Spatial Principal Component Analysis Research Articles

Abstract C107: Use of spatial transcriptomics to identify molecular features associated with African American heritage in pancreatic cancer

Abstract Pancreatic cancer is the third leading cause of cancer-related deaths in the US, with a 5-year survival rate of 12%. Black or African American patients (BAA) have a 20% higher incidence of pancreatic cancer, and recent studies suggest that there are biological factors that may influence this disparity, in addition to complex socioeconomic factors. Pancreatic tumors are highly enriched with stroma and exhibit significant inter- and intra-patient morphological and molecular heterogeneity. To improve the care for all patients, we need to better understand the disease mechanisms by comprehensively mapping different spatial locations within individual patients’ tumors and determining whether there are common patterns of pathogenesis across diverse patient populations. In this study, we utilized the 10X Visium spatial transcriptomics platform on eight treatment-naïve primary pancreatic tumors. We tested multiple published bioinformatic packages, including SpatialDE, SPARK-X, Spatial PCA, and Cottrazm, and optimized a multi-sample integrated analysis pipeline that allows us to automatically segment tumor lesions, infer major cell types in regions of interest on tissues, detect spatially variant genes, and assess associations between tissue morphological phenotypes and transcriptomic features. Importantly, our study cohort includes four White patients and four BAA patients. Through the comparison of spatial transcriptomes between White and BAA patients, we identified several genes displaying differential expression in tumor lesions of distinct racial groups, including Trefoil Factor 1 (TFF1) and CYP3A5. These genes present potential candidates for further investigation to elucidate the biological mechanisms underlying racial disparities in pancreatic cancer. Citation Format: Yuesong Wu, Aoqi Xie, Ian Loveless, Madison George, Kendyll Gartrelle, Julie Clark, Daniel Salas-Escabillas, Rupen Shah, David Kwon, Ralph Francescone, Débora B. Vendramini Costa, Howard Crawford, Brian Theisen, Yuehua Cui, Ling Huang, Nina G. Steele. Use of spatial transcriptomics to identify molecular features associated with African American heritage in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C107.

Construction of a cold island network for the urban heat island effect mitigation

The urban heat island (UHI) effect seriously challenges sustainable urban development strategies and livability. Numerous studies have explored the UHI problem from the perspective of isolated blue and green patches, ignoring the overall function of cold island networks. This study aims to explore the construction method of cold island network by integrating scattered cold island resources, rationally guiding urban planning and construction, and providing effective ideas and methods for improving the urban thermal environment. Taking the central city of Fuzhou as an example, the identification of the cold island core source (CICS) was optimized by applying relative land surface temperature (LST), morphological spatial pattern analysis, and landscape connectivity analysis. The combined resistance surface was constructed based on a spatial principal component analysis. Subsequently, the cold island network was constructed by applying circuit theory and identifying the key nodes. The results showed that the central and eastern parts of the study area experienced the most significant UHI effects and there was a tendency for them to cluster. Overall, 48 core sources, 104 corridors, 89 cooling nodes, and 34 heating nodes were identified. The average LST of the CICSs was 28.43 °C, significantly lower than the average LST of the entire study area (31.50 °C), and the 104 cold corridors were classified into three categories according to their importance. Different targeting measures should be adopted for the cooling and heating nodes to maintain the stability of the cold island network and prevent the formation of a heat network. Finally, we suggest a model for urban cold island network construction and explore methods for mitigating issues with UHI to achieve proactive and organized adaptation and mitigation of thermal environmental risks in urban areas, as well as to encourage sustainable urban development.

Construction of Ecological Security Pattern of Urban Agglomeration Based on Multi-Scale Ecological Corridor Networks

The construction of an ecological security pattern (ESP) is an effective approach to addressing ecological concerns in urban agglomerations. However, previous research has often overlooked the ecological characteristics at different spatial scales, making it difficult to effectively tackle environmental issues. This study focuses on the Changsha–Zhuzhou–Xiangtan urban agglomeration (CZXUA) to construct an ESP from 2 scales: the urban agglomeration and the metropolitan area. First, ecological sources at different scales were identified and optimized using morphological spatial pattern analysis, ecosystem service supply assessment, landscape connectivity evaluation, and ecological demand intensity analysis. Next, spatial principal component analysis was employed to analyze resistance factors across different spatial scales, enabling the construction of a multi-scale landscape resistance surface. Finally, multi-scale ecological corridors were extracted using circuit theory, and the ecological corridors passing through the central urban area were optimized. As a result, 176 ecological sources, 337 ecological corridors, 60 ecological pinch points, and 30 ecological barrier points were identified, forming the overall ESP for the CZXUA. Furthermore, an ecological protection and optimization pattern, described as “One River, Seven Waters, One Heart, and Eight Wedges”, was proposed based on the ESP. This pattern highlights pivotal areas for ecological protection and restoration within the national land space. This study provides a comprehensive example of constructing a multi-scale ecological corridor network and identifying critical areas for ecological protection and restoration. The findings can serve as a reference for special ecological protection planning in urban agglomerations.

Decomposing the late positive potential to cannabis cues in regular cannabis users: A temporal-spatial principal component analysis.

Cannabis use disorder (CUD) is increasing in the United States, yet, specific neural mechanisms of CUD are not well understood. Disordered substance use is characterized by heightened drug cue incentive salience, which can be measured using the late positive potential (LPP), an event-related potential (ERP) evoked by motivationally significant stimuli. The drug cue LPP is typically quantified by averaging the slow wave's scalp-recorded amplitude across its entire time course, which may obscure distinct underlying factors with differential predictive validity; however, no study to date has examined this possibility. In a sample of 105 cannabis users, temporo-spatial Principal Component Analysis was used to decompose cannabis cue modulation of the LPP into its underlying factors. Acute stress was also inducted to allow for identification of specific cannabis LPP factors sensitive to stress. Factor associations with CUD severity were also explored. Eight factors showed significantly increased amplitudes to cannabis images relative to neutral images. These factors spanned early (~372 ms), middle (~824 ms), and late (>1000 ms) windows across frontal, central, and parietal-occipital sites. CUD phenotype individual differences were primarily associated with frontal, middle/late latency factor amplitudes. Acute stress effects were limited to one early central and one late frontal factor. Taken together, results suggest that the cannabis LPP can be decomposed into distinct, temporal-spatial factors with differential responsivity to acute stress and CUD phenotype variability. Future individual difference studies examining drug cue modulation of the LPP should consider (1) frontalcentral poolings in addition to conventional central-parietal sites, and (2) later LPP time windows.

Multi-dimensional landscape ecological risk assessment and its drivers in coastal areas

The eastern coastal areas of Japan are threatened by multiple ecological risks due to frequent natural disasters, climate changes, human activities, etc. Identification spatio-temporal variations and driving mechanisms of landscape ecological risk could be used as significant basis for policymakers. In this study, taking the eastern coastal areas of Japan affected by the 2011 Great East Japan Earthquake and Tsunami Disaster as the study area, the “Nature-Landscape Pattern-Human Society” (NA-LP-HS) multi-dimensional ecological risk assessment framework was established to analyze the spatio-temporal patterns, and identity driving factors using spatial cluster analysis and spatial principal component analysis (SPCA) based on ArcGIS from 2009 to 2021. The findings revealed the distinct geographic patterns in landscape ecological risk, with a noticeable decline from the southwest to the northeast. During the period from 2009 to 2015, the driving factors leading to a sharp risk increase were natural disasters and vegetation coverage. These high-risk areas were concentrated in Sendai Bay and its surroundings. From 2015 to 2021, ecological instability was primarily attributed to a reduction in vegetation coverage, the occurrence of natural disasters, and heightened rainfall erosion. These high-risk areas were mainly clustered within the Tokyo-centered urban agglomeration. Spatial clustering of ecological risks was obvious across all time periods. The key factors contributing to the clustering of high ecological landscape risks focused on the “landscape pattern” criterion, specifically including vegetation coverage, land use land cover. This study demonstrated the ability of multi-dimensional ecological risk assessment to identify high-risk areas and driving factors, and these results could provide a visual analysis and decision-making basis for sustainable development of coastal areas.

Impact of grassland storage balance management policies on ecological vulnerability: Evidence from ecological vulnerability assessments in the Selinco region of China

The Selinco region is a highland grassland ecosystem with a unique lake system and diverse flora and fauna. However, it is highly vulnerable to degradation due to its high altitude and harsh climate. In recent years, the region has been subjected to increasing external pressures, including climate change, human activities, and natural disasters. Therefore, conducting an ecological vulnerability assessment is essential to ensure the sustainable development of the region. To achieve this, we performed a comprehensive integrated spatial principal component analysis (SPCA) of 12 representative ecological vulnerability indicators to assess the ecosystem of the region. This approach facilitated a comprehensive assessment of the ecological status of the region. Our study indicated that population and livestock density are the most important factors influencing environmental vulnerability. While the region has shown a trend of ecological recovery and stability over the past 20 years, some areas still experience ecological deterioration, emphasizing the importance of increasing efforts for to ecological conservation and restoration. Furthermore, we observed that different ecologically fragile areas have experienced varying degrees of transformation, underscoring the importance of more precise ecological conservation policies. At the county level, Nima and Shuanghu counties require focused attention and remedial measures to address severe ecological degradation, while other counties have demonstrated a trend towards ecological restoration, which could be attributed to the implementation of a balanced grass storage management policy that mitigates the impact of human activities. Therefore, further research is essential to determine the persistence of ecological trends and to identify long-term conservation and sustainable use solutions.

Differential responses of crop yields to multi-timescale drought in mainland China: Spatiotemporal patterns and climate drivers

Increasingly frequent and severe droughts pose a growing threat to food security in China. However, our understanding of how different crops respond to multi-timescale drought under varying climatic conditions remains limited, hindering effective drought risk management. To address this knowledge gap, we applied spatial principal component analysis (SPCA) to unveil spatiotemporal patterns in annual yields of major grain crops (rice, wheat, maize) and cotton in response to multi-timescale drought, as indicated by the standardized precipitation evapotranspiration index (SPEI) across China. Subsequently, predictive discriminant analysis (PDA) was employed to identify the primary climatic factors driving these response patterns. The findings indicated that drought-induced interannual variability of crop yields were spatially and temporally heterogeneous, closely tied to the timescale used for drought assessment. Crop types displayed distinct responses to drought, evident in the variations of months and corresponding timescales for their strongest reactions. The initial three principal components, capturing over 65 % of drought-related yield variance, unveiled short- to medium-term patterns for rice, maize, and cotton, and long-term patterns for wheat. Specifically, rice was highly susceptible to drought on a 4-month timescale in September, wheat on a 6-month timescale in May, maize on a 3-month timescale in August, and cotton on a 3-month timescale in September. Moreover, the first three discriminant functions explaining over 90 % of the total variance, effectively distinguish spatiotemporal crop yield response patterns to drought. These patterns primarily stem from seasonal climatic averages, with water balance (precipitation minus potential evapotranspiration) and temperature being the most influential variables (p < 0.05). Interestingly, we observed a weak correlation between drought severity and crop yield in humid conditions, with responses tending to manifest over longer timescales. These findings enhance our comprehension of how drought timescales impact crop yields in China, providing valuable insights for the implementation of rational irrigation management strategies.

Studies on genetic diversity, gene flow and landscape genetic in Avicennia marina: Spatial PCA, Random Forest, and phylogeography approaches

Mangrove forests grow in coastal areas, lagoons, estuaries, and deltas and form the main vegetation in tidal and saline wetlands. Due to the mankind activities and also changes in climate, these forests face degradations and probably extinction in some areas. Avicennia marina is one of the most distributed mangrove species throughout the world. The populations of A. marina occur in a limited region in southern parts of Iran. Very few genetic and spatial analyses are available on these plants from our country. Therefore, the present study was planned to provide detailed information on Avicennia marina populations with regard to genetic diversity, gene flow versus genetic isolation, effects of spatial variables on connectivity and structuring the genetic content of trees populations and also identifying adaptive genetic regions in respond too spatial variables. We used SCoT molecular markers for genetic analyses and utilized different computational approaches for population genetics and landscapes analyses. The results of present study showed a low to moderate genetic diversity in the studied populations and presence of significant Fst values among them. Genetic fragmentation was also observed within each province studied. A limited gene flow was noticed among neighboring populations within a particular province. One population was almost completely isolated from the gene flow with other populations and had peculiar genetic content.Spatial PCA analysis revealed both significant global and local genetic structuring in the studied populations. Spatial variables like humidity, longitude and altitude were the most important spatial features affecting genetic structure in these populations.

Ecological vulnerability assessment of coral islands and reefs in the South China Sea based on remote sensing and reanalysis data

Coral reefs are ecosystems that are highly vulnerable to external environmental impacts, including changes associated with ocean acidification and global warming. Assessing the vulnerability of coral reef growth environments over large areas of the sea is a difficult and complex process, as it is influenced by many variables. There are few studies on environmental vulnerability assessment of coral islands and reefs in the South China Sea. It is therefore particularly important to understand the environmental sensitivity of corals and how coral communities respond to changes in climate-related environmental variables. In this study, indicators were selected mainly from natural environmental factors that hinder the development of coral reefs. The sea surface temperature (SST), sea surface salinity (SSS), wind velocity (WV) and direction, sea level height (SL), ocean currents (OC), and chlorophyll concentration (Chl) of coral reefs in South China Sea Island were integrated to calculate the coral reef environmental vulnerability region. In a GIS environment, Spatial Principal Component Analysis (SPCA) was used to develop sensitivity models and evaluate the ecological vulnerability of coral reefs. Based on the Environmental vulnerability indicator (EVI) values, the study area was classified as 5 grades of ecological vulnerability: Potential (0.000–0.577), Light (0.577–0.780), Medium (0.780–0.886), Heavy (0.886–0.993) and Very Heavy (0.993–1.131). Sensitivity models identified regional gradients of environmental stress and found that some coral reefs in western Malaysia and southwestern Philippines have higher vulnerability. Meanwhile, the study found that the reefs of Paracel Islands and Macclesfield Bank areas of medium vulnerability. Future use of high-precision data from long time series will allow better estimates of site-specific vulnerability and allow for the precise establishment of marine protected areas so that the ecological diversity of coral reefs can be sustained.

Ecological Security Assessment and Territory Spatial Restoration and Management of Inland River Basin—Based on the Perspective of Production–Living–Ecological Space

Ecological security evaluation and land space governance are effective ways to ensure regional ecological security and realize sustainable development. This study evaluated the ecological security status at the raster scale and conducted research on the restoration and governance of the national territory, with the aim of implementing accurate restoration, reducing ecological restoration costs, and increasing ecological restoration benefits. Taking the typical arid inland river Shule River Basin as an example, this study selected evaluation factors from production, living, and ecological perspectives, obtained the influencing factors of regional ecological security by spatial principal component analysis, and calculated the ecological security index on the grid scale of production, life and ecological space. The macro-scale national parks, ecological protection red line and other realistic constraints are combined with the grid-scale ecological security evaluation results to achieve accurate land space restoration and governance. The results show that the ecological space accounts for 79.23%, and the production space only accounts for 7.47%, which is similar to other inland river basins in arid areas. The study found that per capita GDP and distance to the road have a significant impact on the ecological security of the study area from the perspectives of production and life, while distance to the water, vegetation coverage, and land cover have a significant impact on ecological security from the ecological perspective. Moderate, moderate low and low ecological security zones account for 72.09% of the total area of the basin, indicating that the ecological security guarantee ability of the Shule River Basin is low. The ecological security level of the living space was the lowest, and the ecological security pattern of the basin area as a whole presented a “higher in the north and south and lower in the middle” characteristic. The land restoration and governance of the Shule River Basin area was divided into five types of ecological control, ecological conservation, ecological enhancement, ecological restoration and ecological management, of which the ecological control area accounted for as much as 35.86%, implying that ecological security in the Shule River Basin has attracted sufficient attention from the government. It is considered that the management of production and living space is more difficult, complex and important, and the proportion of space is relatively small, so it is necessary to focus on the comprehensive management project of ecological protection and restoration. However, the ecological endowment conditions of ecological space in the Shule River Basin are relatively poor, and the distribution area is vast, so natural restoration should be given priority, supplemented by artificial restoration. This study provides a reference for regional ecological security evaluation, ecological civilization construction, and national ecological security research and practice.

Promoting ecological restoration of deeply urbanized hilly areas: A multi-scale ecological networks approach

With the deep expansion of urbanization, contradictions between human beings and the natural environment in hilly areas have shown the characteristics of multi-scale and complexity. The traditional construction of ecological network rarely focused on the relationship between ecological elements at different scales, which made it difficult to systematically solve the ecological problems. To address the gap, this paper proposed a novel framework to construct multi-scale ecological networks based on the discussion of the ecological environment problems at different space scales. Firstly, one of the most deeply urbanized hilly area in China (Changsha- Zhuzhou- Xiangtan urban agglomeration, CZXUA) was chosen as the study area. By constructing the multi-scale evaluation system of ecological patches importance (EPI) after conducting the Morphological Spatial Pattern Analysis (MSPA), the identification method of ecological sources was optimized at different scales. Then, spatial principal component analysis (SPCA) was used to sort out the resistance factors at different scales, and the multi-scale resistance surfaces was constructed accordingly. Furthermore, the multi-scale ecological networks from the CZXUA to the central urban area were cooperatively constructed through the Least-cost path (LCP), circuit theory, hierarchical transmission and scale nesting. Finally, based on characteristics of the ecological networks at different scales, the study constructed the overall ecological security pattern in urban agglomeration, the ecological space development framework in metropolitan area and the green open space system in central urban area, which was well applied to the territorial space planning at different spacial scales. The results made up for the deficiency of single-scale ecological network in neglecting the important details of local areas, and provided a feasible ecological restoration plan for the decision makers and practitioners. This study can contribute to cross-scale ecosystem restoration and biodiversity conservation in hills.

Assessment of Heavy metal contaminations in agro-ecosystems around distinct pollution sources, its spatial distribution and principal component analysis

Heavy metal (HM) contamination is one of the serious concerns of the environmental deterioration and health hazards in many countries including India. Different anthropogenic activities have added an unusual higher concentration of many toxic metals in the soil and water including agricultural soil which transfer it into the food chain. We report HMs in the different agricultural soil around the riverside, dumping site, brick kilns etc. in and around the metro city Lucknow in India and analysed it for the levels of Fe, Cr, Cu, Mn, Zn, Se, Mo, Cd, As, Pb, Co and Ni. We observed the metals presence in the increasing pattern as Mo &lt; Se &lt; As &lt; Cd &lt; Co &lt; Pb &lt; Cr&lt; Cu &lt; Ni &lt; Zn &lt; Mn &lt; Fe. The concentration of trace metal Fe was higher than the permissible limits given as per the Indian Standards at all sites and 72 folds higher at Gaughat (GAF) site. Further, one of the most toxic metals Cd was 2 folds higher than the Indian standard limit for the soil at GAF site whereas it was slightly higher than the WHO prescribed limits at Sitapur (SAF) site. The levels of Cu, Pb and As in GAF site were also slightly higher than USEPA recommended limit. The results of principal component analysis indicated that PC1 was mainly affected by the municipal waste dumps, usage of contaminated water and agrochemicals whereas PC2 was mainly affected by phosphatic fertilizers.

A Multivariate Time Series Analysis of Ground Deformation Using Persistent Scatterer Interferometry

Ground deformations in urban areas can be the result of a combination of multiple factors and pose several hazards to infrastructures and human lives. In order to monitor these phenomena, Interferometric Synthetic Aperture Radar (InSAR) techniques are applied. The obtained signals record the overlapping of the phenomena, and their separation is a relevant issue. In this framework, we explored a new multi-method approach based on the combination of Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Hierarchal Clustering (HC) on the standardized results to distinguish the main trends and seasonal signals embedded in the time series of ground displacements, to understand spatial-temporal patterns, to correlate ground deformation phenomena with geological and anthropogenic factors, and to recognize the specific footprints of different ground deformation phenomena. This method allows us to classify the ground deformations at the site scale in the metropolitan area of Naples, which is affected by uplift cycles, subsidence, cavity instabilities and sinkholes. At the local scale, the results allow a kinematic classification using the extracted components and considering the effect of the radius of influence generated by each cavity, as it is performed from a theoretical point of view when the draw angle is considered. According to the results, among the classified cavities, 2% were assigned to subsidence and 11% to uplift kinematics, while the remaining were found to be stable. Furthermore, our results show that the centering of the Spatial-PCA (S-PCA) is representative of the region’s main trend, whereas Temporal-PCA (T-PCA) gives information about the displacement rates identified by each component.

Spatial PCA and Random Forest Analyses of Spatial Patterns in Genetic Diversity of Calotropis procera

Landscape genetic study can provide data on spatial effects on the genetic structure of plants. Calotropis procera is an economically and medicinally important plant species that grows in limited regions of southern parts of Iran. Identifying genetic variability and corridor of gene flow may be used in the conservation of this valuable plant. For this reason, we used a multivariate spatial PCA (sPCA) and a machine learning approach of random forest (RF), to reveal the genetic divergence of twelve populations in Calotropis procera with respect to spatial and geographical features. sPCA analyses revealed significant isolation by distance and spatial genetic structuring at both global and local levels. RF analysis identified temperature and altitude as major spatial features affecting the genetic differentiation of these populations based on the Fst value. We also noticed the genetic differentiation of populations within a single area due to local spatial effects. However, these populations did not force a separate infraspecific taxonomic entity. The genetic connectivity graph is constructed and a gene flow corridor is suggested for these populations. Similarly, resistance surface including temperature, latitude, and soil type has been proposed for these plant species.

Fine-Scale Spatial Genetic Structure of Remnant Populations of Abies religiosa, in a Temperate Forest in Central Mexico

Genetic structure of a population can be molded by the resistance of the landscape or the distance between populations that function as barriers to gene flow. We analyzed the population genetic structure of Abies religiosa on a fine spatial scale and examined isolation models by resistance and distance. We collected vegetative tissue from populations located at the altitudinal extremes of the distribution range of the species on three slopes of La Malinche National Park (LMNP) (South, North, and East) in central Mexico. Genomic DNA was obtained using the CTAB 2X method, and eight microsatellite chloroplast loci were amplified. The genetic structure was identified based on an Analysis of Molecular Variance, a Discriminant Analysis of Principal Components with cross-validation and a spatial Principal Component Analysis using the Gabriel-type connectivity network. The isolation hypotheses were evaluated by constructing partial Mantel tests using Reciprocal Causal Modeling and Maximum Likelihood Population Effects models. A genetic structure of isolation by resistance to elevation was identified, and two genetic groups were recognized: one including populations of the South slope and the other comprising populations of the North and East slopes. We detected in Abies religiosa populations of the LMNP an isolation by resistance to elevation that determines the genetic structure, and the greatest genetic exchange between groups of populations located at higher altitudes. It is suggested to promote the connectivity between slopes through assisted migration and immediately halt land-use changes, as part of the actions to preserve genetic diversity in the LMPN. This study contributes to the knowledge of the spatial genetic structure of species at risk in the Mexican temperate forest for their conservation.

Construction and Optimization of an Ecological Network in the Comprehensive Land Consolidation Project of a Small Rural Town in Southeast China

In recent years, China has put forward comprehensive land consolidation projects to solve problems in rural areas, such as cultivated land fragmentation, scattered spatial pattern of construction land and ecological environment pollution, and boost the rural revitalization strategy. Constructing ecological networks is important for maintaining ecological security. This study built an ecological network using morphological spatial pattern analysis (MSPA), spatial principal component analysis (SPCA) method and minimum cumulative resistance model (MCR) models to analyze the spatial and temporal characteristics and ecological security pattern. Finally, it was optimized by analyzing ecological network indices and using two methods of adding additional ecological sources and stepping stones. The results show that ecological sources and ecological corridors for three phases are located in the central and northern parts with an uneven distribution. In fact, adding new ecological sources is more efficient in balancing the ecological pattern of a study area. The ecological network indices α, β, γ and C values increased by 15.3%, 8.4%, 8.5% and 3.3%, respectively. Constructing and optimizing an ecological network is expected to provide scientific basis for small-scale landscape design, provide theoretical reference for spatial pattern optimization of comprehensive land consolidation projects and coordination of regional development and ecological protection.

Spatio-temporal variations in the ecological vulnerability of the Upper Mzingwane sub-catchment of Zimbabwe

Profiling eco-environmentally vulnerable (EV) areas can contribute to the development of mechanisms for environmental protection and sustainable management of ecological resources. Land cover change, population density, annual precipitation, mean temperature, remotely sensed indices, actual evapotranspiration, land surface temperature (LST), and runoff for the catchment for 1990, 2000, 2011, and 2020 were used to assess spatiotemporal ecological vulnerability. Spatial principal component analysis (SPCA) was used to assess thematic vulnerability for each year. The analytical hierarchical process (AHP) was then used to determine the weighting of the thematic maps to produce the final ecological vulnerability maps. Our results showed that most of the sub-basin had low and moderate vulnerability in 1990, 2000, 2011, and 2020, with the combined proportion of these areas being 80.6%, 55.45%, 83.92%, and 85.1%, respectively. The areas classified as high vulnerability decreased steadily over the investigated years, except in 2000, where an increase was observed. Most areas in the southern parts of the sub-basin were classified as moderately vulnerable, while high vulnerability values were recorded in the northern areas. The southern parts of the Upper Mzingwane basin are drier and less populated than the northern parts. The spatial architecture of vulnerability presented will help inform decision makers in mitigation planning and overall disaster risk management initiatives in the basin.

Ecological Sensitivity of Urban Agglomeration in the Guanzhong Plain, China

In the past two decades, China’s urbanization has advanced rapidly. In 2018, Xi’an was successfully selected as a national central city, and the Guanzhong Plain urban agglomeration (GZPUA) is emerging rapidly due to Xi’an. This study focuses on the current ecological status of the region and how to strike a balance between economic development and ecological protection. This study uses the ecological vulnerability of the Guanzhong urban agglomeration as a starting point to investigate the changes in its spatial and temporal distribution of ecological vulnerability and the primary driving factors, as well as to investigate the interaction between the changes in ecological vulnerability and urban agglomeration development in the GZPUA region. Using the “sensitivity–elasticity–pressure (SEP)” assessment framework model, this paper selects the spatial distribution data of natural, social, and economic sources in 2000 and 2020 based on the ecological environment characteristics of GZPUA. By using spatial principal component analysis, this paper quantitatively evaluates the ecological vulnerability changes of GZPUA in two periods, 2000 and 2020, with 1000 m × 1000 m raster as the evaluation unit, classifies the ecological vulnerability of the area into levels, and conducts a sub-regional in-depth study from different administrative regions. This research helps to comprehend the change in ecological environment quality in the GZPUA and provides a basis for ecological environment management decisions in the region. The results showed that (1) the ecological vulnerability of the Guanzhong Plain urban agglomeration as a whole is moderate, with the highest ecological vulnerability index (EVI) value of 0.89 and the lowest EVI value of 0.087 in 2000, and the highest EVI value of 0.93 and the lowest EVI value of 0.082 in 2020. The percentage of areas with the highest ecological vulnerability (moderate or severe) was 5.07% in 2000 and 15.11% in 2020. (2) The variation scope of the integrated EVI in the study region is 1.78–4.96 (2000) and 1.81–4.99 (2020), among which the EVI values in Xi’an, Bei Lin, Lian Hu, and Xin Cheng are the highest and the EVI values in Tai Bai, Zhou Zhi, and Feng Xian are the lowest. (3) In the central region of GZPUA, the spatial variation of CEVI is distributed in a circle that is highly congruent with the region’s economic and population development characteristics, whereas the spatial variation of CEVI in the southern mountainous region of the study area is primarily constrained by the topography and natural conditions. This region has low CEVI because of the high mountains and thick forests, which is a crucial ecological barrier for the GZPUA. (4) The EVI, ecological sensitivity index (ESI), ecological elasticity index (EEI), and ecological pressure index (EPI) have a strong relationship with land use. Among them, farmland and built-up land showed highly significant correlations with the EVI, ESI, EEI, and EPI (p &lt; 0.01).

Thermal-Imaging-Based PCA Method for Monitoring Process Temperature

To overcome the shortage of traditional temperature sensors, this paper adopts infrared thermal imaging technology for temperature measurement. To avoid the spatial information loss issue during the image data vectorization process, this paper adopted the spatial relationship between pixels in principal component analysis (PCA) model training, which is called spatial information-based PCA (SIPCA). Then, spatial information is also used in the fault localization method to enhance the fault location performance. Tested by an experimental tank system, the proposed method achieves better performance than the traditional PCA approach, and it can detect heat leakage faults on the surface of the equipment.

Spatial-Temporal Variation and Driving Factors of Ecological Vulnerability in Nansi Lake Basin, China.

Lake basins are one of the most significant areas of human-land interaction. It is essential for the region's ecological protection and high-quality development to assess their ecological vulnerability (EV) and analyze the key driving factors of EV. Considering the characteristics of the lake basin, we chose 17 indicators to evaluate the EV of the Nansi Lake Basin based on the "sensitivity-resilience-pressure" (SRP) model. Then, spatial principal component analysis (SPCA) and a transfer matrix were used to analyze the spatial-temporal variation characteristics of the EV. Moreover, the optimal parameters-based geographical detector (OPGD) was applied to investigate the factors influencing the spatial heterogeneity of the EV. The results indicated that the EV of the Nansi Lake Basin was characterized by a circling spatial structure, with low values distributed in the Nansi Lake and its surrounding areas, as well as high values concentrated in the northwest. The EV of the Nansi Lake Basin decreased from 2010 to 2020, indicating that the overall ecological pressure in the Nansi Lake Basin decreased. Climatic factors, land use type, and habitat quality were the primary factors that influenced the spatial heterogeneity of the EV in the basin. Our findings can serve as policy guidelines for ecological management and the sustainable development of the Nansi Lake Basin and also contribute to the EV assessment of lake basins.