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Several studies have recognised the importance of urban green spaces (UGSs) in modern cities. However, the distribution and accessibility of green spaces represent a challenge for the sustainable development of territories in terms of fair distribution, reducing inequalities, and mitigating the effects of climate change, such as urban heat islands and runoff. This research identifies every UGS capable of contributing to people's physical and mental wellbeing in the Milan metropolitan area (MMA), one of the most densely populated areas in Europe. The method allows for the various UGSs to be identified and classified using a comparative approach that considers both formal and informal green spaces through a qualitative territorial analysis and the support of open access databases (satellite and thematic maps). Based on this classification, this contribution establishes an 'accessibility map' of the metropolitan area that determines the actual pedestrian accessibility of a UGS within 300 m. The results show that only 37% of the residential surface of the metropolitan area offers access to a UGS within a five-minute walk. This research aims to identify the most fragile segment of the MMA, which is pivotal for the tree-planting activities sponsored by the Forestami project. [ABSTRACT FROM AUTHOR]

The large-scale identification of urban vacant land (UVL) and informal green spaces (IGSs) using conventional identification methods is challenged by the high cost of time and resources as well as inconsistent outcomes. Moreover, the spatial–temporal changes of UVL and IGSs have received limited academic attention. We introduce a methodological framework for the large-scale automatic identification of UVL and IGSs in Hangzhou, China, based on semantic segmentation. We construct and release a large-scale dataset for UVL identification, containing five different UVL categories, and one of them is IGS, with 3096 patches for training and 128 patches for evaluation. We then train five different semantic segmentation networks using the dataset and utilise Segformer to predict UVL and IGSs within the whole urban area of Hangzhou. The presented segmentation model has a hierarchically structured Transformer encoder and a multilayer perceptron decoder, which incorporates local and global information to obtain effective feature representations. Extensive experiments have been conducted to evaluate the segmentation performance of the applied Segformer. Experimental results show the good identification performance of Segformer for UVL and IGSs. Results also verify that the proposed identification framework can be effectively used to analyse the spatial–temporal changes of UVL and IGSs in Hangzhou. [ABSTRACT FROM AUTHOR]

In this experiment, we operated within the novel research area of Informal Green Spaces (often called green wastelands), exploring emotional well-being with the employment of portable electroencephalography (EEG) devices. The apparatus (commercial EEG Muse headband) provided an opportunity to analyze states of calmness and alertness in n = 20 participants as they visited selected Informal Green Spaces in Warsaw, Poland. The article aims to test the hypothesis that passive recreation in Informal Green Spaces (IGSs) has a positive impact on emotional well-being and that there is a connection between the intensity of states of calmness and alertness and 1. the type of green space (IGS/GS), 2. the type of scenery and 3. the type of IGS. The preliminary experiment showed that there might be no substantial distinction in the users' levels of emotional states when considering existing typologies. On the other hand, data-driven analysis suggests that there might be a connection between the state of alertness and some characteristics of specific areas. After carrying out the multivariate analyses of variance in the repeated measurement scheme and finding significant differences between oscillations in different areas, we conclude that there might be three possible sources of lower alertness and increased calmness in some areas. These are 1. the presence of "desirable" human intervention such as paths and urban furniture, 2. a lack of "undesirable" users and signs of their presence and 3. the presence of other "desirable" users. [ABSTRACT FROM AUTHOR]