There is an urgent need for holistic tools to assess the health impacts of climate change mitigation and adaptation policies relating to increasing public green spaces. Urban vegetation provides numerous ecosystem services on a local scale and is therefore a potential adaptation strategy that can be used in an era of global warming to offset the increasing impacts of human activity on urban environments. In this study, we propose a set of urban green ecological metrics that can be used to evaluate urban green ecosystem services. The metrics were derived from two complementary surveys: a traditional remote sensing survey of multispectral images and Laser Imaging Detection and Ranging (LiDAR) data, and a survey using proximate sensing through images made available by the Google Street View database. In accordance with previous studies, two classes of metrics were calculated: greenery at lower and higher elevations than building facades. In the last phase of the work, the metrics were applied to city blocks, and a spatially constrained clustering methodology was employed. Homogeneous areas were identified in relation to the urban greenery characteristics. The proposed methodology represents the development of a geographic information system that can be used by public administrators and urban green designers to create and maintain urban public forests.
The paper presents an integrated methodology to assess psychological and physiological responses of people when exposed to forests, with the main objective of assessing the suitability of different stands for stress recovery on the basis of tree species and density. From the methodological viewpoint, the study applies both a Restoration Outcome Scale (ROS) questionnaire and a neuroscientific technique grounded on electro-encephalographic (EEG) measurement. Results show different outcomes for conifers and broadleaves as well as a statistical significance of density in the evaluation of an individual’s emotional state. A forest with a high density of conifers and low density of broadleaves seems to be the proper combination for stress recovery. The differences among psychological stated preferences and EEG trends highlights potential conflict among “needs” and “wants” of people in the topic of stress relief. Potential applications of the research for health care and territorial marketing operations are suggested.
Purpose Wine packaged tours as a specific aspect of wine tourism have so far been neglected in research, for this reason, the purpose of this study is to study the key elements for the success of the wine tour in Tuscany (Italy), evaluating the points of strength and weakness. Design/methodology/approach The study combines approaches of text mining, sentiment analysis and natural language processing, drawing on data from the TripAdvisor platform, obtaining through an automatic procedure 9,616 reviews from 600 tours in the years 2010–2020. Findings The authors identified six elements of successful wine tours expressed by research subjects: tour guide; logistical aspects; the quality of the wine; the quality of the food; complementary tourist and recreational activities; the landscape and historic villages. The key strength associated with success was the integration of the leading wine product with food, landscape and historic villages, while the main criticisms were concerned with the organization and planning of the tour. Furthermore, the tour guide also plays a fundamental role in consumer satisfaction. Research limitations/implications The limitations of the method were linked to the origin of the data used. The main one is that TripAdvisor does not allow you to have social and personal information about the tourist who wrote the review; therefore, the methods are substantially complementary to the traditional survey through questionnaires. Practical implications The proposed model can be used both by professionals to improve the quality of their products and by policymakers to promote the territorial development of quality wine-growing areas. Social implications The proposed model can be useful for policymakers to promote the territorial development of quality wine-growing areas. Originality/value The methodology we tested is easily transferable to many countries and to the authors’ knowledge, for the first time attempts to combine multidimensional scaling, sentiment analysis and natural language processing approaches.
The climate of a city influences the ways in which its outdoor spaces are used. Especially, public spaces intended for use by pedestrians and cyclists, such as parks, squares, residential and commercial streets, and foot and cycle paths will be used and enjoyed more frequently if they have a comfortable and healthy climate. Due to the predicted global temperature increase, urban climate is likely to become more uncomfortable, especially in summer when an increase in heat stress is expected. Urban forestry has been proposed as one approach for mitigating the human health consequences of increased temperature resulting from climate change. The aims of the current research were to (a) provide a transferable methodology useful for analyzing the effect of urban trees on surface temperature reduction, particularly in public spaces, and (b) provide high-resolution urban mapping for adaptation strategies to climate change based on green space projects. To achieve the established aims, we developed a methodology that uses multisource data: LiDAR data, high-resolution Landsat imagery, global climate model data from CMIP5 (IPPC Fifth Assessment), and data from meteorological stations. The proposed model can be a useful tool for validating the efficiency of design simulations of new green spaces for temperature mitigation. ARTICLE HISTORY
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