Lanzhou City Research Articles

Epidemiological analysis of 2106 geriatric trauma patients in a level I trauma center in Lanzhou City, Gansu Province, China.

As the global population ages, geriatric trauma gains attention. Limited studies on geriatric trauma in developing countries necessitate comprehensive investigation. This study aims to delineate the epidemiological characteristics of geriatric trauma, providing insights for prevention and enhanced elderly trauma care. Clinical data of 2106 geriatric trauma patients (age ≥ 60) treated from November 1, 2020, to October 31, 2023, at the trauma center of the First Hospital of Lanzhou University were retrospectively analyzed. Descriptive statistics covered temporal and monthly distribution, trauma sites, causes, and length of stay. Inclusive were 2106 geriatric patients (941 males, 1165 females; male-to-female ratio 1:1.24). Trauma incidence was higher in summer and autumn (May-October) than winter (November-December). Peak incidents occurred between 14:00-16:00, with concentrations at 12:00-16:00 and 20:00-22:00. Falls (59.35%), road traffic accidents (16.62%), other traumas (14.10%), cutting/stabbing (4.56%), violence (3.42%), mechanical injuries (1.61%), winter sports injuries (0.14%), burns (0.14%), and animal bites (0.06%) were major causes. Extremity and skin injuries prevailed, with significant site distribution differences (P < .001). Average length of stay at the trauma center was 78.35 ± 48.32 minutes. The gender distribution, timing, causes, and sites of trauma in the elderly differ significantly from other age groups. Unlike the higher occurrence of trauma in young men compared to women, among the elderly, it is more prevalent in women than men, mainly attributed to falls. It is crucial to implement specific measures to prevent trauma in the elderly, and the advancement of information technology in the trauma care system could additionally improve the quality of care.

How to Achieve the Ecological Sustainability Goal of Ecologically Fragile Areas on the Qinghai-Tibet Plateau: A Multi-Scenario Simulation of Lanzhou-Xining Urban Agglomerations

The future of the ecologically fragile areas on the Qinghai-Tibet Plateau (QTP) is a matter of concern. With the implementation of the Western Development Strategy, the Lanzhou-Xining Urban Agglomeration (LXUA) has encountered conflicts and compromises between urban expansion, ecological protection, and farmland protection policies in the rapid development of the past 2 decades. These deeply affect the land use layout, making the ecological sustainable development of the ecologically fragile areas of the QTP a complex and urgent issue. Exploring the impact of different policy-led land use patterns on regional ecosystem services is of great significance for the sustainable development of ecologically fragile areas and the formulation of relevant policies. Following the logical main line of “history-present-future”, the Patch-level Land Use Simulation (PLUS) model, which explores potential factors of historical land use, and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model were used to construct three future scenarios for the modernization stage in 2031 dominated by different land use policies in this study. These scenarios include the Business-as-Usual Scenario (BS), the Cropland Protection Scenario (CP), and the Ecological Protection Scenario (EP). The study analyzed and predicted land use changes in the LXUA from 2001 to 2031 and assessed carbon storage, habitat quality at different time points, and water yield in 2021. The results indicated that land use changes from 2001 to 2021 reflect the impacts and conflicts among the Western Development Strategy, ecological protection policies, and cropland preservation policies. In 2031, construction land continues to increase under all three scenarios, expanding northwards around Lanzhou, consistent with the actual “northward expansion” trend of Lanzhou City. Changes in other land uses are in line with the directions guided by land use policy. By 2031, carbon storage and habitat quality decline under all scenarios, with the highest values observed in the EP scenario, the lowest carbon storage in the BS scenario, and the lowest habitat quality in the CP scenario. Regarding water yield, the LXUA primarily relies on alpine snowmelt, with construction land overlapping high evapotranspiration areas. Based on the assessment of ecosystem services, urban expansion, delineation of ecological red lines, and improvement of cropland quality in the LXUA were proposed. These findings and recommendations can provide a scientific basis for policy makers and planning managers in the future.

Refined Identification of Urban Functional Zones Integrating Multisource Data Features: A Case Study of Lanzhou, China

Identifying urban functional zones is one of the important foundational activities for urban renewal and the development of high-quality urban areas. Efficient and accurate identification methods for urban functional zones are significant for smart city planning and industrial layout optimization. However, existing studies have not adequately considered the impact of the interactions between human activities and geographical space provision on the delineation of urban functional zones. Therefore, from the perspective of integrating the spatiotemporal characteristics of human activities with the distribution of urban functional facilities, by incorporating mobile signaling, POI (point of interest), and building outline data, we propose a multifactorial weighted kernel density model that integrates ‘human activity–land feature area–public awareness’ to delineate urban functional zones quantitatively. The results show that the urban functional zones in the central city area of Lanzhou are primarily characterized by dominant single functional zones nested within mixed functional zones, forming a spatial pattern of ‘single–mixed’ synergistic development. Mixed function zones are widely distributed in the center of Lanzhou City. However, the area accounted for a relatively small proportion, the overall degree of functional mixing is not high, and the inter-district differences are obvious. The confusion matrix showed 85% accuracy and a Kappa coefficient of 0.83.

Study on bearing characteristics of single pile in heterogeneous layered foundation

Based on a project in Lanzhou City, Gansu Province, China, the bearing and internal force characteristics of 2 piles of different lengths under vertical load were tested and analyzed by using BOFDA technology and anchor pile method static load test. The results show that long pile has higher vertical bearing capacity and greater elastic working range, but the axial force of long pile and short pile has the same trend. The lateral friction resistance of the soil layer around the pile plays a role earlier than the pile tip resistance, and the lateral friction resistance of the upper soil layer plays a role earlier than the lower soil layer. The increasing amplitude of lateral friction resistance in different soil layers is also different. The settlement of short pile top is mostly caused by the displacement of pile bottom, and the pile tip resistance is more affected by the pile tip sediments. The relationship between pile end resistance and displacement under the influence of sediments can be analyzed by three-fold line model.

Construction of landslide warning by combining rainfall threshold and landslide susceptibility in the gully region of the Loess Plateau: A case of Lanzhou City, China

Regional forecasting of the landslide rainfall threshold is complex, and the empirical prediction of the rainfall threshold relies on historical statistical data. To obtain the intensity I ∼ duration (D) rainfall threshold, Lanzhou City was selected as the research object, and a field investigation, 3S technology, mathematical statistics and a Python language environment were employed to develop a set of automatic rainfall threshold calculation programs. Factor elimination, the information value method, weight of evidence, the frequency ratio, the density method and receiver operating characteristic (ROC) curve were applied to obtain landslide susceptibility, and the I ∼ D rainfall threshold (temporal probability) and landslide susceptibility (spatial probability) were combined to construct regional landslide rainfall threshold warning levels (red, orange, yellow, and blue). The results showed the rainfall duration of historical landslides ranged from 0.99 to 216 h, thereinto, it was accounted for 92.78 % with that of between 6 and 96 h, and the rainfall intensity was between 0.11 and 23.6 mm/h, and the α and β of the rainfall threshold curve was gradually increased with an increase in the rainfall threshold probability. Additionally, when the rainfall condition probability was the same, landslides occurrence was more frequent in Chenguan District, where there are large areas of bare land, and slope and annual rainfall are less than 10 °and 300 mm, respectively. Fifteen, nine, and six factors were used to obtain landslide susceptibility, and the accuracy of the ROC ranged from 0.78 to 0.80 under different methods and different factor combinations. The spatial distribution of landslide susceptibility was very similar. There were 35, 12, 25, and 108 landslides associated with red, orange, yellow, and blue levels, respectively, under the spatial–temporal probability, but 30, 26, 54, and 70, respectively, under temporal probability. Under the different conditions, there were 89, 69, and 22 landslide points with unchanged, increased, and decreased warning levels, respectively. The ability and accuracy of rainfall threshold warning and prediction were effectively improved by integrating the temporal and spatial probabilities of the rainfall threshold.

Hybrid Deep Learning Model for Traffic Flow and Speed Forecasting at Urban Junction

The hybrid deep learning model H-CNN-LSTM (Hybrid Convolution Neural Network and Long Short-Term Memory) is introduced in this paper. The model combines CNN to extract traffic flow and speed features, LSTM networks to model temporal dependencies, and employs a combined matrix and a rolling forward input method during data input, enhancing the coarse-grained extraction of traffic data and further refining the utilization of adjacent data. Our research focuses on the complex dynamic traffic conditions of Fuli East Road in Xigu District, Lanzhou City of China. Using detailed traffic video data collected during one month of evening rush hours, we predict future traffic using the H-CNN-LSTM model. By comparing it with other prediction methods, we validate the effectiveness of our approach in predicting traffic flow and speed in real-world traffic scenarios

The correlation between daily temperature, diurnal temperature range, and asthma hospital admissions in Lanzhou city, 2013–2020

BackgroundWith the backdrop of global climate change, the impact of climate change on respiratory diseases like asthma is receiving increasing attention. However, the effects of temperature and diurnal temperature range (DTR) on asthma are complex, and understanding these effects across different seasons, age groups, and sex is of utmost importance.MethodsThis study utilized asthma hospitalization data from Lanzhou, China, and implemented a distributed lag nonlinear model (DLNM) to investigate the relationship between temperature and DTR and asthma hospitalizations. It considered differences in the effects across various seasons and population subgroups.ResultsThe study revealed that low temperatures immediately increase the risk of asthma hospitalization (RR = 1.2010, 95% CI: 1.1464, 1.2580), and this risk persists for a period of time. Meanwhile, both high and low DTR were associated with an increased risk of asthma hospitalization. Lower temperatures (RR = 2.9798, 95% CI: 1.1154, 7.9606) were associated with higher asthma risk in the warm season, while in the cold season, the risk significantly rose for the general population (RR = 3.6867, 95% CI: 1.7494, 7.7696), females (RR = 7.2417, 95% CI: 2.7171, 19.3003), and older individuals (RR = 18.5425, 95% CI: 5.1436, 66.8458). In the warm season, low DTR conditions exhibited a significant association with asthma hospitalization risk in males (RR = 7.2547, 95% CI: 1.2612, 41.7295) and adults aged 15–64 (RR = 9.9494, 95% CI: 2.2723, 43.5643). Children also exhibited noticeable risk within specific DTR ranges. In the cold season, lower DTR increases the risk of asthma hospitalization for the general population (RR = 3.1257, 95% CI: 1.4004, 6.9767). High DTR significantly increases the risk of asthma hospitalization in adults (RR = 5.2563, 95% CI: 2.4131, 11.4498).ConclusionThis study provides crucial insights into the complex relationship between temperature, DTR, and asthma hospitalization, highlighting the variations in asthma risk across different seasons and population subgroups.

Optimization Study of Outdoor Activity Space Wind Environment in Residential Areas Based on Spatial Syntax and Computational Fluid Dynamics Simulation

In the context of increasing global energy shortages and climate change, the human living environment, as a crucial component of residents’ daily lives, has garnered growing attention from the academic community. Research on residential environments is vital for promoting the sustainable development of urban construction and constitutes an important aspect of sustainable development studies. This study focuses on the optimization strategy for the outdoor activity space wind environment in the Xihuayuan residential area in Lanzhou city, utilizing spatial syntax analysis and Computational Fluid Dynamics (CFD) simulation technology. Firstly, the outdoor activity space is analyzed for visibility and spatial accessibility using DepthmapX0.6 software. Then, the outdoor wind environment in the residential area is simulated using PHOENICS 2018 software, and the analysis is conducted on outdoor spaces with a poor wind environment in terms of high accessibility. The results indicate that residents’ outdoor comfort in these spaces is poor, highlighting the urgent need for improvement in the wind environment. This research attempts to optimize the wind environment in high-accessibility spaces within the residential area by improving building layout, orientation, and height. The simulation results after optimization demonstrate an increase in the overall average wind speed to 1.44 m/s, with the proportion of spaces with a good wind environment in high-accessibility areas during summer rising from 33.4% to 59.2%. The optimization strategy effectively improves the wind environment in high-accessibility areas of the residential area.

Wintertime ozone surges: The critical role of alkene ozonolysis

Ozone (O3) pollution is usually linked to warm weather and strong solar radiation, making it uncommon in cold winters. However, an unusual occurrence of four high O3 episode days (with maximum hourly concentrations exceeding 100 ppbv and peaking at 121 ppbv) was recorded in January 2018 in Lanzhou city, China. During these episodes, the average daytime concentration of total non-methane volatile organic compounds (TVOCs) reached 153.4 ± 19.0 ppbv, with alkenes—largely emitted from the local petrochemical industry—comprising 82.3 ± 13.1 ppbv. Here we show a photochemical box model coupled with a Master Chemical Mechanism to elucidate the mechanisms behind this unusual wintertime O3 pollution. We find that the typically low temperatures (−1.7 ± 1.3 °C) and weak solar radiation (263.6 ± 60.7 W m-2) of those winter episode days had a minimal effect on the reactivity of VOCs with OH radicals. Instead, the ozonolysis of alkenes generated Criegee intermediates, which rapidly decomposed into substantial ROx radicals (OH, HO2, and RO2) without sunlight. This radical production led to the oxidation of VOCs, with alkene ozonolysis ultimately contributing to 89.6 ± 8.7% of the O3 formation during these episodes. This mechanism did not activate at night due to the depletion of O3 by the NO titration effect. Furthermore, the findings indicate that a reduction of alkenes by 28.6% or NOx by 27.7% in the early afternoon could significantly mitigate wintertime O3 pollution. Overall, this study unravels the unique mechanism of alkene-induced winter O3 pollution and offers a reference for winter O3 reduction strategies in the petrochemical industrial regions.

Deterministic and probabilistic assessment of heavy metals in herbal teas sold in Lanzhou City, China

To evaluate the health risks of consuming herbal teas to residents in Lanzhou City, this study used ICP-MS to determine the Hg, Cd, and Pb content in 131 herbal tea samples (leaf, flower, and fruit) and conducted risk assessment by two methods. The Hg contents were all within safe limit of China, but the Cd and Pb levels in some samples were higher than the same limit. At the P95 exposure level, the ranking of heavy metals based on hazard quotient (HQ) was Pb > Cd > Hg in both methods. The deterministic assessment showed that HQs of Hg, Cd, and Pb were below 1, hazard index (HI) was also below 1, but cancer risk (CR) of Cd was above 10−4. In probability assessment, the HQs of Hg and Pb were less than 1, but the HQ of Cd had a certain probability of being greater than 1, and the CR of Cd is greater than 10−4. Therefore, we conclude that Hg and Pb in herbal teas may not pose a health risk, but Cd pose a health risk to consumers. Thus, measures should be taken to minimize the excessive accumulation of Pb and Cd in the cultivation and production process of floral tea.

Validation of the athletic mental energy scale for Chinese school-age adolescents

Mental energy is an important factor in many domains, including athletic performance. The athletic mental energy scale (AMES) is one of the established tools available to measure athletes’ perceived mental energy state. To date, there is no validated questionnaire to assess athletic mental energy for Chinese adolescents. Therefore, purpose of this study was to validate a Chinese version of AMES (C-AMES) among the Chinese adolescents in Lanzhou, Gansu Province, China. We sampled 729 adolescents aged 14 to 18 in five middle schools in Lanzhou City, Gansu Province, China to complete the revised C-AMES. Data were analyzed for factor structure validity by performing CFA. The results showed that the fit index was acceptable (RMSEA = 0.050, CFI = 0.962, TLI = 0.951), and a six-factor model containing 18 C-AMES items had good measurement properties for athletic mental energy. We suggest future study may use C-AMES to examine the relationship between athletes’ mental energy and athletic performance and sporting behavior.

Spatial and Temporal Distribution Characteristics and Cytotoxicity of Atmospheric PM2.5 in the Main Urban Area of Lanzhou City.

PM2.5, as one of the most harmful pollutant in the atmospheric environment and population health, has received much attention. We monitored PM2.5 levels at five sampling sites in the Lanzhou City and collected PM2.5 particles from two representative sites for cytotoxicity experiment. The cytotoxicity of PM2.5 samples on A549 cells and migration ability of the cells were respectively detected by Cell Counting kit-8 (CCK-8) assay and scratch assay. We detected the levels of cellular inflammatory factors and oxidative damage-related biochemical indexes. RT-qPCR was used to detect the mRNA levels of NF-κB and epithelial-mesenchymal transition (EMT)-related genes. We found that the Lanlian Hotel station had the highest PM2.5 annual average concentration. The annual average concentration change curve of PM2.5 showed a roughly "U"-shaped distribution during the whole sampling period. The cytotoxicity experiment showed the viability of A549 cells decreased and the scratch healing rate increased in the 200 and 400μg/mL PM2.5-treated groups. We also found 400μg/mL PM2.5 induced changes in the mRNA levels of NF-κB and EMT-related genes, the mRNA levels of IKK-α, NIK, and NF-κB in the 400μg/mL PM2.5 group were higher than those in the control group. The mRNA levels of E-cadherin decreased and α-SMA increased in the 400μg/mL PM2.5 groups, and the mRNA levels of Fibronectin increased in the 400μg/mL PM2.5 groups. Moreover, we found hydroxyl radical scavenging ability and T-AOC levels were lower, and LPO levels were higher in the 200 and 400μg/mL PM2.5 groups, and the SOD activity of cells in the 400µg/mL PM2.5 group decreased. And compared with the control group, the levels of TNF-α were higher in the 200 and 400μg/mL PM2.5 groups and the levels of IL-1 were higher in the 400μg/mL PM2.5 group. The results indicated that the cytotoxicity of atmospheric PM2.5 was related to oxidative damage, inflammatory response, NF-κB activity and EMT.

Metagenomics reveals the potential transmission risk of resistomes from urban park environment to human

Urban parks play a significant role in urban ecosystems and are strongly associated with human health. Nevertheless, the biological contamination of urban parks – opportunistic pathogens and antibiotic resistance genes (ARGs) – has been poorly reported. Here, metagenomic and 16 S rRNA sequencing methods were used to study the distribution and assembly of opportunistic pathogens and ARGs in soil and water from nine parks in Lanzhou city, and further compared them with local human gut microbiomes to investigate the potential transmission risk. Our results revealed that the most important type of drug resistance in urban parks was multidrug resistance, with various resistance mechanisms. Approximately half of ARGs were shared between human gut and park environment, and it was noteworthy that cross-species transmission might exist among some high-risk ARGs, such as mepA and mdtE, with a significant enrichment in human gut. Metagenomic binning uncovered several bacterial genomes carrying adjacent ARGs, MGEs, and virulence genes, indicating a possibility that these genes may jointly transfer among different environments, particularly from park environment to human. Our results provided a reference point for the management of environmental pollutants in urban parks.

Evaluation of the prevalence of adolescent scoliosis and its associated factors in Gansu Province, China: a cross-sectional study.

Gansu Province is situated in the northwest region of China, characterized by diverse and complex topography and a rich diversity of ethnic groups. This study aims to explore the prevalence and risk factors of adolescent suspected scoliosis in Gansu Province through a cross-sectional population study. From April 2022 to July 2022, a prospective cross-sectional study was conducted in Baiyin City, Jinchang City, Lanzhou City, Linxia Hui Autonomous Prefecture, and Gannan Tibetan Autonomous Prefecture in Gansu Province. The screening covered 3,118 middle and high school students across 24 institutions, including middle and high schools. Diagnosis of suspected scoliosis was established through visual inspection, the Adams forward bend test, and measurement of trunk rotation angle. Employing a custom-designed questionnaire, demographic data were collected, and the prevalence of suspected scoliosis was calculated. Univariate and multivariate logistic regression analyses were employed to assess factors associated with suspected scoliosis. A total of 3,044 participants were ultimately included in the analysis. The overall prevalence of suspected scoliosis was 5.68% in Gansu Province. The peak prevalence for boy is at 14 years (6.70%), while for girl, it is at 15 years (8.75%). Lanzhou City exhibits the highest prevalence rates (boy, 9.82%; girl, 10.16). The results of univariate logistic regression analysis presented that BMI (OR = 0.92, 95% CI: 0.88-0.96), altitude of habitation (1,600 m-2000 m) (OR = 0.50, 95% CI: 0.34-0.73), altitude of habitation (2000 m-3321 m) (OR = 0.58, 95% CI: 0.40-0.83), family medical history (OR = 1.56, 95% CI: 1.02-2.31), and shoulders of unequal height (OR = 1.49, 95% CI: 1.09-2.03) were significantly correlated with suspected scoliosis. The multivariate logistic regression analysis indicated that BMI (OR = 0.91, 95% CI: 0.86-0.95), altitude of habitation (1,600 m-2000 m) (OR = 0.35, 95% CI: 0.23-0.54), altitude of habitation (2000 m-3321 m) (OR = 0.39, 95% CI: 0.24-0.60), family medical history (OR = 1.66, 95% CI:1.08-2.49), and shoulders of unequal height (OR = 1.45, 95% CI:1.06-1.99) were independently associated with suspected scoliosis. Low BMI, residence at an altitude of 1,600 m-3321 m, family medical history, and shoulders of unequal height were independently associated with an increased prevalence of suspected scoliosis. It is recommended to promptly screen high-risk adolescents for suspected scoliosis, provide effective preventive and intervention measures.

Achieving accurate and balanced regional electric vehicle charging load forecasting with a dynamic road network: a case study of Lanzhou City

Achieving accurate and balanced regional electric vehicle charging load forecasting with a dynamic road network: a case study of Lanzhou City

Study on the sustainable utilisation of water resources in semi-arid megacities of China based on water footprint

ABSTRACT As urbanisation continues to accelerate in China, the contradiction between rapid economic development and water scarcity in semi-arid cities is becoming increasingly evident. Consequently, the study of the relationship between water resources use and economic growth is of particular importance. Lanzhou City was selected as the study area, an evaluation index system was established to comprehensively evaluate the status of water resources utilisation, meanwhile, the water footprint method and Tapio decoupling model were adopted to measure the decoupling status between water utilisation and economic development from 2002 to 2021. The result showed that the total water footprint and per capita water footprint followed an increasing and then decreasing trend. The water footprint varied significantly by industrial sector, with agriculture accounting for 72.87% of total water use. The self-sufficiency rate of water resources was above 96.5%. The economic value increased substantially from 22.25 CNY/m3 in 2002 to 183.99 CNY/m3 in 2021. The water scarcity index and the pressure index were high, with annual mean values of 0.96 and 1, respectively. Water consumption and economic growth are generally decoupled weakly and strongly, with the number of strong decoupling occurrences increasing significantly from 2011 to 2021.

Modeling landslide susceptibility using alternating decision tree and support vector

Globally, but especially in the Chinese Loess Plateau, landslides are considered to be one of the most severe and significant geological hazards. The purpose of this study is to design two ensemble machine learning methods, which are denoted as ADTree-Dagging and SVM-Dagging, for modeling landslide susceptibility in Lanzhou City (China). For this aim, the slope units extracted by the curvature watersheds method are used to construct landslide susceptibility modeling, and ten landslide conditioning factors are included in the landslide susceptibility evaluation (altitude, slope angle, slope aspect, cutting depth, surface roughness, relief amplitude, gully density, rainfall, distance to roads, and lithology). The conditioning factors selection and spatial correlation analysis were implemented by using the correlation attribute evaluation method and the frequency ratio model. The comprehensive performance of the models was tested using the receiver operating characteristic (ROC), area under the ROC curve (AUC), the root mean square error (RMSE), and several other performance metrics. For the training dataset, the results show that the SVM-Dagging model acquire the largest AUC value (0.953), lowest RMSE (0.3125), highest positive predictive value (96.0%), highest negative predictive value (91.2%), highest sensitivity (91.6%), highest specificity (95.8%), highest accuracy (93.6%), and highest Kappa (0.873). Similar results are observed in the validation dataset. Results demonstrated that the Dagging technique has improved significantly the prediction ability of SVM and ADTree models. The Dagging method can combine different models by leveraging the strengths of each model to create methods with higher flexibility than traditional machine learning methods. Therefore, in this study, the proposed new models can be applied for land-use planning and management of landslide susceptibility in the study area and in other areas containing similar geological conditions.

An Accurate Recognition Method for Landslides Based on a Semi-Supervised Generative Adversarial Network: A Case Study in Lanzhou City

With the development of computer technology, landslide recognition based on machine learning methods has been widely applied in geological disaster management and research. However, in landslide identification, the problems of an insufficient number of samples and an imbalance of samples are often ignored; that is, landslide samples are much smaller than non-landslide samples. In order to solve this problem, taking the main urban area of Lanzhou City as an example, this paper proposes to construct a semi-supervised generated countermeasure network (SSGAN) model, which aims to achieve high performance with a limited number of labeled samples for precise landslide identification, and to help prevent and reduce the harm caused by disasters. In order to express the environmental characteristics of landslide development and the optical texture features of landslide occurrence, the study constructs three sets of samples to represent landslide features, including a landslide influencing factor sample set, a Sentinel-2A optical remote sensing sample set, a joint influencing factor and Sentinel-2A sample set. The three kinds of sample sets are transferred to SSGAN for training to form a comparative study. The results show that the joint sample set has excellent feature results in discriminator and generator. Through the experimental comparison, the model proposed in this paper is compared with the model without semi-supervised generated confrontation training. The experimental results show that the proposed method is better than the unsupervised adversarial learning model in terms of accuracy, F1 score, Kappa coefficient, and MIoU. A total of 160 landslides have been identified in the study area, with a total area of 10.328 km2, with an accuracy rate of 83%. Therefore, the generated results are accurate and reliable, and show that SSGAN can better distinguish landslides from non-landslides in an image, under the condition of obtaining a large number of unmarked environmental features; enhance the effect of landslide classification in complex geographical environment; and then put forward effective suggestions for the prevention and control of landslides and geological disasters in the main urban area of Lanzhou.

Changes in human settlement environments and their drivers in valley cities located in arid and semi-arid regions: A case study of Lanzhou in Western China

Development of urban human settlement environments (HSEs) is an integral part of promoting high-quality and sustainable regional development and constructing a beautiful China. The city of Lanzhou, located at the geometric center of China, is the only provincial capital traversed by the Yellow River. Given the constraints posed by the valley topography and the need for economic development, the development of this HSE, which is located within an arid region, poses considerable challenges. Evidently, an understanding of the evolution of HSEs and drivers of changes in them contributes to high-quality, sustainable urban development in arid and semi-arid regions. An analytical model was developed using the parameters of relief degree of land surface, human comfort days, the land cover index, nighttime light index, and precipitation. This model was used in combination with population density and the gross domestic product to analyze the spatial distribution of Lanzhou's HSE and its drivers. The results showed that landscapes in Lanzhou underwent significant changes between 2000 and 2022, with an increase in building-up land (+0.946%), cultivated land (+0.134%), and forest land (+0.018%) and a decrease in grassland (−1.10%). There was significant outward expansion of the main urban zone of Lanzhou and of various county towns, with the increase in building-up land being most prominent. During this period, there were significant changes in the periphery of the core urban area and county towns in Lanzhou, with decreases moving from the urban center (the highest value) to the surrounding areas (Yongdeng County had the lowest value). The correlation between the HSE and population density grew stronger in Anning and Chengguan Districts but became weaker in Xigu and Qilihe Districts. Spatiotemporal variations in the HSE were primarily caused by climate change, followed by human activities, and were also influenced by the valley topography. Overall, the spatial distribution of population density and the HSE in Lanzhou demonstrated good consistency under the influence of economic development and urbanization.

Spatial-Temporal Evolution Characteristics Analysis of Color Steel Buildings in Lanzhou City

With the continuous acceleration of China’s urbanization process, color steel plate, as a new type of building material, has been widely used in all kinds of temporary buildings and has become the spatial carrier of the specific development stage of urbanization. This study focuses on Lanzhou City as a case study to deeply analyze the spatiotemporal distribution and evolution of color steel plate buildings. Utilizing data extracted from Google imagery and GF-2 satellite images of the built-up areas in Lanzhou, spatial statistical and analytical methods such as centroid analysis, compactness index, and patch density are applied. Systematic analysis is conducted across different time periods and spatial scales to examine the evolution of indicators, including quantity, centroid distribution, spatial clustering, and distribution direction. The results show that from 2013 to 2021, the prevalence of color steel buildings in Lanzhou city initially increased and then decreased, and the number peaked in 2017, but there is a significant difference between distinct areas in the urban area. By quantitatively analyzing the spatial and temporal evolution characteristics of color steel plate buildings, this study reveals the important role it plays in promoting the urbanization process and provides a scientific basis for relevant planning decisions.