Cold Spots Research Articles

Climatology of cold spots and LST minimums in Iran using high-resolution satellite data

Climatology of cold spots and LST minimums in Iran using high-resolution satellite data

Study on the spatial correlation effects and influencing factors of carbon emissions from the electricity industry: a fresh evidence from China.

Carbon emissions from the electricity industry (CEEI) account for a large proportion of China's total carbon emissions, and it is important to study the spatial correlation between CEEI and the influencing factors to promote cross-regional synergistic emission reduction and low-carbon development of the power system. In this paper, the quasi-input-output (QIO) model is applied to assess the transfer of carbon emissions generated by electricity trading based on the consideration of electricity carbon transfer, and the exploratory spatial data analysis (ESDA) method is applied to analyze the spatial correlation effect of carbon emissions from China's electric power sector from 2001 to 2020, analyzes its distribution pattern in both spatial and temporal dimensions, and applies the improved logarithmic mean Divisia index (LMDI) two-stage decomposition model to decompose the changes in CEEI into 11 influencing factors from the perspective of the whole industrial chain of power production, transmission, trade, and consumption. The research results show that (1) the spatial distribution of CEEI has obvious unevenness and aggregation characteristics, with high-high aggregation areas and hot spot aggregation areas generally concentrated in the North China Power Grid and the East China Power Grid, but the aggregation trend is gradually decreasing, while low-low aggregation areas and cold spot aggregation areas are concentrated in the Northwest China Power Grid and the Central China Power Grid, but the area is very limited. (2) The direction of carbon emission diffusion in China's electricity industry is gradually transitioning from southwest-northeast to northwest-southeast, and the east-west diffusion trend is stronger than the north-south diffusion trend and carbon emissions are gradually shifting to the northwest grid. (3) The total amount of electricity production is the most influential factor in the change of CEEI, driving the cumulative growth of CEEI by 4495.34 Mt, followed by GDP per capita and electricity consumption intensity. Coal consumption for power generation, the share of thermal power, and net electricity exports were the main factors inhibiting the increase in carbon emissions from the power sector, with cumulative contributions of -797.74 Mt, -619.99 Mt, and -47.76 Mt, respectively.

Ecological risk assessment and management for riverfront development along the Yangtze River in Jiangsu Province, China

The riverfront along large rivers, representing the water–land and human–nature interaction zone, is of great importance for economic and social development and eco-environmental protection. Human activities, such as urbanization and industrialization, together with inadequate urban planning and disorderly development, can result in serious ecological risks to riverfront ecosystems. The focus of this study was the riverfront along the Yangtze River in Jiangsu province, an area experiencing conflicting demands in terms of ecological protection and economic development. We identified the ecological problems and risks at different spatial scales (micro, meso, and macro) and, based on PSR model, construct an ecological risk assessment index system for any further development along the Yangtze River. Ecological hot spots and cluster zones were identified based on Getis-Ord Gi* hot spot analysis and Ward’s hierarchical clustering. The results showed that the ecological risk index at micro scale of the study area presented spatially positive correlation, with hot spots mainly concentrated in municipal districts. The hot spots of ecological risk assessment at the meso-scale are distributed in the estuary around the Yangtze River, and the cold spots are distributed on the Yang-Tai plain. According to the assessment indices of social economy, ecological function, and planning response at the macro scale, the study area could be divided into four clusters. Lastly, a spatial division of ecological risk posed by riverfront development along the Yangtze River in Jiangsu Province was constructed. On the basis of this analysis, we propose suitable risk management and resource protection measures.

Analysis of Spatiotemporal Patterns of Undernutrition among Children below Five Years of Age in Uganda

Background: This study aimed at examining the prevalence and variations in undernutrition among children below five years of age in Uganda while considering the influence of space and time factors. Various studies conducted in Uganda analyzed the undernutrition phenomenon among children below five years of age with a focus on the risk factors and spatial variations; however, no study has ever integrated the elements of time in examining the problem of undernutrition in Uganda. The approach of spatial and spatiotemporal analysis is essential in identifying cluster patterns, hotspots, trends, and emerging hotspots, which is crucial in making timely and location-specific interventions. Methods: Data from the six Uganda Demographic and Health Surveys spanning from 1990 to 2016 were used, with the main outcome variable being undernutrition among children below five years of age. A Composite Index of Anthropometric Failure was derived from the three undernutrition outcomes and subsequently used as a proxy of undernutrition in this study. All data that were relevant to this study were retrieved from the survey datasets and combined with the 2014 shape files of Uganda to enable spatial and spatiotemporal analysis. Spatial maps with the spatial distribution of the prevalence of undernutrition, both in space and time, were generated using ArcGIS Pro version 2.8. Moran’s I, an index of spatial autocorrelation, was used to test the hypothesis of no spatial autocorrelation, while the Getis–Ord (Gi*) statistic was used to examine hot and cold spot areas. Furthermore, space-time cubes were generated to establish the trend in undernutrition as well as to mirror its variations over time and across the country. Moreover, emerging hot spot analysis was done to help in identifying the patterns of undernutrition over time. Results: The national prevalence of undernutrition among children below five years of age was 31.96 percent, with significant spatial variations both in space across Uganda and in the time since 1989. The index of spatial autocorrelation (Moran’s I) confirmed spatial clustered patterns as opposed to random distributions of undernutrition prevalence. Four hot spot areas, namely, the Karamoja, the Sebei, the West Nile, and the Toro regions, were significantly evident. Most of the central parts of Uganda were identified as cold spot clusters, while most of Western Uganda, the Acholi, and the Lango regions had no statistically significant spatial patterns by the year 2016. The spatio-temporal analysis identified the Karamoja and Sebei regions as clusters of persistent, consecutive, and intensifying hot spots, West Nile region was identified as a sporadic hotspot area, while the Toro region was identified with both sporadic and emerging hotspots. In conclusions, undernutrition is a silent pandemic that calls for immediate and stringent measures. At 31.96 percent, the prevalence is still very high and unpleasant. To reduce the prevalence of undernutrition and to achieve SDG goal 2, policymakers, as well as implementers, should consider the spatial effects and spatial and spatiotemporal variations across the country and prioritize interventions to hot spot areas. This would ensure efficient, timely, and region-specific interventions.

Dynamics changes and prediction of ecosystem services in the Qinghai-Tibet Plateau, western China

As an important ecological security barrier and a key region for biodiversity conservation in China, assessing ecosystem services (ESs) on the Qinghai-Tibet Plateau (QTP) over long time series is of great significance. In this study, we quantified and analyzed the ESs of the QTP based on modeling combined with multivariate data. The results showed that habitat quality, water conservation, carbon storage and soil retention on the QTP from 1985 to 2020 were generally positive, and the quality of ESs and the distribution of cold hot spots were spatially consistent. The conservation of forest, shrub and grassland on the QTP contributed to the improvement of ESs. The supply capacity of ESs was higher in the southeastern part of the QTP while the areas with higher demand were located in the northeast. Based on quadrant division, it was found that the mismatch between supply and demand of ESs on the QTP was mainly "low supply and low demand" and "high supply and low demand". From 2020–2050, ESs on the QTP show varying degrees of increase under all scenarios, with greater changes in ESs under the SSP3–7.0 scenario and the slowest growth in ESs under the SSP5–8.5 scenario.

Fractionation versus Adaptation for Compensation of Target Volume Changes during Online Adaptive Radiotherapy for Bladder Cancer: Answers from a Prospective Registry.

Online adaptive radiotherapy (ART) allows adaptation of the dose distribution to the anatomy captured by with pre-adaptation imaging. ART is time-consuming, and thus intra-fractional deformations can occur. This prospective registry study analyzed the effects of intra-fraction deformations of clinical target volume (CTV) on the equivalent uniform dose (EUDCTV) of focal bladder cancer radiotherapy. Using margins of 5-10 mm around CTV on pre-adaptation imaging, intra-fraction CTV-deformations found in a second imaging study reduced the 10th percentile of EUDCTV values per fraction from 101.1% to 63.2% of the prescribed dose. Dose accumulation across fractions of a series was determined with deformable-image registration and worst-case dose accumulation that maximizes the correlation of cold spots. A strong fractionation effect was demonstrated-the EUDCTV was above 95% and 92.5% as determined by the two abovementioned accumulation methods, respectively, for all series of dose fractions. A comparison of both methods showed that the fractionation effect caused the EUDCTV of a series to be insensitive to EUDCTV-declines per dose fraction, and this could be explained by the small size and spatial variations of cold spots. Therefore, ART for each dose fraction is unnecessary, and selective ART for fractions with large inter-fractional deformations alone is sufficient for maintaining a high EUDCTV for a radiotherapy series.

Numerical and Techno-Economic Analysis of Batch Annealing Performance Improvements in Tinplate Manufacturing

The present study examines the performance improvement in the batch annealing process used in tinplate manufacturing by enhancing the heat transfer towards the steel coils and altering annealing cycle parameters. Presently, the heat transfer in the furnace is non-uniform, resulting in non-uniform temperature profiles and recrystallisation inside the coils, affecting the final coated steel quality. This study modelled a current furnace and four improvement proposals utilising transient computational fluid dynamics, to produce coil temperature profiles and rank the cases by the highest coil temperature uniformity achieved at the end of soaking. By increasing the soaking temperature and time, as well as the coiling tension before annealing and altering the coil size, the aim was to achieve higher and more uniform coil temperatures that could ensure successful recrystallisation with less defects, especially at the cold spot area in the middle of the coil. Then, a techno-economic analysis compared the cost-effectiveness of the scenarios based on the associated costs and the improvement in the scratching defects of the batch-annealed steel. Overall, most cases exhibited positive results regarding temperature uniformity enhancement, but increasing the coiling tension was considered the most promising option, due to the combination of a large defect reduction potential and cost savings per cycle.

Analysis on the vaccination coverage of 13-valent pneumococcal conjugate vaccine in China from 2017 to 2021

Objective: To explore the vaccination coverage of the 13-valent pneumococcal conjugate vaccine (PCV13) in China from 2017 to 2021. Methods: Using the reported number of PCV13 administrated doses from 2017 to 2021 and the population data from 31 provinces in China, which were collected by the Immunization Program Information System and summarized data at different levels (prefecture, provincial, and national). Collecting batch release data of PCV13 during the same period through the official website of the National Institutes for Food and Drug Control. The average coverage level of PCV13 was calculated by comparing the number of PCV13 vaccinations reported annually to the number of births in that year, and the spatial auto-correlation analysis was conducted in 2021 at the prefecture level. The coverage of PCV13 vaccination was estimated by the total vaccine doses administered each year divided by the number of newborn in the year, as of the administrated dose number per 100 people. Results: From March 2017 to December 2020, the total batch release of PCV13 was 20.06 million, with a total of 71.54, 384.75, 475.45, and 10.8886 million doses each year. During the same period, PCV13 reported doses were 20.2369 million and the vaccination doses from 2017 to 2021 were 4.08, 170.46, 407.52, 599.77, and 8.4185 million doses, respectively. From 2017 to 2021, the ratio of PCV13 doses administrated per 100 infants in each year was 0.25, 10.26, 23.81, 38.16, and 69.90 doses per 100 people, respectively. The range of the ratio in each province increased from 3.85 doses in 2017 to 264.41 doses per 100 people in 2021. The spatial auto-correlation analysis results showed that based on prefecture-level cities, there was spatial clustering in a certain area of PCV13 coverage from 2017 to 2021, and the spatial correlation in 2021 was the highest. The hotspot analysis showed that the hotspot areas with high coverage levels of PCV13 were concentrated in Jiangsu, Zhejiang, Shanghai, Fujian and their surrounding areas. The cold spots with low vaccine coverage were concentrated in Yunnan, Qinghai, Tibet, and their surrounding areas. Conclusion: The average coverage level of PCV13 is low in China with significant regional differences.

CFD Investigation of Fin Design Influence on Phase Change Material Melting for Solar Thermal Energy Storage

In this study, an investigation was conducted on four distinct configurations, designated as Case-1, Case-2, Case-3, and Case-4, focusing on parametric analysis. Each configuration features a cylindrical enclosure containing pure Gallium, a phase change material (PCM). The solid-to-liquid phase transition of the encapsulated material was examined using a 2D CFD methodology. Additionally, the effect of applying three temperatures, T1=32∘C, T2=39∘C, and T3=42∘C, along the generator of the enclosure, with or without fins, was also studied. To accurately model the melting process of the PCM, the Enthalpy- Porosity Method was employed, and meticulous detailing of underlying assumptions was under- taken to ensure precise representation. The validation process involved comparing outcomes of the physical solidification/melting model with reference data from a state-of-the-art study. The specific cases comprised Case-1 - a slender finless cylinder; Case-2 - a thin finned cylinder (l=10mm, t=0.6mm); Case-3 - featuring larger fins (l=20mm, t=0.6mm); and Case-4 - incorporating the largest fins (l=30mm, t=0.6mm). Strategically incorporating thin fins accelerates Gallium melting significantly, reducing times by up to 89%. This enhancement is driven by a 96% increase in the heat transfer coefficient (h), leading to faster melting rates. In addition, fins boost the Nusselt number (Nu) by 91%, indicating improved convective heat transfer and enhanced melting. Melting rates increase by around 30%, notably in Case-3. Temperature T1 shifts dominant heat transfer from convection to conduction, as seen in 2D CFD contours with stratified patterns in Case-3 at t=240s and Case-4 at t=240s and t=300s. A localized cold spot at t = 300s in Case-4 signals localized heat transfer effects.

THU500 Geospatial Analysis To Quantify Spatial Heterogeneity Of Tumor Microenvironment

Abstract Disclosure: J. Yoo: None. C. Mitra: None. Y. Yue: None. A. Soliman: None. Z. Madak Erdogan: None. Metabolic heterogeneity, a concept describing distinct differences in nutrient metabolism within the cells of a healthy or diseased tissue, is a common challenge in development and cancer research. Current methods, such as histology and Magnetic Resonance Imaging (MRI), cannot visualize nutrient uptake into single cells, making it difficult to understand the heterogeneity that affects cellular growth and metabolism. Visium Spatial Transcriptomics, a method that shows regional gene expression, is emerging as a powerful spatial analysis tool, and we aim to integrate this transcriptomic method with other biologically relevant datasets to highlight the importance of cell-microenvironment interactions. We propose to leverage geostatistical tools to model the multivariate covariance structure of genes expression profiles to allow: 1) understanding of their spatial characteristics and covariance changes under certain conditions (e.g. drug treatment or damage), 2) using these covariance structures to simulate synthetic samples at a scale sufficient to train the state of art neural network architectures, and 3) incorporating spatial awareness directly in the machine learning/deep learning models by enriching the spatial transcriptomics data using distance proximity functions. We will quantify the tumor microenvironment spatial heterogeneity using different approaches. First, we will analyze the degree of spatial auto-correlation to estimate the ranges of spatial heterogeneity within a tumor. We also plan to quantify the degree of anisotropy to identify if the tumor heterogeneity is happening along specific axis. Different local clustering indicators will be also calculated, such as the Getis-Ord (Gi*) statistic and Local Moran's I to identify the prevalence of hot and cold spots in the tumor. These hot and cold spots will be used to segment the tumor area into sub-regions and further quantify the local heterogeneity with a single tumor. We hypothesize that transcriptional heterogeneity reflects phenotypic differences in different regions of healthy or diseased tissue, rendering cells in certain regions to display a differential response to external stimuli (e.g. diet or drugs). Integration of multiple information (e.g. retrospective patient data) with different spatial heterogeneity indicators identified from the geospatial analyses could aid in identification of patients who are resistant to cancer therapies and further advance personalized therapy. Presentation: Thursday, June 15, 2023

Dynamic cosmography of the local Universe: Laniakea and five more watershed superclusters

This article delivers the dynamical cosmography of the local Universe within z = 0.1 (1 giga light-years). We exploited the gravitational velocity field computed using the CosmicFlows-4 catalog of galaxy distances in order to delineate superclusters as watersheds, publishing for the first time their size, shape, main streams of matter, and the location of their central attractor. We confirm the size of Laniakea, our home supercluster, to be 2 × 106 (Mpc h−1)3. We dynamically define five more known superclusters in the same way as Laniakea: Apus, Hercules, Lepus, Perseus-Pisces, and Shapley. Additionally, we found the central repellers of the Bootes and Sculptor voids, and based on our analysis, the Dipole and Cold Spot repellers appear as a single gigantic entity. Interestingly, the observed superclusters are an order of magnitude larger than the theoretical ones predicted by cosmological ΛCDM simulations.

Research on the spatial-temporal evolution pattern of China's industrial carbon emission efficiency-based on the super-efficiency SBM model

This paper uses the super efficiency SBM model based on unexpected output to calculate the industrial carbon emission efficiency of 30 provinces in China from 2005 to 2019, and uses spatial autocorrelation and other methods to conduct an empirical analysis on the dynamic evolution process and temporal and spatial differences of carbon emission efficiency. The results show that China's industrial carbon emission efficiency is still in the low efficiency stage, with an average value of 0.34. In the study period, although the overall trend is rising, the spatial and temporal differences between provinces are obvious. The overall Moran's I index is subject to the impact of social policy environment on the time path, showing an overall "M" type fluctuation trend, and its spatial difference characteristics change in stages. At the same time, there is a significant global spatial agglomeration effect across the country, and there is a spatial dependency between provinces. The agglomeration trend is significant, forming a cluster with the eastern coastal area as the high value center, and the northwest inland area as the low value center. The Getis OrdGI * index reveals that the local spatial agglomeration characteristics of China's industrial carbon emission efficiency always maintain the pattern of "hot in the east and cold in the west", which echoes the overall spatial evolution pattern of China. The hot spots and sub hot spots of China's industrial carbon emission efficiency are mainly concentrated in the southeast coastal areas with relatively superior economic development, and present a "semi enclosed" pattern. Cold spot area and sub cold spot area gradually evolved into a "suppression" pattern dominated by provinces in northwest China, comprehensively suppressing hot spots. This paper conducts an all-round evaluation of China's industrial carbon emission efficiency from the perspective of regional differentiation, and deeply studies the regional differences and spatial evolution pattern of carbon emission efficien cy in various provinces. It is crucial to achieve the goal of carbon emission reduction in China, and has important practical value and practical significance.

An Investigation of High-Z Material for Bolus in Electron Beam Therapy

Electron beams are frequently used for superficial tumors including: primary skin cancers, surgical scars, cutaneous lymphomas and benign conditions like keloids. However, due to electron beam characteristics the surface dose is 75-95% of the prescribed dose depending on beam energy thus requiring placement of bolus to augment surface dose. Various types of boluses; wet gauge/towel, superflab, superstuff, aquaplast, 3D printed plastics, customized dot-decimal bolus, thermoshield, brass and tantalum wire mesh are commonly used in clinics with variable difficulties that are not perfect. As majority of these devices do not snug to the skin contour and create air-gap that is known to produce significant dose perturbations creating hot and cold spot. The variable dosimetry has cosmetic implications and potentially increased risk of recurrence. A new cloth-like high-Z materials; Tungsten, (Z = 74) and Bismuth, (Z = 83) impregnated with silicone gel are now commercially available which is investigated in this study for bolus purpose. Commercially available, super soft silicone-gel based submillimeter thin Tungsten and Bismuth sheets were investigated for bolus properties in electron beams in the range of 6-12 MeV using 10x10 cm2 applicator. These materials were tested on various body contour for perfect snug without any air traps. Using parallel plate ion chamber measurements were performed in a solid water phantom on a medical linear accelerator machine. Depth dose characteristics were measured to optimize the thickness for surface dose to be 100% for selected electron therapy. Surface dose for a 10x10 cm2 cone for 6, 9, 12 MeV beams were measured to be 75.1%, 80.1% and 86.2%, respectively. Silicone-gel Tungsten and Bismuth sheets produce significant electrons thus increasing surface dose. Based on measured depth dose, our data showed that Tungsten sheets of 0.14 mm, 0.18 mm and 0.2 mm and Bismuth sheets of 0.42 mm, 0.18 mm and 0.2 mm provide 100% surface dose for 6, 9 and 12 MeV beams, respectively without any changes in depth dose except increasing surface dose. The new Tungsten and Bismuth based silicone-gel clothlike sheets are extremely soft but high tensile metallic bolus materials that can fit flawlessly on any skin contour without any air trap or variable thickness or spillage of the water as in conventionally used wet gauge. Only 0.2 mm thick sheets are needed for 100% surface dose without degradation of the depth dose characteristics. These materials are reusable and ideal for bolus in electron beam treatment. This investigation opens a new frontier in designing new bolus materials optimum for patient treatment.

Images of Betelgeuse with VLTI/MATISSE across the Great Dimming

ABSTRACT From Nov. 2019 to May 2020, the red supergiant star Betelgeuse experienced an unprecedented drop of brightness in the visible domain called the Great Dimming event (GDE). Large atmospheric dust clouds and large photospheric convective features are suspected to be responsible for it. To better understand the dimming event, we used mid-infrared long-baseline spectro-interferometric measurements of Betelgeuse taken with the Very Large Telescope Interferometer/Multi AperTure mid-Infrared SpectroScopic Experiment (VLTI/MATISSE) instrument before (Dec. 2018), during (Feb. 2020), and after (Dec. 2020) the GDE. We present data in the 3.98–4.15 µm range to cover SiO spectral features molecules as well as adjacent continuum. We have employed geometrical models, image reconstruction, as well as radiative transfer models to monitor the spatial distribution of SiO over the stellar surface. We find a strongly inhomogeneous spatial distribution of SiO that appears to be looking very different between our observing epochs, indicative of a vigorous activity in the stellar atmosphere. The contrast of our images is small in the pseudo-continuum for all epochs, implying that our MATISSE observations support both cold spot and dust cloud model.

‘Cold spots’ in language degree provision in England

ABSTRACT People have been raising the alarm about a language education crisis in the UK, particularly in England, for twenty years. Yet the crisis continues: the number of young people studying languages at school is low, especially in socioeconomically less-privileged areas. University programmes – particularly in universities with below average entry tariffs – are closing, but we do not understand the regional impact of this decline. This paper fills that gap by identifying ‘cold spots’: areas of the country where no universities offer language degrees. The programming language R was used to analyse the location of universities at various entry tariffs, and areas of the country further than a commutable distance of 60 km were identified. Large cold spots were found in the North, East and South West of England for universities offering languages at below average entry tariff, with the cold spot in the South West also present at higher entry tariffs. This is a social justice issue, since most students attend university close to home, with students from less-privileged socioeconomic backgrounds and some ethnic minority backgrounds more likely to commute. This leads to a key strategic recommendation: to open language degree programmes at one lower tariff university in each cold spot.

Spatio–Temporal Evolutionary Features and Drivers of Green Competitiveness of Cities Surrounding the Yellow River

Based on the scientific concept of city green competitiveness, an integrated evaluation indicator system was established to use the entropy method in order to measure the green competitiveness index of 78 cities surrounding the Yellow River (YR) from 2006 to 2020. Further, the spatio–temporal features and drivers of city green competitiveness were analyzed using various methods. The research found the following: (1) Although the green competitiveness of cities surrounding the YR has been growing steadily, the overall level is not high. (2) The green competitiveness of cities surrounding the YR can be spatially characterized as “downstream > midstream > upstream”; the absolute and relative differences between cities are both increasing, and overall differences stem mainly from the hypervariable density. (3) The positive spatial correlation between the green competitiveness of cities surrounding the YR is significant, with the “cold spot” in southeastern Gansu and the “hot spot” in the Shandong Peninsular city cluster. (4) The level of city infrastructure construction, the level of urbanization, and science and technology innovation are the main drivers of the green competitiveness of cities surrounding the YR. In addition, the interaction forces of each factor were found to be much stronger than the effects of individual factors.

A GIS Approach for Analysis of Traffic Accident Hotspots in Abha and Bisha Cities, Saudi Arabia

Road traffic accidents present substantial global challenges, encompassing a wide range of consequences that have implications for the economy, public health, the environment, and society. The present study is focused on the phenomenon of rapid urbanization in Abha and Bisha, two cities located in the Kingdom of Saudi Arabia. These cities have witnessed a substantial growth in urbanization, with a notable increase of 225% over a span of 40 years. The expansion of urban areas has given rise to significant concerns regarding the density of the road infrastructure, which has been further exacerbated by an increase in the volume of vehicles. Consequently, this has led to a notable escalation in traffic-related issues and accidents. Analysis reveals that traffic accidents are concentrated in specific areas, with hotspots primarily located in the western regions of Abha and Bisha, while cold spots are concentrated in the northern areas. Furthermore, a strong positive correlation (r = 0.93) is observed between the number of traffic accidents and road type, with over half of the accidents occurring on highways. Notably, the highways in Abha and Bisha predominantly follow a direction from southwest to northeast at a 71.1° angle. In conclusion, this research offers significant findings regarding the prevalence and determinants of traffic accidents in Abha and Bisha, emphasizing the need for effective traffic management strategies to enhance road safety and mitigate the associated risks.

Operationalizing data-driven campaigning: designing a new tool for mapping and guiding regulatory intervention

ABSTRACT Since the Cambridge Analytica scandal, governments are increasingly concerned about the way in which citizens’ personal data are collected, processed and used during election campaigns To develop the appropriate tools for monitoring and controlling this new mode of “data-driven campaigning” (DDC) regulators require a clear understanding of the practices involved. This paper provides a first step toward that goal by proposing a new organizational and process-centred operational definition of DDC from which we derive a set of empirical indicators. The indicators are applied to the policy environment of a leading government in this domain – the European Union (EU) – to generate a descriptive “heat map” of current regulatory activity toward DDC. Based on the results of this exercise, we argue that regulation is likely to intensify on existing practices and extend to cover current “cold spots”. Drawing on models of internet governance, we argue that this expansion is likely to occur in one of two ways. A “kaleidoscopic” approach, in which current legislation extends to absorb DDC practices and a more “designed” approach that involves more active intervention by elites, and ultimately the generation of a new regulatory regime.

Land surface and air temperature dynamics: The role of urban form and seasonality

Due to the scarcity of air temperature (Ta) observations, urban heat studies often rely on satellite-derived Land Surface Temperature (LST) to characterise the near-surface thermal environment. However, there remains a lack of a quantitative understanding on how LST differs from Ta within urban areas and what are the controlling factors of their interaction. We use crowdsourced air temperature measurements in Sydney, Australia, combined with urban landscape data, Local Climate Zones (LCZ), high-resolution satellite imagery, and machine learning to explore the influence of urban form and fabric on the interaction between Ta and LST. Results show that LST and Ta have distinct spatiotemporal characteristics, and their relationship differs by season, ecological infrastructure, and building morphology. We found greater seasonal variability in LST compared to Ta, along with more pronounced intra-urban spatial variability in LST, particularly in warmer seasons. We also observed a greater temperature difference between LST and Ta in the built environment compared to the natural LCZs, especially during warm days. Natural LCZs (areas with mostly dense and scattered trees) showed stronger LST-Ta relationships compared to built areas. In particular, we observe that built areas with higher building density (where the heat vulnerability is likely more pronounced) show insignificant or negative relationships between LST- Ta in summer. Our results also indicate that surface cover, distance from the ocean, and seasonality significantly influence the distribution of hot and cold spots for LST and Ta. The spatial distribution for Ta hot spots does not always overlap with LST. We find that relying solely on LST as a direct proxy for the urban thermal environment is inappropriate, particularly in densely built-up areas and during warm seasons. These findings provide new perspectives on the relationship between surface and canopy temperatures and how these relate to urban form and fabric.

Spatio-temporal dynamics of ecosystem service values in China’s Northeast Tiger-Leopard National Park from 2005 to 2020: Evidence from environmental factors and land use/land cover changes

The Northeast Tiger-Leopard National Park (NTLNP) in China is an area of great ecological significance, known for its abundant wilderness resources and biodiversity. However, the habitats in NTLNP have been threatened by historical land use and land cover (LULC) changes caused by urban expansion and economic development. In response to this challenge, this study based on remote sensing-derived LULC products from 2005 to 2020, utilized the equivalent factors refined ecosystem service values (ESV) assessment model, and in conjunction with Moran’s I and Getis-Ord Gi* spatial analysis methods to evaluate the macro-scale and pixel-scale spatio-temporal dynamics of ESV in the NTLNP. We also employed the cold and hot spot analysis (CHSA) method to identify zones of ESV improvement and degradation within the NTLNP. Our findings indicate that over the past 15 years: (1) Forestland in the NTLNP possesses the most substantial ESV proportion (97.48%), and the regulating service value is the major contributor among the four types of services (71.31%). (2) Despite a fluctuating trend of increasing, decreasing, and then growing overall ESV growth within the NTLNP, the ecological benefits have been difficult to return to their peak values of 42.184 billion CNY in 2015. (3) The waters of NTLNP exhibit a high LULC dynamic of 27.91%, with an ESV underestimation of 28.4 million CNY. (4) The pixel-scale analysis unveils a dispersed distribution of ESV degradation pixels, with their cumulative area significantly larger than the share of ESV improvement pixels. (5) The CHSA results showed that areas with intensive human activity, such as towns and their surrounding areas, tend to experience ESV degradation, while regions with effective river management, such as the river basin of Hunchun county-level city, experience ESV improvement. Therefore, this study delineates the regulatory zones of the NTLNP by the result of the CHSA-based decision tree, pinpoints ecologically threatened core areas and further categorizes these based on risk levels and types, helping maintain a dynamic balance between the allocation of human and physical resources for park management and the primary conservation needs within the national park. Moreover, the study recommends that policymakers take measures to strengthen risk mitigation, enhance their focus on areas where ESV is fragile, and optimize the allocation of internal resources in national parks.