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The article discusses the impact of teleworking during the COVID-19 pandemic on families residing in the North Lisbon Metropolitan Area, Portugal. The study identified that the option for teleworking is not unanimous among the interviewees and highlighted challenges related to time management, work-life balance, perception of productivity, and improvement of mental and environmental health. The increase in teleworking during the pandemic raises concerns about labor rights and conditions, but also offers the possibility of organizing daily life in a more sustainable and closer-to-home manner. The study analyzes the impact of teleworking on daily commutes of families in Portugal and highlights concerns about workers' mental health and the challenges of balancing professional and personal life. Further studies are needed to assess the preference for the hybrid work model and analyze the impacts on families and work and family planning policies. [Extracted from the article]

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Physical activity, as a health determinant related to habits and lifestyles, is an important element in influencing the health status of populations. Thus, it is relevant to observe how it is included in family daily life and how families relate to places of practice. The literature shows the relationship between physical activity and health, socioeconomic conditions, space, and time. The objective of this study is to identify which factors condition the practice of physical activity, trying to verify if proximity to public spaces, equipment and sports and leisure services accessible by pedestrian mode can stimulate the integration of this practice within the framework of daily family activities. This analysis has as a case study the parish of Rio de Mouro (Sintra), in the Lisbon Metropolitan Area, Portugal. The methods included the collection of information on public spaces and recreational and leisure activities and a household survey to verify the residents' practices linking them with socioeconomic conditions and proximity to services. The results show that the population practicing physical activity constitutes a minority, a situation that arises from several factors: socioeconomic factors, the extent of commuting and working hours and the composition of the household, with evidence for differences between households with or without minors. The most controversial result is the verification that the use of a car in daily life is fundamental for the practice of physical activity since it allows the realization of more activities by families in the same available time. [ABSTRACT FROM AUTHOR]

The relevance of air pollution in the public health agenda has recently been reinforced—it is known that exposure to it has negative effects in the health of individuals, especially in big cities and metropolitan areas. In this article we observed the evolution of air pollutants (CO, NO, NO2, O3, PM10) emissions and we confront them with health vulnerabilities related to respiratory and circulatory diseases (all circulatory diseases, cardiac diseases, cerebrovascular disease, ischemic heart disease, all respiratory diseases, chronic lower respiratory diseases, acute upper respiratory infections). The study is supported in two databases, one of air pollutants and the other of emergency hospital admissions, in the 2005–2015 period, applied to the Lisbon Metropolitan Area. The analysis was conducted through Ordinary Least Squares (OLS) regression, while also using semi-elasticity to quantify associations. Results showed positive associations between air pollutants and admissions, tendentially higher in respiratory diseases, with CO and O3 having the highest number of associations, and the senior age group being the most impacted. We concluded that O3 is a good predictor for the under-15 age group and PM10 for the over-64 age group; also, there seems to exist a distinction between the urban city core and its suburban areas in air pollution and its relation to emergency hospital admissions. [ABSTRACT FROM AUTHOR]

The process of spreading the virus across countries and regions around the world, highlights the importance of geography in interpreting the phenomena. This article aims to identify the evolution of the phenomena in Portugal, between March and April, seeking to relate this pattern to the demographic and socio-economic characteristics of the territory. The diffusion process starts by the metro areas and other densely urbanised territories, follows to boarder areas and finally went to ageing and less dense territories. [ABSTRACT FROM AUTHOR]

The spatial monitoring of plant diversity in the endangered species-rich grasslands of European mountain pastoral systems is an important step for fairer and more efficient Agri-Environmental policy schemes supporting conservation. This study assessed the underlying support for a spatially explicit monitoring of plant species richness at parcel level (policy making scale) in Southern European mountain grasslands, with statistical models informed by Sentinel-2 satellite and environmental factors. Twenty-four grassland parcels were surveyed for species richness in the Peneda-Gerês National Park, northern Portugal. Using a multi-model inference approach, three competing hypotheses guided by the species-scaling theoretical framework were established: species–area (P1), species–energy (P2) and species–spectral heterogeneity (P3), each representing a candidate spatial pathway to predict species richness. To evaluate the statistical support of each spatial pathway, generalized linear models were fitted and model selection based on Akaike information criterion (AIC) was conducted. Later, the performance of the most supported spatial pathway(s) was assessed using a leave-one-out cross validation. A model guided by the species–energy hypothesis (P2) was the most parsimonious spatial pathway to monitor plant species richness in mountain grassland parcels (P2, AICc = 137.6, ∆AIC = 0.0, wi = 0.97). Species–area and species–spectral heterogeneity pathways (P1 and P3) were less statistically supported (ΔAICc values in the range 5.7–10.0). The underlying support of the species–energy spatial pathway was based on Sentinel-2 satellite data, namely on the near-infrared (NIR) green ratio in the spring season (NIR/Greenspring) and on its ratio of change between spring and summer (NIR/Greenchange). Both predictor variables related negatively to species richness. Grassland parcels with lower values of near-infrared (NIR) green ratio and lower seasonal amplitude presented higher species richness records. The leave-one-out cross validation indicated a moderate performance of the species–energy spatial pathway in predicting species richness in the grassland parcels covered by the dataset (R2 = 0.44, RMSE = 4.3 species, MAE = 3.5 species). Overall, a species–energy framework based on Sentinel 2 data resulted in a promising spatial pathway for the monitoring of species richness in mountain grassland parcels and for informing decision making on Agri-Environmental policy schemes. The near-infrared (NIR) green ratio and its change in time seems a relevant variable to deliver predictions for plant species richness and further research should be conducted on that. [ABSTRACT FROM AUTHOR]

• We modelled vegetation and soil moisture content with Sentinel-1 and 2 satellite data. • The hypothesis of a universal landscape model for VMC and SMC was not supported. • Vegetation type models showed promise for VMC in shrubland conditions. • The combination of Sentinel optical and radar data improved model performance. • The relationships between satellite predictors and VMC and SMC varied with time. The satellite monitoring of vegetation moisture content (VMC) and soil moisture content (SMC) in Southern European Atlantic mountains remains poorly understood but is a fundamental tool to better manage landscape moisture dynamics under climate change. In the Atlantic humid mountains of Portugal, we investigated an empirical model incorporating satellite (Sentinel-1 radar, S1; Sentinel-2 optical, S2) and ancillary predictors (topography and vegetation cover type) to monitor VMC (%) and SMC (%). Predictors derived from the S1 (VV, HH and VV/HH) and S2 (NDVI and NDMI) are compared to field measurements of VMC (n = 48) and SMC (n = 48) obtained during the early, mid and end of summer. Linear regression modelling was applied to uncover the feasibility of a landscape model for VMC and SMC, the role of vegetation type models (i.e. native forest, grasslands and shrubland) to enhance predictive capacity and the seasonal variation in the relationships between satellite predictors and VMC and SMC. Results revealed a significant but weak relationship between VMC and predictors at landscape level (R2 = 0.30, RMSEcv = 69.9 %) with S2_NDMI and vegetation cover type being the only significant predictors. The relationship improves in vegetation type models for grasslands (R2 = 0.35, RMSEcv = 95.0 % with S2_NDVI) and shrublands conditions (R2 = 0.52, RMSEcv = 45.3 %). A model incorporating S2_NDVI and S1_VV explained 52 % of the variation in VMC in shrublands. The relationship between SMC and satellite predictors at the landscape level was also weak, with only the S2_NDMI and vegetation cover type exhibiting a significant relationship (R2 = 0.28, RMSEcv = 18.9 %). Vegetation type models found significant associations with SMC only in shrublands (R2 = 0.31, RMSEcv = 9.03 %) based on the S2_NDMI and S1_VV/VH ratio. The seasonal analysis revealed however that predictors associated to VMC and SMC may vary over the summer. The relationships with VMC were stronger in the early summer (R2 = 0.31, RMSEcv = 90.1 %; based on S2_NDMI) and mid (R2 = 0.37, RMSEcv = 70.8 %; based on S2_NDVI), butnon-significant in the end of summer. Similar pattern was found for SMC, where the link with predictors decreases from the early summer (R2 = 0.33, RMSEcv = 16.0 %; based on S1_VH) and mid summer (R2 = 0.30, RMSEcv = 17.8 %; based on S2_NDMI) to the end of summer (non-significant). Overall, the hypothesis of a universal landscape model for VMC and SMC was not fully supported. Vegetation type models showed promise, particularly for VMC in shrubland conditions. Sentinel optical and radar data were the most significant predictors in all models, despite the inclusion of ancillary predictors. S2_NDVI, S2_NDMI, S1_VV and S1_VV/VH ratio were the most relevant predictors for VMC and, to a lesser extent, SMC. Future research should quantify misregistration effects using plot vs. moving window values for the satellite predictors, consider meteorological control factors, and enhance sampling to overcome a main limitation of our study, small sample size. [ABSTRACT FROM AUTHOR]

Urban mobility plays an important role in addressing urban livability. The complexification and dispersion of travel due to the improvement of transport and the multiplication of our daily living places underline the relevance of multilevel territorial planning, recognizing that the knowledge of local differences is essential for more effective urban policies. This paper aims (1) to comprehend conceptually how urban mobility contributes to the urban livability from the local to metropolitan level and (2) to assess the previous relation toward a livable metropolis based on the readily available statistics for the Lisbon Metropolitan Area. Hence, a triangulation between conceptual, political/operative, and quantitative/monitoring approaches is required. The methodology follows four steps: (1) literature review focusing on the quantification of urban mobility within the urban livability approach; (2) data collection from the Portuguese statistics system; (3) data analysis and results, using principal component analysis (PCA) followed by cluster analysis (CA); (4) discussion and conclusions. In Portugal, although it is implicit, consistency is evident between the premises of recent urban mobility policies and respective planning instruments, such as the Sustainable Urban Mobility Plans (SUMP), and the premises of urban livability as an urban movement. Focusing on the national statistics system, the available indicators that meet our quality criteria are scarce and represent a reduced number of domains. Even so, they allow identifying intra-metropolitan differences in the Lisbon Metropolitan Area (LMA) that could support multilevel planning instruments. The results identified five principal components related to commuting at the local and intermunicipal level, including car use as well as social and environmental externalities, and they reorganized the 18 LMA municipalities into eight groups, clearly isolating Lisbon, the capital, from the others. The identification of sensitive territories and respective problems based on urban livability principles is fundamental for an effective urban planning from livable communities to livable metropolis.