Urban Population Research Articles

Knowledge and practices related to Ambient Air Pollution in an urban population in the Capital City of India

Knowledge and practices related to Ambient Air Pollution in an urban population in the Capital City of India

Examination of Housing Quality in The Peri-Urban Areas of Akure, Nigeria

Rapid urban population expansion, high living costs, and a need for affordable housing all encourage migration to Akure’s peri-urban districts. This drive has led to increased land utilization for housing development in peri-urban areas. This study evaluated housing quality in the peri-urban areas of Oba-Ile, Oda, and Ibule-Soro in Akure. Households were the unit of analysis, with one household head per building selected for questionnaire administration. Based on an average household size of five people per family and five households per building in Ondo State, the total number of households in the three locations was 47,110. From the 47,110 households, 800 households (1.7%) were randomly selected for the questionnaire administration. Data from the field survey were subjected to statistical analysis. The results revealed that some buildings were structurally unsound; most buildings had corrugated iron roofs and lacked sanitation infrastructure; and open defecation was commonplace, particularly in Ibule-Soro. These findings call for better urban planning and investment in basic amenities to improve housing quality and living standards in peri-urban areas.

Rethinking Urban Water Management Through Drivers-Pressures-States-Impacts-Responses Framework Application in Chennai, India.

Cities suffering water scarcity are projected to increase in the following decades. However, the application of standardized indicator frameworks for assessing urban water resource management problems is on an early stage. India is expected to have the highest urban population facing water scarcity in the world by 2050. In this study, the authors assess how the Drivers-Pressures-States-Impacts-Responses framework, a causal framework adopted by the European Environment Agency, can contribute to evaluate water management challenges in cities and apply it to Chennai, India´s fourth-largest urban agglomeration. The framework proved to be a helpful tool for the evaluation of water management challenges in cities by disentangling relationships between environmental indicators and structuring dispersed data that allows a better understanding for policymakers. The main drivers identified in Chennai were population growth and economic development which generated impacts such as loss of aquatic ecosystems, low water table, low water quality, and reduction of biodiversity and human health. As a response, better urban planning, projects for new water infrastructure, and water bodies restoration have been implemented. Nevertheless, Chennai keeps facing difficulties to achieve proper water management. The severe hit of the COVID-19 pandemic on the Indian economy and its future management will be key for achievements related to water management.

Air pollution, viral spread and health outcomes evidence from strikes in France.

To evidence the impact of air pollution on the health of urban populations, several studies use natural experiments that shift commuting from public transport to cars (or vice-versa). However, as public transport use declines, reduced interpersonal contact may lead to slower virus spread and thus lower respiratory morbidity. Using a difference-in-differences strategy, we show that respiratory hospitalisations are both positively affected by air pollution and negatively affected by viral spread following partial unavailability of public transport due to strikes in the ten most populated French cities during the period 2010-2015. Our results are in line with studies in other countries that have found a significant increase in urgent respiratory hospitalisations following a public transport strike, most likely due to car pollution, but we also find a detectable interaction with viral spread, which should not be overlooked when interpreting these studies.

Evaluating urban population carrying capacity of Surat: probability-satisfaction approach

With around 36 % of urbanization, Indian cities are becoming saturated because of increased migration. This is resulting in excessive utilization of natural resources and physical infrastructure. The unprecedented excessive utilization of the resources needs critical evaluation for better planning. For that, it is important to evaluate an urban area's true population carrying capacity given its limited resources and infrastructure. It helps planners and policymakers for better management of cities. This paper shows an estimation of the urban population carrying capacity of Surat City using the Probability-Satisfaction method with the help of various factors like water treatment & solid waste management to employment & hospital beds which cover physical as well as social factors. Analysis shows the population carrying capacity of Surat City at different Probability-Satisfaction levels and compares it with the current scenario. Some important results are that when the Probability-Satisfaction level changes from acceptable to ideal level, Surat City’s health infrastructure has a maximum population carrying capacity of 112.1 million to 102.2 million simultaneously and solid waste management has the lowest population carrying capacity which is 4.7 million to 3.9 million simultaneously. Also, it's observed that factors like healthcare, wastewater treatment, and green area show less rigidness while factors like wastewater treatment, road area, and electricity show more rigidness in increasing carrying capacity.

A Data Analytics and Machine Learning Approach to Develop a Technology Roadmap for Next-Generation Logistics Utilizing Underground Systems

The increasing density of urban populations has spurred interest in utilizing underground space. Underground logistics systems (ULS) are gaining traction due to their effective utilization of this space to enhance urban spatial efficiency. However, research on technological advancements in related fields remains limited. To address this gap, we applied a data-driven approach using patent data related to the ULS to develop a technology roadmap for the field. We employed Latent Dirichlet Allocation (LDA), a machine learning-based topic modeling technique, to categorize and identify six specific technology areas within the ULS domain. Subsequently, we conducted portfolio analytics to pinpoint technology areas with high technological value and to identify the major patent applicants in these areas. Finally, we assessed the technology market potential by mapping the technology life cycle for the identified high-value areas. Among the six technology areas identified, Topic 1 (Underground Material Handling System) and Topic 4 (Underground Transportation System) showed significant patent activity from companies and research institutions in China, the United States, South Korea, and Germany compared to other countries. These areas have the top 10 patent applicants, accounting for 20.8% and 13.6% of all patent applications, respectively. Additionally, technology life cycle analytics revealed a growth trajectory for these identified areas, indicating their rapid expansion and high innovation potential. This study provides a data-driven methodology to develop a technology roadmap that offers valuable insights for researchers, engineers, and policymakers in the ULS industry and supports informed decision-making regarding the field’s future direction.

Mild and moderate COVID-19 during Alpha, Delta and Omicron pandemic waves in urban Maputo, Mozambique, December 2020-March 2022: A population-based surveillance study.

In sub-Saharan Africa, reported COVID-19 numbers have been lower than anticipated, even when considering populations' younger age. The extent to which risk factors, established in industrialised countries, impact the risk of infection and of disease in populations in sub-Saharan Africa, remains unclear. We estimated the incidence of mild and moderate COVID-19 in urban Mozambique and analysed factors associated with infection and disease in a population-based surveillance study. During December 2020-March 2022, 1,561 households (6,049 participants, median 21 years, 54.8% female, 7.3% disclosed HIV positive) of Polana Caniço, Maputo, Mozambique, were visited biweekly to report respiratory symptoms, anosmia, or ageusia, and self-administer a nasal swab for SARS-CoV-2 testing. Every three months, dried blood spots of a subset of participants (1,412) were collected for detection of antibodies against SARS-CoV-2 spike glycoprotein and nucleocapsid protein. Per 1000 person-years, 364.5 (95%CI 352.8-376.1) respiratory illness episodes were reported, of which 72.2 (95%CI 60.6-83.9) were COVID-19. SARS-CoV-2 seroprevalence rose from 4.8% (95%CI 1.1-8.6%) in December 2020 to 34.7% (95%CI 20.2-49.3%) in June 2021, when 3.0% were vaccinated. Increasing age, chronic lung disease, hypertension, and overweight increased risk of COVID-19. Older age increased the risk of SARS-CoV-2 seroconversion. We observed no association between socio-economic status, behaviour and COVID-19 or SARS-CoV-2 seroconversion. Active surveillance in an urban population confirmed frequent COVID-19 underreporting, yet indicated that the large majority of cases were mild and non-febrile. In contrast to reports from industrialised countries, social deprivation did not increase the risk of infection nor disease.

The Spatiotemporal Matching Relationship between Metro Networks and Urban Population from an Evolutionary Perspective: Passive Adaptation or Active Guidance?

With the operation of the first route in Xi’an City, the matching relationship between the metro networks and the urban population is a root factor affecting the utilization of rail transit facilities. The mismatch between the metro networks and the urban population has led to an imbalance between the supply and demand for rail transport, resulting in wasted urban infrastructure. Based on this issue, the research objective is to focus on the spatiotemporal variations of the matching relationship. Firstly, the topological network model abstractly extracted metro spatial distribution features, and the spatial autocorrelation model was adopted to identify the evolution characteristics of the metro networks and urban population. Secondly, this paper adopted a time-lagged regression model to demonstrate the action relationship from 2011 to 2021. Then, the compositive coordination index was utilized to assess the variation of the global matching relationship. Finally, the paper explored spatial heterogeneity through the coupling coherence degree attached to grid cells. The research results indicate that the Moran’s I value of metro elements decreased from 0.782 to 0.510 with the further complexity of topological networks, while the population was consistently high in spatial dependence with a Moran’s I value of around 0.75 during the decade. Based on the regression coefficients and significance, this paper verified the hypothesis that the metro networks and urban population had a positive time-lagged feedback effect in urban development. From 2011 to 2021, the compositive coordination index symbolizing the global matching relationship increased from 0.29 to 0.90, but the coupling coherence degree shows significant spatial heterogeneity in different grid units. Differentiated spatial planning strategies were proposed for varied areas to efficiently utilize rail transit, which may provide a reference for other cities with the same reality problem.

Optimizing green and gray infrastructure planning for sustainable urban development

The anticipated increase in urban population of 2.5 billion people by 2050 poses significant environmental challenges. While the various environmental impacts of urbanisation have been studied individually, integrated approaches are rare. This study introduces a spatially explicit model to assess urbanization’s effects on ecosystem services (green infrastructure availability, cooling, stormwater retention) and the environmental impact of building construction (material demand, greenhouse gas emissions, land use). Applied to the Netherlands from 2018 to 2050, our results show that integrating green infrastructure development with building construction could increase green areas by up to 5% and stabilize or increase ecosystem service provisioning. Dense building construction with green infrastructure development is generally more beneficial across the Netherlands, reducing resource use and enhancing ecosystem services. Conversely, sparse construction with green infrastructure is more advantageous for newly built areas. These findings offer insights into the environmental consequences of urbanization, guiding sustainable urban planning practices.

Exploring the user experience, quality, and provision of urban greenspace: A mixed-method approach

Urban greenspace plays a crucial role in city design, offering residents various benefits for their health and wellbeing. With increasing urbanisation and human population growth, urban greenspace is becoming an even more significant resource. By implementing a mixed-method approach, we conducted a comprehensive assessment of urban greenspace based on public usage and perceptions, and quality, availability and accessibility in Derby, UK. Our methodology included an online questionnaire to investigate greenspace usage and perceptions, an in-situ assessment to assess greenspace quality, and Geographical Information Systems analysis to quantify greenspace provision based on Natural England’s (2023) Accessible Greenspace Standards (AGS). We found that greenspace usage and perception vary according to demographic and socioeconomic aspects, with younger people and students showing lower engagement with greenspace. Positive engagement correlates with factors such as proximity, car access, employment, and education. We also found that moderately high levels of greenspace quality (69.47/100) are available in the city, with the most notable insufficiencies related to quietness/peacefulness, aesthetics, and naturalness. Finally, none of the AGS criteria are met at a city-wide scale given the lack of large greenspace sites (particularly over 100 ha) and inequalities in spatial distribution. Our study highlights the value of the use of different methodologies to assess greenspace-related factors and emphasises the significance of public engagement in evaluating greenspace quality. Additionally, we identified factors adversely affecting greenspace use, including parking fees and issues with facilities, amenities, and safety. We therefore recommend interventions to address these challenges and enhance greenspace experience and accessibility in the city.

The flower does not open in the city: evolution of plant reproductive traits of Portulaca oleracea in urban populations.

The impact of urbanization on plant evolution, particularly the evolution of reproductive traits, remains largely unknown. In this study, we aimed to investigate the consequences of urbanization on the reproductive traits of Portulaca oleracea in the Kantō region of Japan. Portulaca oleracea has a unique cleistogamous reproductive system, which consists of genetically determined chasmogamous (open, CH) and cleistogamous (closed, CL) plants. We collected seeds of P. oleracea from ten populations in rural areas and ten populations in urban areas. In a common garden experiment, we recorded the type of flowers (CH or CL), reproductive phenology and seed production. All individuals produced either CH or CL flowers, allowing us to classify them as either CH or CL plants. We observed a significant difference in the prevalence of CH and CL plants between rural and urban populations: the number of CH plants was generally low and was particularly low among urban individuals. Compared to CH plants, CL plants showed earlier phenology and produced heavier seeds, which is consistent with stress avoidance in response to heat and drought stress conditions in urban areas. Our findings suggest that urbanization may drive an evolutionary change in the cleistogamous reproductive system of P. oleracea. CL plants with earlier phenology and larger seeds might be better adapted to urban environments, where they are subjected to harsh heat and drought stress.

Rural-Urban Cancer Incidence and Trends in the United States, 2000 to 2019.

Despite consistent improvements in cancer prevention and care, rural and urban disparities in cancer incidence persist in the United States. Our objective was to further examine rural-urban differences in cancer incidence and trends. We used the North American Association of Central Cancer Registries dataset to investigate rural-urban differences in 5-year age-adjusted cancer incidence (2015-2019) and trends (2000-2019), also examining differences by region, sex, race/ethnicity, and tumor site. Age-adjusted rates were calculated using SEER∗Stat 8.4.1, and trend analysis was done using Joinpoint, reporting annual percent changes (APC). We observed higher all cancer combined 5-year incidence rates in rural areas (457.6 per 100,000) compared with urban areas (447.9), with the largest rural-urban difference in the South (464.4 vs. 449.3). Rural populations also exhibited higher rates of tobacco-associated, human papillomavirus-associated, and colorectal cancers, including early-onset cancers. Tobacco-associated cancer incidence trends widened between rural and urban from 2000 to 2019, with significant, but varying, decreases in urban areas throughout the study period, whereas significant rural decreases only occurred between 2016 and 2019 (APC = -0.96). Human papillomavirus-associated cancer rates increased in both populations until recently with urban rates plateauing whereas rural rates continued to increase (e.g., APC = 1.56, 2002-2019). Rural populations had higher overall cancer incidence rates and higher rates of cancers with preventive opportunities compared with urban populations. Improvements in these rates were typically slower in rural populations. Our findings underscore the complex nature of rural-urban disparities, emphasizing the need for targeted interventions and policies to reduce disparities and achieve equitable health outcomes.

Small towns limit dispersal and reduce genetic diversity in populations of Texas horned lizards.

There is a general expectation that urban populations will be fragmented and the movement of individuals will be restricted leading to low effective population sizes, low genetic diversity, higher inbreeding, and higher differentiation than populations living in more continuous habitat. In this study, we compare the genetic diversity and differentiation of Texas horned lizards that are found in four small towns (Kenedy, Karnes City, Rockdale, and Smithville) in Texas and at Tinker Air Force Base, Oklahoma to populations that occur in 16 natural areas and to an introduced population in South Carolina. We also present more detailed spatial genetic data and home range data for several of the towns. Texas horned lizards (Phrynosoma cornutum) living in small towns have lower genetic diversity, higher differentiation, and smaller effective population sizes than populations located in more natural areas. There was evidence for human-mediated movement of lizards into town; however, it has not been enough to counteract the effects of drift. Home range size is smaller in town than in more natural areas. Genetic patterns suggest dispersal occurs over short distances and is inhibited across areas with a high percent of impervious surface and major roads. These data suggest that effective planning to maintain suitable habitat and corridors to facilitate movement is critical to maintaining small terrestrial species like the Texas horned lizard and must be integrated into the early stages of urban development.

Spatial Accessibility and Uptake of Pediatric COVID-19 Vaccinations by Social Vulnerability.

Geographic accessibility predicts pediatric preventive care utilization, including vaccine uptake. However, spatial inequities in the pediatric coronavirus disease 2019 (COVID-19) vaccination rollout remain underexplored. We assessed the spatial accessibility of vaccination sites and analyzed predictors of vaccine uptake. In this cross-sectional study of pediatric COVID-19 vaccinations from the US Vaccine Tracking System as of July 29, 2022, we described spatial accessibility by geocoding vaccination sites, measuring travel times from each Census tract population center to the nearest site, and weighting tracts by their population demographics to obtain nationally representative estimates. We used quasi-Poisson regressions to calculate incidence rate ratios, comparing vaccine uptake between counties with highest and lowest quartile Social Vulnerability Index scores: socioeconomic status (SES), household composition and disability (HCD), minority status and language (MSL), and housing type and transportation. We analyzed 15 233 956 doses administered across 27 526 sites. Rural, uninsured, white, and Native American populations experienced longer travel times to the nearest site than urban, insured, Hispanic, Black, and Asian American populations. Overall Social Vulnerability Index, SES, and HCD were associated with decreased vaccine uptake among children aged 6 months to 4 years (overall: incidence rate ratio 0.70 [95% confidence interval 0.60-0.81]; SES: 0.66 [0.58-0.75]; HCD: 0.38 [0.33-0.44]) and 5 years to 11 years (overall: 0.85 [0.77-0.95]; SES: 0.71 [0.65-0.78]; HCD: 0.67 [0.61-0.74]), whereas social vulnerability by MSL was associated with increased uptake (6 months-4 years: 5.16 [3.59-7.42]; 5 years-11 years: 1.73 [1.44-2.08]). Pediatric COVID-19 vaccine uptake and accessibility differed by race, rurality, and social vulnerability. National supply data, spatial accessibility measurement, and place-based vulnerability indices can be applied throughout public health resource allocation, surveillance, and research.

Decomposition Analysis of Depressive Symptom Differences Among Older Adults With Hypertension Between Urban and Rural Areas: Cross-Sectional Study.

Hypertension is the most prevalent chronic disease among China's older population, which comprises a growing proportion of the overall demographic. Older individuals with chronic diseases have a higher risk of developing depressive symptoms than their healthy counterparts, as evidenced in China's older population, where patients with hypertension exhibit varying rates of depression depending on residing in urban or rural areas. This study aimed to investigate factors influencing and contributing to the disparities in depressive symptoms among older urban and rural patients with hypertension in China. We used a cross-sectional study design and derived data from the 8th Chinese Longitudinal Health Longevity Survey of 2018. The Fairlie model was applied to analyze the factors contributing to disparities in depressive symptoms between urban and rural older populations with hypertension. The sample size for this study was 5210, and 12.8% (n=669) of participants exhibited depressive symptoms. The proportions of depressive symptoms in rural and urban areas were 14.1% (n=468) and 10.7% (n=201), respectively. In rural areas, years of education (1-6 years: odds ratio [OR] 0.68, 95% CI 1.10-1.21; ≥7 years: OR 0.47, 95% CI 0.24-0.94), alcohol consumption (yes: OR 0.52, 95% CI 0.29-0.93), exercise (yes: OR 0.78, 95% CI 0.56-1.08), and sleep duration (6.0-7.9 hours: OR 0.29, 95% CI 0.17-0.52; 8.0-9.9 hours: OR 0.24, 95% CI 0.13-0.43; ≥10.0 hours: OR 0.22, 95% CI 0.11-0.41) were protective factors against depressive symptoms in older adults with hypertension, while gender (female: OR 1.94, 95% CI 1.33-2.81), self-reported income status (poor: OR 3.07, 95% CI 2.16-4.37), and activities of daily living (ADL) dysfunction (mild: OR 1.69, 95% CI 1.11-2.58; severe: OR 3.03, 95% CI 1.46-6.32) were risk factors. In urban areas, age (90-99 years: OR 0.37, 95% CI 0.16-0.81; ≥100 years: OR 0.19, 95% CI 0.06-0.66), exercise (yes: OR 0.33, 95% CI 0.22-0.51), and sleep duration (6.0-7.9 hours: OR 0.27, 95% CI 0.10-0.71; 8.0-9.9 hours: OR 0.16, 95% CI 0.06-0.44; ≥10.0 hours: OR 0.18, 95% CI 0.06-0.57) were protective factors, while years of education (1-6 years: OR 1.91, 95% CI 1.05-3.49), self-reported income status (poor: OR 2.94, 95% CI 1.43-6.08), and ADL dysfunction (mild: OR 2.38, 95% CI 1.39-4.06; severe: OR 3.26, 95% CI 1.21-8.76) were risk factors. The Fairlie model revealed that 91.61% of differences in depressive symptoms could be explained by covariates, including years of education (contribution 63.1%), self-reported income status (contribution 13.2%), exercise (contribution 45.7%), sleep duration (contribution 20.8%), ADL dysfunction (contribution -9.6%), and comorbidities (contribution -22.9%). Older patients with hypertension in rural areas had more depressive symptoms than their counterparts residing in urban areas, which could be explained by years of education, self-reported income status, exercise, sleep duration, ADL dysfunction, and comorbidities. Factors influencing depressive symptoms had similarities regarding exercise, sleep duration, self-reported income status, and ADL dysfunction as well as differences regarding age, gender, years of education, and alcohol consumption.

Proximal humeral fractures with vascular compromise.

Vascular compromise due to arterial injury is a rare but serious complication of a proximal humeral fracture. The aims of this study were to report its incidence in a large urban population, and to identify clinical and radiological factors which are associated with this complication. We also evaluated the results of the use of our protocol for the management of these injuries. A total of 3,497 adult patients with a proximal humeral fracture were managed between January 2015 and December 2022 in a single tertiary trauma centre. Their mean age was 66.7 years (18 to 103) and 2,510 (72%) were female. We compared the demographic data, clinical features, and configuration of those whose fracture was complicated by vascular compromise with those of the remaining patients. The incidence of vascular compromise was calculated from national population data, and predictive factors for its occurrence were investigated using univariate analysis. A total of 18 patients (0.5%) had a proximal humeral fracture and clinical evidence of vascular compromise, giving an annual incidence of 0.29 per 100,000 of the population. Their mean age was 68.7 years (45 to 92) and ten (56%) were female. Evidence of a mixed pattern neurological deficit (brachial plexus palsy) (odds ratio (OR) 380.6 (95% CI 85.9 to 1,685.8); p < 0.001), complete separation of the proximal shaft from the humeral head with medial displacement (OR 39.5 (95% CI 14.0 to 111.8); p < 0.001), and a fracture-dislocation (OR 5.0 (95% CI 1.6 to 15.3); p = 0.015) were all associated with an increased risk of associated vascular compromise. A policy of reduction and fixation of the fracture prior to vascular surgical intervention had favourable outcomes without vascular sequelae. The classic signs of distal ischaemia are often absent in patients with proximal injuries to major vessels. We were able to identify specific clinical and radiological 'red flags' which, particularly when present in combination, should increase the suspicion of a fracture with an associated vascular injury, and facilitate early diagnosis and appropriate combined orthopaedic and vascular intervention.

The deviation characteristics and influencing factors of urban scaling laws in China: industrial and sectoral perspective

ABSTRACT When facing the complex and enormous system of cities, it is imperative to interpret urban development phenomena in a scientifically rigorous manner. Urban scaling laws describe the logarithmic relationship between the population size of a city and various systemic indicators, providing insights into the reasons behind urban population distribution patterns and scaling characteristics. While research related to urban scaling laws has garnered increasing attention, current studies often focus on revealing the relationships between urban size and economic, social, and infrastructural indicators, neglecting investigations into the relationships between population size and industrial sector indicators. Therefore, this study approaches the topic from the perspective of industries and sectors, employing methods such as ordinary least squares regression and comparative analysis to identify the deviation characteristics of urban scaling laws in China. Additionally, the XGBoost + Shap value modeling method is utilized to discern the factors influencing these deviations. The study findings indicate that from 1988 to 2019, China’s secondary industry scaling index exhibited superlinear growth, while the tertiary industry scaling index demonstrated linear growth, with significant differences observed across various industries. The range of deviation in China’s industry scaling index is relatively large. Among the variables considered, the growth rate of gross domestic product (GDP) exerts the strongest influence on the industry scaling index, followed by urbanization growth rate and urbanization rate. Factors such as population density, per capita national income, and the proportion of secondary industry to GDP also impact industry scaling indices. The research reveals disparities in urban development and suggests responses through urban policy interventions, thereby providing a basis for urban planning and policy formulation.

Groundwater Quality Assessment: A Case of Urban Population Demography and Nutrient Enrichment in Ibadan, Southwestern Nigeria

Groundwater Quality Assessment: A Case of Urban Population Demography and Nutrient Enrichment in Ibadan, Southwestern Nigeria

Wild raccoons demonstrate flexibility and individuality in innovative problem-solving.

Cognitive skills, such as innovative problem-solving, are hypothesized to aid animals in urban environments. However, the significance of innovation in wild populations, and its expression across individuals and socio-ecological conditions, is poorly understood. To identify how and when innovation arises in urban-dwelling species, we used advanced technologies and new testing and analytical methods to evaluate innovative problem-solving abilities of wild raccoons (Procyon lotor). We deployed multi-compartment puzzle boxes with either one or multiple solution types and identified raccoons using radio frequency identification. Raccoons solved these novel extractive foraging tasks, and their success was influenced by age and exploratory diversity. Successful raccoons always discovered multiple different solution types, highlighting flexible problem-solving. Using a unique, comparative sequence analysis approach, we found that variation in raccoon solving techniques was greater between individuals than within individuals, and this self-similarity intensified during times of competition. Finally, the inclusion of an easier solution in the multi-solution trials enabled previously unsuccessful raccoons to bootstrap their learning and successfully open multiple difficult solutions. Our study suggests that innovative problem-solving is probably influenced by many factors and has provided novel field and analytical methods, as well as new insights on the socio-ecological dynamics of urban populations.

Assessment of Chinese urban land-use efficiency (SDG11.3.1) utilizing high-precision urban built-up area data

Assessment of SDG11.3.1 indicator of the United Nations Sustainable Development Goals (SDGs) is a valuable tool for policymakers in urban planning. This study aims to enhance the accuracy of the SDG11.3.1 evaluation and explore the impact of varying precision levels in urban built-up area on the indicator's assessment outcomes. We developed an algorithm to generate accurate urban built-up area data products based on China's Geographical Condition Monitoring data with a 2 m resolution. The study evaluates urban land-use efficiency in China from 2015 to 2020 across different geographical units using both the research product and data derived from other studies utilizing medium and low-resolution imagery. The results indicate: (1) A significant improvement in the accuracy of our urban built-up area data, with the SDG11.3.1 evaluation results demonstrating a more precise reflection of spatiotemporal characteristics. The indicator shows a positive correlation with the accuracy level of the built-up area data; (2) From 2015 to 2020, Chinese prefecture-level cities have undergone faster urbanization in terms of land expansion relative to population growth, leading to less optimal land resource utilization. Only in extra-large cities does urban population growth show a relatively balanced pattern. However, urban population growth in other regions and cities of various sizes lags behind land urbanization. Notably, Northeast China and small to medium cities encounter significant challenges in urban population growth. Our comprehensive framework for evaluating SDG11.3.1 with high-precision urban built-up area data can be adapted to different national regions, yielding more accurate SDG11.3.1 outcomes. Our urban area and built-up area data products provide crucial inputs for calculating at least four indicators related to SDG11.