China

Since the 21st century, rice–crayfish fields have been widely distributed in the Yangtze River Basin in China. However, the spontaneous construction of these fields by farmers has given rise to the issue of rice–crayfish field fragmentation (RCFF) in certain areas. This study introduced a novel method for evaluating RCFF using township-level administrative regions as the evaluation units. Three key evaluation elements, including five landscape indices, were employed: area and edge metrics (rice–crayfish area ratio), shape metrics (perimeter–area ratio distribution), and aggregation metrics (rice–crayfish patch density, percentage of like adjacencies, and rice–crayfish contagion index). The RCFF was quantified and its spatial distribution pattern was analyzed through the entropy method and GIS spatial analysis. Empirical studies conducted in Qianjiang city yielded insightful results: (1) The contribution of evaluation elements to the RCFF was ranked in descending order as follows: aggregation metrics > shape metrics > area and edge metrics. (2) The RCFF of Yunlianghu farm was the lowest at 0.06, while the RCFF of Yangshi subdistrict 2 was the highest at 0.94. The spatial distribution of the RCFF exhibited a distinct trend, showing a gradual decrease from the northeast to the southwest in Qianjiang, and a low-RCFF area in the southwest. This evaluation system enables local government decisionmakers to comprehend the current status of rice–crayfish field management and construction. It facilitates the scientific planning of rice–crayfish field layouts and provides guidance for farmers in their expansion strategies. This method can be promoted in counties (cities) where rice–crayfish fields are primarily distributed in the Yangtze River Basin, promoting the transition of traditional agriculture to environmentally friendly agriculture in China.

Evaluation of Rice–Crayfish Field Fragmentation Based on Landscape Indices: A Case Study of Qianjiang City, China

Since the 21st century, rice–crayfish fields have been widely distributed in the Yangtze River Basin in China. However, the spontaneous construction of these fields by farmers has given rise to the issue of rice–crayfish field fragmentation (RCFF) in certain areas. This study introduced a novel method for evaluating RCFF using township-level administrative regions as the evaluation units. Three key evaluation elements, including five landscape indices, were employed: area and edge metrics (rice–crayfish area ratio), shape metrics (perimeter–area ratio distribution), and aggregation metrics (rice–crayfish patch density, percentage of like adjacencies, and rice–crayfish contagion index). The RCFF was quantified and its spatial distribution pattern was analyzed through the entropy method and GIS spatial analysis. Empirical studies conducted in Qianjiang city yielded insightful results: (1) The contribution of evaluation elements to the RCFF was ranked in descending order as follows: aggregation metrics > shape metrics > area and edge metrics. (2) The RCFF of Yunlianghu farm was the lowest at 0.06, while the RCFF of Yangshi subdistrict 2 was the highest at 0.94. The spatial distribution of the RCFF exhibited a distinct trend, showing a gradual decrease from the northeast to the southwest in Qianjiang, and a low-RCFF area in the southwest. This evaluation system enables local government decisionmakers to comprehend the current status of rice–crayfish field management and construction. It facilitates the scientific planning of rice–crayfish field layouts and provides guidance for farmers in their expansion strategies. This method can be promoted in counties (cities) where rice–crayfish fields are primarily distributed in the Yangtze River Basin, promoting the transition of traditional agriculture to environmentally friendly agriculture in China.

Evolutionary Characteristics of Urban Public Space Accessibility for Vulnerable Groups from a Perspective of Temporal–Spatial Change: Evidence from Nanjing Old City, China

Social equity/inequity and equal/unequal rights to the city extend beyond the distribution of urban parks and green spaces, necessitating research on equitable accessibility to encompass a broader range of public spaces. However, previous research has predominantly focused on green spaces, neglecting other types of public spaces. To address this gap, the present study takes the public space pattern of Nanjing Old City as the research object, employing the minimum distance method, the gravity potential method, and bivariate local Moran’s I to evaluate the matching relationship between the demand of socially vulnerable groups and the supply of public spaces, as well as its temporal–spatial evolution from 2010 to 2020. The results reveal spatial heterogeneity in the accessibility of public spaces for vulnerable groups at the block level, with 28.1% of the total number of blocks and 22.1% of the total area of blocks experiencing a supply–demand imbalance in 2010. From 2010 to 2020, under the rapid urban development, construction of public spaces, and the general decline in population density and proportion of vulnerable populations, the supply–demand imbalance has exacerbated the distribution of public spaces at both individual and aggregate levels. This imbalance is reflected in the deteriorated accessibility of public spaces for vulnerable groups. This study reveals the mismatches between development, population movement, and public space construction in the old city of Nanjing over the past decade, providing decision-making suggestions and foundations for the future optimization of public spaces, thereby offering an effective tool for assessing and improving the accessibility and equitable distribution of public spaces based on the needs of vulnerable groups.

Evolutionary Characteristics of Urban Public Space Accessibility for Vulnerable Groups from a Perspective of Temporal–Spatial Change: Evidence from Nanjing Old City, China

Social equity/inequity and equal/unequal rights to the city extend beyond the distribution of urban parks and green spaces, necessitating research on equitable accessibility to encompass a broader range of public spaces. However, previous research has predominantly focused on green spaces, neglecting other types of public spaces. To address this gap, the present study takes the public space pattern of Nanjing Old City as the research object, employing the minimum distance method, the gravity potential method, and bivariate local Moran’s I to evaluate the matching relationship between the demand of socially vulnerable groups and the supply of public spaces, as well as its temporal–spatial evolution from 2010 to 2020. The results reveal spatial heterogeneity in the accessibility of public spaces for vulnerable groups at the block level, with 28.1% of the total number of blocks and 22.1% of the total area of blocks experiencing a supply–demand imbalance in 2010. From 2010 to 2020, under the rapid urban development, construction of public spaces, and the general decline in population density and proportion of vulnerable populations, the supply–demand imbalance has exacerbated the distribution of public spaces at both individual and aggregate levels. This imbalance is reflected in the deteriorated accessibility of public spaces for vulnerable groups. This study reveals the mismatches between development, population movement, and public space construction in the old city of Nanjing over the past decade, providing decision-making suggestions and foundations for the future optimization of public spaces, thereby offering an effective tool for assessing and improving the accessibility and equitable distribution of public spaces based on the needs of vulnerable groups.

Spatial analysis and extent of soil erosion risk using the RUSLE approach in the Swat River Basin, Eastern Hindukush

Spatial analysis and extent of soil erosion risk using the RUSLE approach in the Swat River Basin, Eastern Hindukush

Evolution and Drivers of Production Patterns of Major Crops in Jilin Province, China

Exploring the evolution of the production patterns of major crops and their driving factors can provide new ideas to ensure the security of supply of important agricultural products. This study selected four major crop types in Jilin Province—grain, oil crop, vegetable, and fruit—as research subjects. Using the center of gravity migration model, spatial autocorrelation analysis, and comparative advantage index, the spatial and temporal evolution of these crops’ production patterns from 2000 to 2020 was examined. A geographically weighted regression model was employed to analyze driving factors. The results showed that the planting area of grain was the most extensive; the percentage of production of grain, oil crop, and fruit increased to different degrees; the unit area yield of the four crops increased. The centers of gravity of all four crops’ productions were located in the central-northwestern region of Jilin Province. The global Moran’s I was positive for all four crops’ productions. The comparative advantage characteristics of the four crops were closely related to the natural geographical environment. Grain, vegetable, and fruit production were significantly and positively correlated with fertilizer application, and the most significant factor affecting oil crop production was land input intensity.

Single-cell transcriptome analysis reveals two subtypes of tumor cells of sclerosing pneumocytoma with distinct molecular features and clinical implications

Pulmonary sclerosing pneumocytoma (PSP) is a rare, distinctive benign lung adenoma of pneumocyte origin. Despite its rarity, the tumor's unique cellular morphology has sparked ongoing debates regarding the origin of its constituent cells. This study aimed to elucidate the molecular features of PSP tumor cells and enhance our understanding of the cellular processes contributing to PSP formation and biological behavior. Tissue samples from PSP and corresponding normal lung tissues (n = 4) were collected. We employed single-cell RNA sequencing and microarray-based spatial transcriptomic analyses to identify cell types and investigate their transcriptomes, with a focus on transcription factors, enriched gene expression, and single-cell trajectory evaluations. Our analysis identified two types of tumor cells: mesenchymal epithelial dual phenotype cells (MEDPs) and a distinct subpopulation of type II alveolar epithelial cells exhibiting characteristics slightly reminiscent of type I alveolar epithelial cells (AT2Cs), corresponding to histological round stromal cells and surface cuboidal cells, respectively. MEDPs displayed weak alveolar epithelial differentiation but strong collagen production capabilities, as indicated by the expression of both TTF-1 and vimentin. These cells played a pivotal role in forming the solid and sclerotic areas of PSP. Moreover, MEDPs exhibited a pronounced propensity for epithelial-mesenchymal transition, suggesting a greater potential for metastasis compared to AT2Cs. The capillary endothelial cells of PSP displayed notable diversity. Overall, this study provides, for the first time, a comprehensive mapping of the single-cell transcriptome profile of PSP. Our findings delineate two distinct subtypes of tumor cells, MEDPs and AT2Cs, each with its own biological characteristics and spatial distribution. A deeper understanding of these cell types promises insights into the histology and biological behaviors of this rare tumor.

Evolution and Drivers of Production Patterns of Major Crops in Jilin Province, China

Exploring the evolution of the production patterns of major crops and their driving factors can provide new ideas to ensure the security of supply of important agricultural products. This study selected four major crop types in Jilin Province—grain, oil crop, vegetable, and fruit—as research subjects. Using the center of gravity migration model, spatial autocorrelation analysis, and comparative advantage index, the spatial and temporal evolution of these crops’ production patterns from 2000 to 2020 was examined. A geographically weighted regression model was employed to analyze driving factors. The results showed that the planting area of grain was the most extensive; the percentage of production of grain, oil crop, and fruit increased to different degrees; the unit area yield of the four crops increased. The centers of gravity of all four crops’ productions were located in the central-northwestern region of Jilin Province. The global Moran’s I was positive for all four crops’ productions. The comparative advantage characteristics of the four crops were closely related to the natural geographical environment. Grain, vegetable, and fruit production were significantly and positively correlated with fertilizer application, and the most significant factor affecting oil crop production was land input intensity.