Sunshine is an important factor which limits the choice of urban plant species, especially in environments with high-density buildings. In practice, plant selection and configuration is a key step of landscape architecture, which has relied on an experience-based qualitative approach. However, the rationality and efficiency of this need to be improved. To maintain the diversity of plant species and to ensure their ecological adaptability (solar radiation) in the context of sustainable development, we developed the Urban Plants Decision Support System (UP-DSS) for assisting plant selection in urban areas with diversified solar radiation. Our methodology mainly consists of the solar radiation model and calibration, the urban plant database, and information retrieval model. The structure of UP-DSS is also presented at the end of the methodology section, which is based on the platform of Geographic Information Systems (GIS) and Microsoft Excel. An application of UP-DSS is demonstrated in a residential area of Wuhan, China. The results show that UP-DSS can provide a very scientific and stable tool for the adaptive planning of shade-tolerant plants and photoperiod-sensitive plants, meanwhile, it also provides a specific plant species and the appropriate types of plant community for user decision-making according to different sunshine radiation conditions and the designer's preferences.
Automated fare collection (AFC) systems can provide tap-in and tap-out records of passengers, allowing us to conduct a comprehensive analysis of spatiotemporal patterns for urban mobility. These temporal and spatial patterns, especially those observed over long periods, provide a better understanding of urban transportation planning and community historical development. In this paper, we explored spatiotemporal evolution of travel patterns using the smart card data of subway traveling from 2011 to 2017 in Shenzhen. To this end, a Gaussian mixture model with expectation–maximization (EM) algorithm clusters the travel patterns according to the frequency characteristics of passengers’ trips. In particular, we proposed the Pareto principle to negotiate diversified evaluation criteria on model parameters. Seven typical travel patterns are obtained using the proposed algorithm. Our findings highlighted that the proportion of each pattern remains relatively stable from 2011 to 2017, but the regular commuting passengers play an increasingly important position in the passenger flow. Additionally, focusing on the busiest commuting passengers, we depicted the spatial variations over years and identified the characters in different periods. Their cross-year usage of smart cards was finally examined to understand the migration of travel patterns over years. With reference to these methods and insights, transportation planners and policymakers can intuitively understand the historical variations of passengers’ travel patterns, which lays the foundation for improving the service of the subway system.
Hostplant limitation is a key focus of the spatial interaction between a phytophagous butterfly and a hostplant. The possible drivers related to the hostplants are species richness, abundance, or availability, but no consensus has been reached. In this study, we investigated the butterfly–hostplant interaction using the case of the forest canopy butterfly T. aureus in Asia, whose narrow distribution is assumed to be limited by its exclusive hostplant, Magnoliaceae, in tropic and subtropic regions. We recorded the Magnoliaceae species, as well as plant and butterfly individuals in transect, and we collected tree traits and topography variables. The results confirm that this butterfly is limited by the hostplants of their larval stage. The hostplants occurred exclusively in the middle-mountain region, with preference only for primeval forests. The hostplant resource was superior in the middle-mountain region, particularly concentrating in primeval forests. The hostplant’s abundance, together with altitude and habitat types, was critical to this butterfly’s occurrence, while those hostplant trees with an exposed crown, which are demanded by this butterfly in its oviposition, were the best drivers of positive butterfly–hostplant interactions. Therefore, the hostplant’s limitation was mainly determined by the availability of the hostplant. This case study supports the hypothesis that the limitation on this butterfly’s occurrence was driven by the hostplant’s availability, and it suggests that protecting high-quality forests is a valuable activity and essential in the conservation of canopy butterflies.
With the rapid expansion of high-rise and high-density buildings in urban areas, visual privacy has become one of the major concerns affecting human environmental quality. Evaluation of residents’ visual exposure to outsiders has attracted more attention in the past decades. This paper presents a quantitative indicator; namely, the Potential Visual Exposure Index (PVEI), to assess visual privacy by introducing the damage of potential visual incursion from public spaces and neighborhoods in high-density residences. The method for computing the PVEI mainly consists of three steps: extracting targets and potential observers in a built environment, conducting intervisibility analysis and identifying visible sightlines, and integrating sightlines from building level and ground level to compute the PVEI value of each building opening. To validate the proposed PVEI, a case study with a sample building located at the center of Kowloon, Hong Kong, was evaluated. The results were in accordance with the common-sense notion that lower floors are subjected to poor visual privacy, and privacy is relatively well-preserved in upper floors in a building. However, residents of middle floors may suffer the worst circumstances with respect to visual privacy. The PVEI can be a useful indicator to assess visual privacy and can provide valuable information in architectural design, hotel room selection, and building management.
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