Cooling Island Effect of Blue-Green Corridors: Quantitative Comparison of Morphological Impacts

The patterns of green corridors in urban riverfront districts provide different synergistic cooling effects of blue-green space in urban areas. The purpose of this study is to quantify the spatial morphological impact of green corridors in riverfront block-scale area on the cooling effect. Three representative patterns (radiate, grid and dendritic) were selected in the study. The comprehensive influences analysis between multi-dimensional factors of spatial structure and morphology of green corridors and Ta (air temperature) distribution are processed by Envi-met4.4.5 simulation data and statistical analysis methods, such as regression tree model (BRT), were combined. The results showed that the D (distance from riverbank) has the greatest impact on the cooling effect of each belt green space. The D in the range of 600–750 m was affected by the cooling effect of blue-green space; The orientation with parallel to (southeast–northwest) or roughly the same as the prevailing wind direction (north–south) green corridors had relatively better cooling effect. When the width of green corridor was 20–25 m, the ME (marginal effect) of cooling was the largest; at 30–35 m (corridor width), the overall ME of cooling was the best; When the dPC (decreased probability connectivity, here the index was adapted to describe the connectivity degree) of green corridors was in the range of 0.5–1.5, the cooling effect of green corridor could be significantly improved. When dPC is 1.5, its marginal effect on temperature reached the maximum. The study provided a quantitative correlation technology for the morphological influence of blue-green on the distribution of UCI (urban cooling island), which can guide the spatial layout control of green corridors in the planning and design of urban riverfront district.

The Effects of Different Natural Environment Influences on Health and Psychological Well-Being of People: A Case Study in Selangor

Background: People benefit from the recreational services provided by an urban corridor, urban park, and urban forest. Due to ongoing land-use interest and urban development, however, these natural environments are coming under increasing pressure. Simultaneously, the world is becoming increasingly urbanised, and living in cities has been linked to mental health issues. On the other hand, different natural environments are known to create healthier environments, and the need for effective restorative environments has never been greater. The purpose of the study was to compare the impacts of walking in different natural environments. Methods: I) Kota Damansara Community Forest Reserve, II) Mutiara Damansara Recreational Park, and III) the Urban Green Corridor along Jalan PJU 7/7 were used as control study sites in this study. Each site was visited only once by the study participants (40 women and 40 men). Walking for 30 min was a part of the experiment. To identify the psychological effects of different natural environments, the Depression, Anxiety, and Stress Scale (DASS21), Profile of Mood States (POMS), Positive and Negative Affect Schedule (PANAS), and Restoration Outcome Scale (ROS) were utilised. Results: In all three natural environments, the restorative effects were found to increase significantly. Conclusion: The overall conclusion of the field experiment is that being in an urban green corridor can also provide a refreshing environment. In terms of stress reduction among working adults, the recreational park is sufficient, while urban-forested areas are more effective in improving mental health by minimising stress, anxiety, and depression.

RFID Based Smart Traffic Management and Green Corridor for Emergency Vehicles

Transportation has become a global crisis. In the current situation, we have a huge increase in the population. This rise has increased facilities to soothe the needs of human beings. Each family has at least one vehicle, to travel to their destination. With such an increase in the vehicular count, we don't have the infrastructure to meet these rising demands. Not only the adequate infrastructure but also the right management of the vehicles is important. Such is the below-proposed system where a smart IOT based traffic management system is designed. Also, an automatic high-tech green corridor creation mechanism is proposed for the smooth movement of emergency vehicles. The resultant system,upon testing and experiments proves to be more efficient. The time taken without implementing the above system is more than the one taken using the given proposed system.

Exploring simple K-means clustering algorithm for automating segregation of colors in leaf of Axonopus compressus: Towards maintenance of an urban landscape

Images of green infrastructure (gardens, green corridor, green roofs and grasslands) large area can be captured and processed to provide spatial and temporal variation in colours of plant leaves. This may indicate average variation in plant growth over large urban landscape (community gardens, green corridor etc). Towards this direction, this short technical note explores development of a simple automated machine learning program that can accurately segregate colors from plant leaves. In this newly developed program, a machine learning algorithm has been modified and adapted to give the proportion of different colors present in a leaf. Python script is developed for an image processing. For validation, experiments are conducted in green house to grow Axonopus compressus. Script first extracts different RGB (Red Green and Blue) colors present in the leaf using the K-means clustering algorithm. Appropriate centroids required for the clusters of leaf colors are formed by the K-means algorithm. The new program provides saves computation time and gives output in form of different colors proportion as a CSV (Comma-Separated Values) file. This study is the first step towards the demonstration of using automated programs for the segregation of colors from the leaf in order to access the growth of the plant in an urban landscape.