The city nature challenge: A global citizen science phenomenon contributing to biodiversity knowledge and informing local government practices.

The bioblitz phenomenon has recently branched into cities, presenting exciting opportunities for local governments to channel participants' efforts toward local issues. The City Nature Challenge (CNC) is one such initiative that has been quickly taken up by hundreds of municipalities worldwide. Despite high levels of participation, we still lack a framework for evaluating how the CNC contributes to local biodiversity knowledge and to inform local government practices. In the present article, we develop such a tool and present a case study that illustrates its applicability. We demonstrate that the collected records contributed to a better understanding of contemporary, local biodiversity patterns and provide a more realistic representation of understudied groups such as insects and fungi. Importantly, we show that the CNC presented local governments with a cost-effective tool to make informed, evidence-based management and policy decisions, improve education and engagement programs, foster cross-council collaborations, and support a stronger sense of environmental stewardship within the local community.

Allopolyploidy enhances survival advantages for urban environments in the native plant genus Commelina.

BACKGROUND AND AIMS: Urbanization-induced environmental changes affect the geographical distribution of natural plant species. This study focused on how polyploidization, a dynamic genome change, influences the survival and distribution of Commelina communis L. (Cc) and its subspecies, C. communis f. ciliata (Masam.) Murata (Ccfc) which have different chromosome numbers (e.g. Cc: 2n = 88, Ccfc: 2n = 46). The aim is to investigate polyploidization effects on natural plant distribution in urban environments. METHODS: The geographical distribution across urban-rural gradients was investigated at a total of 218 sites in Japan. Stomata size and density were measured and compared between Cc and Ccfc. Flow cytometry determined genome size and polyploidy. Chromosome karyotyping was performed using genomic in situ hybridization (GISH) method. KEY RESULTS: Urban areas were exclusively dominated by Cc, while Cc and Ccfc coexisted in rural areas. Cc had larger and fewer stomata and more than twice the genome size than Ccfc. GISH results indicated that Cc possesses Ccfc and another unknown genome, suggesting allopolyploidy. CONCLUSIONS: Our results show that the ploidy difference affects the geographical distribution, the stomata traits, and genome size between two distinct taxa in the genus Commelina, C. communis as a neo-tetraploid and C. communis f. ciliata, the diploid. Cc is an allopolyploid, therefore, not only polyploidy but also an additional genome with new sets of genes and alleles contributes to Cc having enhance survival potentials in urban environments compared to Ccfc. This is the first investigation to clarify the distribution difference related to urban environments, the difference in stomata traits and genome size, and to conduct chromosome composition in Commelina species.

Assessing the Impact of Urban Environments on Mental Health and Perception Using Deep Learning: A Review and Text Mining Analysis.

Understanding how outdoor environments affect mental health outcomes is vital in today's fast-paced and urbanized society. Recently, advancements in data-gathering technologies and deep learning have facilitated the study of the relationship between the outdoor environment and human perception. In a systematic review, we investigate how deep learning techniques can shed light on a better understanding of the influence of outdoor environments on human perceptions and emotions, with an emphasis on mental health outcomes. We have systematically reviewed 40 articles published in SCOPUS and the Web of Science databases which were the published papers between 2016 and 2023. The study presents and utilizes a novel topic modeling method to identify coherent keywords. By extracting the top words of each research topic, and identifying the current topics, we indicate that current studies are classified into three areas. The first topic was "Urban Perception and Environmental Factors" where the studies aimed to evaluate perceptions and mental health outcomes. Within this topic, the studies were divided based on human emotions, mood, stress, and urban features impacts. The second topic was titled "Data Analysis and Urban Imagery in Modeling" which focused on refining deep learning techniques, data collection methods, and participants' variability to understand human perceptions more accurately. The last topic was named "Greenery and visual exposure in urban spaces" which focused on the impact of the amount and the exposure of green features on mental health and perceptions. Upon reviewing the papers, this study provides a guide for subsequent research to enhance the view of using deep learning techniques to understand how urban environments influence mental health. It also provides various suggestions that should be taken into account when planning outdoor spaces.

Blood meal sources of mosquitoes (Diptera: Culicidae) in domestic and open green environments from two urbanisations of temperate Argentina.

Understanding the blood-feeding patterns of mosquitoes is essential for evaluating their potential as disease vectors, especially in urban areas where mosquitoes coexist with humans, domestic animals and wildlife. This study aimed to bridge a substantial gap in regional knowledge by identifying the blood meal sources of field-collected mosquitoes in domestic and open green environments from two urbanisations of temperate Argentina, the Área Metropolitana de Buenos Aires (AMBA) and Tandil, using molecular techniques. Female mosquitoes were collected from November 2019 to March 2020 and April-May 2021. A bipartite network analysis was performed for each environment and urbanisation. A total of 103 blood meals from Aedes (2 species) and Culex (7 species) were identified. Among these, five mammal and 18 bird species were recognised as hosts. Aedes mosquitoes exclusively fed on mammals, while Culex mosquitoes exhibited a broader host range including both birds and mammals. In AMBA, the open green environments were composed by more mosquito species than the domestic environments, while both presented similar numbers of vertebrate species. In contrast, in open green environments from Tandil only blood-fed Aedes albifasciatus were collected. For open green environments of AMBA and domestic environments of Tandil, results suggested some degree of host selection. For the three main vectors of diseases in the region, Aedes aegypti, Ae. albifasciatus and Culex pipiens molestus, we present the first molecular evidence of human blood meals in South America. Epidemiological significance of the present findings is discussed.

Gender, race, and space: A qualitative exploration of young Black women's perceptions of urban neighborhoods.

How people think and feel about their neighborhood impacts the way they think of themselves and their futures. These linkages are especially important to understand in the case of urban-residing young Black women. Researchers know very little about what contributes to young Black adults' urban neighborhood perceptions and often rely on "expert" definitions of markers of neighborhood quality. These definitions and subsequent explorations of residents' neighborhood assessment have not adequately considered intersecting oppressive systems that structure urban spaces both physically and socially. Further, within-group diversity of young Black adults based on other social identities, such as gender and class, has gone underexplored in research on residents' neighborhood assessment. We used theory from Black feminist geography and sociology to guide our thematic analysis of interviews with young Black women (N = 9) regarding their urban neighborhood quality. We sought to explore the aspects or features of the neighborhood that young Black women discussed and how social identities may play a role in young Black women's descriptions of their urban neighborhoods. We argue three themes tell an overarching story of young Black women's urban spatial critical analysis: (1) outsiders' perceptions versus our realities, (2) gendered safety, and (3) visibility of young Black women. Young Black women's narratives highlighted communal aspects of neighborhood evaluation and attention to dominant narratives regarding marginalized groups and urban spaces.

Influence of Neighborhood Built Environments on the Outdoor Free Play of Young Children: a Systematic, Mixed-Studies Review and Thematic Synthesis.

Urban environments shape early childhood exposures, experiences, and health behaviors, including outdoor free play, influencing the physical, cognitive, social, and emotional development of young children. We examined evidence for urban or suburban built environment influences on outdoor free play in 0-6-year-olds, considering potential differences across gender, culture, and geography. We systematically searched seven literature databases for relevant qualitative, quantitative, and mixed methods studies: of 5740 unique studies, 53 met inclusion criteria. We assessed methodological quality and thematically synthesized findings from included studies. Three broad themes, features of spaces for play, routes, and social factors intersected to influence the availability, accessibility, and acceptability of neighborhoods for young children's outdoor free play across diverse cultural and geographic contexts. Proximity to formal or informal space for play, protection from traffic, pedestrian environment, green and natural environments, and opportunity for social connection supported outdoor free play. Family and community social context influenced perceptions of and use of space; however, we did not find consistent, gendered differences in built environment correlates of outdoor free play. Across diverse contexts, playable neighborhoods for young children provided nearby space for play, engaging routes protected from traffic and facilitated frequent interaction between people, nature, and structures.

The short term adaptation of the autonomic nervous systems (ANS) by type of urban environment and ethnicity.

BACKGROUND: Previous studies examined the effects of urban environments on the Autonomic Nervous System (ANS). These studies measured the effects of environments on Heart Rate Variability (HRV) averaging different time intervals to one value. Yet, the dynamics of change, reflecting the functions and their derivatives that describe the adaptation to the new environments remain unknown. In addition, ethnic differences in the ANS adaptation were not investigated. METHOD: Forty-eight Arab and 24 Jewish women ages 20-35 years, all healthy, non-smokers were recruited by a snowball sample. Both groups were of a similar socioeconomic status and BMI distributions. Using a portable monitor, the HRV response was continuously analyzed for 35 min of sedentary sitting in each of the three environments: a park, a city center and a residential area. LF/HF polynomial function was adapted to describe the dynamic change in each environment for each ethnic group. RESULTS: Green area exposure was associated with 90% immediate change while in built-up areas, the change in HRV is about 40% adaptive (changing gradually). The adaptive process of HRV may stabilize after 15 min in the city center yet not even after 35 min in the residential environment. The total change (immediate + adaptive) reached 24% in city centers and 10% in residential areas. Changes in HRV rates in the park and the city center environments were higher among Arab women as compared to Jewish women but similar between the two groups in the residential area. The distributions of LF/HF in each time cohort were normal, meaning that shifting the focus to analyze functions of change in HRV, opens the possibility to employ analytic methods that assume the normal distribution. CONCLUSIONS: Changing the focus from average levels of HRV to functions of change and their derivatives brings new insight into the understanding of the ANS response to environmental challenges. ANS short term adaptation to different environments is gradual and spans differently both in magnitude of response and latencies between different environments. Importantly, in green areas, the response is immediate unlike the adaptation to urban environments that is significantly more gradual. The ethnic differences in ANS adaptation is also noteworthy. In addition, adaptation proceeesses are normaly distributed in each time cohort suggesting a possible novel ANS index.

Functional Objects in Urban Walking Environments and Pedestrian Trajectory Modelling.

Functional objects are large and small physical entities installed in urban environments to offer specific functionalities to visitors, such as shops, escalators, and information kiosks. Instances of the novel notion are focal points of human activities and are significant in pedestrian movement. Pedestrian trajectory modelling in an urban scene is a challenging problem because of the complex patterns resulting from social interactions of the crowds and the diverse relation between pedestrians and functional objects. Many data-driven methods have been proposed to explain the complex movements in urban scenes. However, the methods considering functional objects in their formulation are rare. This study aims to reduce the knowledge gap by demonstrating the importance of pedestrian-object relations in the modelling task. The proposed modelling method, called pedestrian-object relation guided trajectory prediction (PORTP), uses a dual-layer architecture that includes a predictor of pedestrian-object relation and a series of relation-specific specialized pedestrian trajectory prediction models. The experiment findings indicate that the inclusion of pedestrian-object relation results in more accurate predictions. This study provides an empirical foundation for the novel notion and a strong baseline for future work on this topic.

Impact of COVID-19 Restrictions on the Urban Thermal Environment of Edmonton, Canada.

The effects of the COVID-19 pandemic on urban environments are addressed in many recent studies. However, limited research has been conducted to examine the impact of the pandemic on anthropogenic emissions over urban land use types, and their relation to socioeconomic characteristics. Anthropogenic heat, as the main contributor to the urban temperature, is changed by the sudden halt imposed by COVID-19 lockdowns. This study thus focuses on previously under-explored urban thermal environments by quantifying the impact of COVID-19 on urban thermal environments across different land-use types and related socioeconomic drivers in Edmonton, Canada. Using Landsat images, we quantified and mapped the spatial pattern of land surface temperature (LST) for business, industrial, and residential land use areas during both the pandemic lockdown and pre-pandemic periods in the study area. Results show that temperature declined in business and industrial areas and increased in residential areas during the pandemic lockdown. Canadian census and housing price data were then used to identify the potential drivers behind the LST anomaly of residential land use. The most important variables that affected LST during the lockdown were found to be median housing price, visible minority population, postsecondary degree, and median income. This study adds to the expanding body of literature about the impact of the COVID-19 pandemic by providing unique insights into the effect of lockdown on a city's thermal environments across different land use types and highlights critical issues of socioeconomic inequalities, which is useful for future heat mitigating and health equity-informed responses.

Route effects in city-based survey knowledge estimates.

When studying wayfinding in urban environments, researchers are often interested in obtaining measures of participants' survey knowledge, i.e., their estimate of distant locations relative to other places. Previous work showed that distance estimations are consistently biased when no direct route is available to the queried target or when participants follow a detour. Here we investigated whether a corresponding bias is manifested in two other popular measures of survey knowledge: a pointing task and a sketchmapping task. The aim of this study was to investigate whether there is a systematic bias in pointing/sketchmapping performance associated with the preferred route choice in an applied urban setting. The results were mixed. We found moderate evidence for the presence of a systematic bias, but only for a subset of urban locations. When two plausible routes to the target were available, survey knowledge estimates were significantly biased in the direction of the route chosen by the participant. When only one plausible route was available, we did not find a statistically significant pattern. The results may have methodological implications for spatial cognition studies in applied urban settings that might be obtaining systematically biased survey knowledge estimates at some urban locations. Researchers should be aware that the choice of urban locations from which pointing and sketchmapping are performed might systematically distort the results, in particular when two plausible but diverging routes to the target are visible from the location.

High ambient temperature and child emergency and hospital visits in New York City.

BACKGROUND: Emerging literature has documented heat-related impacts on child health, yet few studies have evaluated the effects of heat among children of different age groups and comparing emergency department (ED) and hospitalisation risks. OBJECTIVES: To examine the differing associations between high ambient temperatures and risk of ED visits and hospitalisations among children by age group in New York City (NYC). METHODS: We used New York Statewide Planning and Research Cooperative System (SPARCS) data on children aged 0-18 years admitted to NYC EDs (n = 2,252,550) and hospitals (n = 228,006) during the warm months (May-September) between 2005 and 2011. Using a time-stratified, case-crossover design, we estimated the risk of ED visits and hospitalisations associated with daily maximum temperature (Tmax) for children of all ages and by age group. RESULTS: The average Tmax over the study period was 80.3°F (range 50°, 104°F). Tmax conferred the greatest risk of ED visits for children aged 0-4, with a 6-day cumulative excess risk of 2.4% (95% confidence interval [CI] 1.7, 3.0) per 13°F (ie interquartile range) increase in temperature. Children and adolescents 5-12 years (0.8%, 95% CI 0.1, 1.6) and 13-18 years (1.4%, 95% CI 0.6, 2.3) are also sensitive to heat. For hospitalisations, only adolescents 13-18 years had increased heat-related risk, with a cumulative excess risk of 7.9% (95% CI 2.0, 14.2) per 13°F increase in Tmax over 85°F. CONCLUSIONS: This urban study in NYC reinforces that young children are particularly vulnerable to effects of heat, but also demonstrates the sensitivity of older children and adolescents as well. These findings underscore the importance of focussing on children and adolescents in targeting heat illness prevention and emergency response activities, especially as global temperatures continue to rise.

Insufficient Condensable Organic Vapors Lead to Slow Growth of New Particles in an Urban Environment.

Atmospheric new particle formation significantly affects global climate and air quality after newly formed particles grow above ∼50 nm. In polluted urban atmospheres with 1-3 orders of magnitude higher new particle formation rates than those in clean atmospheres, particle growth rates are comparable or even lower for reasons that were previously unclear. Here, we address the slow growth in urban Beijing with advanced measurements of the size-resolved molecular composition of nanoparticles using the thermal desorption chemical ionization mass spectrometer and the gas precursors using the nitrate CI-APi-ToF. A particle growth model combining condensational growth and particle-phase acid-base chemistry was developed to explore the growth mechanisms. The composition of 8-40 nm particles during new particle formation events in urban Beijing is dominated by organics (∼80%) and sulfate (∼13%), and the remainder is from base compounds, nitrate, and chloride. With the increase in particle sizes, the fraction of sulfate decreases, while that of the slow-desorbed organics, organic acids, and nitrate increases. The simulated size-resolved composition and growth rates are consistent with the measured results in most cases, and they both indicate that the condensational growth of organic vapors and H2SO4 is the major growth pathway and the particle-phase acid-base reactions play a minor role. In comparison to the high concentrations of gaseous sulfuric acid and amines that cause high formation rates, the concentration of condensable organic vapors is comparably lower under the high NOx levels, while those of the relatively high-volatility nitrogen-containing oxidation products are higher. The insufficient condensable organic vapors lead to slow growth, which further causes low survival of the newly formed particles in urban environments. Thus, the low growth rates, to some extent, counteract the impact of the high formation rates on air quality and global climate in urban environments.

Unified DeepLabV3+ for Semi-Dark Image Semantic Segmentation.

Semantic segmentation for accurate visual perception is a critical task in computer vision. In principle, the automatic classification of dynamic visual scenes using predefined object classes remains unresolved. The challenging problems of learning deep convolution neural networks, specifically ResNet-based DeepLabV3+ (the most recent version), are threefold. The problems arise due to (1) biased centric exploitations of filter masks, (2) lower representational power of residual networks due to identity shortcuts, and (3) a loss of spatial relationship by using per-pixel primitives. To solve these problems, we present a proficient approach based on DeepLabV3+, along with an added evaluation metric, namely, Unified DeepLabV3+ and S3core, respectively. The presented unified version reduced the effect of biased exploitations via additional dilated convolution layers with customized dilation rates. We further tackled the problem of representational power by introducing non-linear group normalization shortcuts to solve the focused problem of semi-dark images. Meanwhile, to keep track of the spatial relationships in terms of the global and local contexts, geometrically bunched pixel cues were used. We accumulated all the proposed variants of DeepLabV3+ to propose Unified DeepLabV3+ for accurate visual decisions. Finally, the proposed S3core evaluation metric was based on the weighted combination of three different accuracy measures, i.e., the pixel accuracy, IoU (intersection over union), and Mean BFScore, as robust identification criteria. Extensive experimental analysis performed over a CamVid dataset confirmed the applicability of the proposed solution for autonomous vehicles and robotics for outdoor settings. The experimental analysis showed that the proposed Unified DeepLabV3+ outperformed DeepLabV3+ by a margin of 3% in terms of the class-wise pixel accuracy, along with a higher S3core, depicting the effectiveness of the proposed approach.

Field Evaluation and Calibration of Low-Cost Air Pollution Sensors for Environmental Exposure Research.

This paper seeks to evaluate and calibrate data collected by low-cost particulate matter (PM) sensors in different environments and using different aggregated temporal units (i.e., 5-s, 1-min, 10-min, 30 min intervals). We first collected PM concentrations (i.e., PM1, PM2.5, and PM10) data in five different environments (i.e., indoor and outdoor of an office building, a train platform and lobby of a subway station, and a seaside location) in Hong Kong, using five AirBeam2 sensors as the low-cost sensors and a TSI DustTrak DRX Aerosol Monitor 8533 as the reference sensor. By comparing the collected PM concentrations, we found high linearity and correlation between the data reported by the AirBeam2 sensors in different environments. Furthermore, the results suggest that the accuracy and bias of the PM data reported by the AirBeam2 sensors are affected by rainy weather and environments with high humidity and a high level of hygroscopic salts (i.e., a seaside location). In addition, increasing the aggregation level of the temporal units (i.e., from 5-s to 30 min intervals) increases the correlation between the PM concentrations obtained by the AirBeam2 sensors, while it does not significantly improve the accuracy and bias of the data. Lastly, our results indicate that using a machine learning model (i.e., random forest) for the calibration of PM concentrations collected on sunny days generates better results than those obtained with multiple linear models. These findings have important implications for researchers when designing environmental exposure studies based on low-cost PM sensors.

Assessment of doses in contaminated urban areas: modelling exercise based on Fukushima data.

State-of-the-art dose assessment models were applied to estimate doses to the population in urban areas contaminated by the Fukushima Daiichi Nuclear Power Plant accident. Assessment results were compared among five models, and comparisons of model predictions with actual measurements were also made. Assessments were performed using both probabilistic and deterministic approaches. Predicted dose distributions for indoor and outdoor workers from a probabilistic approach were in good agreement with the actual measurements. In addition, when the models were applied to assess the doses to the representative person, based on a concept recommended by the International Commission on Radiological Protection and in the International Atomic Energy Agency Safety Standards, it was evident that doses to the representative person obtained with a deterministic approach were always higher than those obtained with a probabilistic approach using the same model.

Urban working groups in the IAEA's model testing programmes: overview from the MODARIA I and MODARIA II programmes.

The IAEA's model testing programmes have included a series of Working Groups concerned with modelling radioactive contamination in urban environments. These have included the Urban Working Group of Validation of Environmental Model Predictions (1988-1994), the Urban Remediation Working Group of Environmental Modelling for Radiation Safety (EMRAS) (2003-2007), the Urban Areas Working Group of EMRAS II (2009-2011), the Urban Environments Working Group of (Modelling and Data for Radiological Impact Assessments) MODARIA I (2013-2015), and most recently, the Urban Exposures Working Group of MODARIA II (2016-2019). The overarching objective of these Working Groups has been to test and improve the capabilities of computer models used to assess radioactive contamination in urban environments, including dispersion and deposition processes, short-term and long-term redistribution of contaminants following deposition events, and the effectiveness of various countermeasures and other protective actions, including remedial actions, in reducing contamination levels, human exposures, and doses to humans. This paper describes the exercises conducted during the MODARIA I and MODARIA II programmes. These exercises have included short-range and mid-range atmospheric dispersion exercises based on data from field tests or tracer studies, hypothetical urban dispersion exercises, and an exercise based on data collected after the Fukushima Daiichi accident. Improvement of model capabilities will lead to improvements in assessing various contamination scenarios (real or hypothetical), and in turn, to improved decision-making and communication with the public following a nuclear or radiological emergency.

Combustion by-products and their health effects: Summary of the 16th international congress.

The 16th International Congress on Combustion By-Products and their Health Effects (PIC2019) was held in Ann Arbor, Michigan, from July 10 to 12, 2019. For the last 28 years, this conference has served as an interdisciplinary platform for the discussion of the formation, environmental fate, health effects, policy, and remediation of combustion by-products. The technical areas for PIC2019 included mobile and stationary sources in urban environments, open fires, indoor air pollution, and halogenated pollutants. The congress was sponsored by the National Institute of Environmental Health Sciences (NIEHS), the U.S. EPA, the School of Public Health at the University of Michigan, the Civil and Environmental Engineering Department at the University of Michigan, the Mechanical Engineering Department at the University of Michigan, the Aerospace Engineering Department at the University of Michigan, and the Climate and Space Sciences and Engineering Department at the University of Michigan. Special features of the conference included a career path and round table discussion on translating research and engaging communities.

There's no place like home? The psychological, physiological, and cognitive effects of short visits to outdoor urban environments compared to staying in the indoor home environment, a field experiment on women from two ethnic groups.

BACKGROUND: The home environment is regarded as a safe, comfortable environment, however, home can also be a stressful place. Compared to staying in the indoor home environment, the effects of short visits to outdoor urban environments on short-term psychological, physiological and cognitive responses were not studied previously. AIM: To evaluate whether visits to different urban and ethnic environments, in comparison to staying in the home indoor environment, leads to short-term changes in psychological, physiological and cognitive responses and whether these responses are independent of ethnicity. METHODS: The participants, 20-35 year-old healthy women (N = 72, 48 Arab and 24 Jewish), started the experiment at their home and visited six different outdoor urban environments in predominantly ethnic Arab or Jewish cities, in Israel. First they visited intra-ethnic city and afterward inter-ethnic city environments. In each city they first visited an urban park and afterward, in a random order, a residential neighborhood and the city center. In each environment (including home) the following measures were used to evaluate psychological, physiological and cognitive effects: mood (measured as positive and negative emotions, cheerfulness, relaxed, natural and discomfort feelings), autonomic nervous system balance (assessed using heart rate variability (HRV)) and working memory (measured by a backwards digit-span task). Several potential mediators were measured: carbon monoxide (CO), heat, noise, social aspects, and the self-perceived restoration scale. RESULTS: Compared to staying in the indoor home environment, short visits to outdoor urban environments, specifically intra and inter-ethnic parks, were associated with beneficial psychological, physiological, and cognitive responses, and the strongest effects were found for the intra-ethnic park. The results for the other urban environments were different between Jewish and Arab women. The self-perceived restoration, social aspects and reduced CO, heat and noise exposures during the visits did not explain the observed changes between the outdoor environments and home. CONCLUSIONS: Visits to urban parks compared to staying in the home environment had beneficial short-term changes in psychological, physiological, and cognitive responses, regardless of ethnicity. The changes could not be attributed to the investigated mediators. Women should be encouraged to go outdoors and specifically visit parks to improve their psychological and physiological health.

An SVM Based Weight Scheme for Improving Kinematic GNSS Positioning Accuracy with Low-Cost GNSS Receiver in Urban Environments.

High-precision positioning with low-cost global navigation satellite systems (GNSS) in urban environments remains a significant challenge due to the significant multipath effects, non-line-of-sight (NLOS) errors, as well as poor satellite visibility and geometry. A GNSS system is typically implemented with a least-square (LS) or a Kalman-filter (KF) estimator, and a proper weight scheme is vital for achieving reliable navigation solutions. The traditional weight schemes are based on the signal-in-space ranging errors (SISRE), elevation and C/N0 values, which would be less effective in urban environments since the observation quality cannot be fully manifested by those values. In this paper, we propose a new multi-feature support vector machine (SVM) signal classifier-based weight scheme for GNSS measurements to improve the kinematic GNSS positioning accuracy in urban environments. The proposed new weight scheme is based on the identification of important features in GNSS data in urban environments and intelligent classification of line-of-sight (LOS) and NLOS signals. To validate the performance of the newly proposed weight scheme, we have implemented it into a real-time single-frequency precise point positioning (SFPPP) system. The dynamic vehicle-based tests with a low-cost single-frequency u-blox M8T GNSS receiver demonstrate that the positioning accuracy using the new weight scheme outperforms the traditional C/N0 based weight model by 65.4% and 85.0% in the horizontal and up direction, and most position error spikes at overcrossing and short tunnels can be eliminated by the new weight scheme compared to the traditional method. It also surpasses the built-in satellite-based augmentation systems (SBAS) solutions of the u-blox M8T and is even better than the built-in real-time-kinematic (RTK) solutions of multi-frequency receivers like the u-blox F9P and Trimble BD982.

Ecosystem Services and Economic Assessment of Land Uses in Urban and Periurban Areas.

This work quantified ecosystem services (ES) and the geographic gross product (GGP) at municipal level in the Metropolitan Region of Buenos Aires (MRBA), Argentina. The ES offer and GGP were evaluated for each land use (extensive agriculture EA, intensive agriculture IA, urban and periurban agriculture UPA, green areas GA, urban use URB), expressed as a percentage (%), at the municipality level. Municipalities with a greater URB percentage (<70) presented an elevated ES offer from GA. In periurban municipalities EA contributed to ES offer more than other vegetated land uses (IA, GA, and UPA). Urban municipalities presented 20% more GGP than periurban municipalities. The GGP was negatively associated with total ES offer (-0.34) and ES offer from EA (-0.46). The identification and quantification of ES and GGP is relevant for achieving an adequate landscape planning and a sustainable environmental and economic use of urban systems.