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Most sustainable planning frameworks assess natural and social–economic landscape systems as separate entities, and our understanding of the interrelationships between them is incomplete. Landscape classification in urbanizing environments requires an integrated spatial planning approach to better address the United Nation’s sustainable development challenges. The objective of this research is to apply a multicriteria evaluation which ranked diverse ecosystem–service producing landscapes and synthesize the findings within a unique green infrastructure spatial planning framework. Local government stakeholder derived weighting and GIS classification were operated to map both the urban and natural landscapes of the Salt Lake City region of Utah, one of the most rapidly urbanizing areas in North America. Results were assimilated through five regional landscape typologies—Ecological, Hydrological, Recreational, Working Lands, and Community—and indicated those highest ranked landscape areas which provided multiple ecosystem services. These findings support collaborative decision making among diverse stakeholders with overlapping objectives and illustrates pathways to the development of ecosystem service criteria. This paper contributes to a better understanding of how to integrate data and visualize the strategic approaches required for sustainable planning and management, particularly in urban and urbanizing regions where complex socioecological landscapes predominate.

In this study, a recovery assessment of the permanent housing and living conditions in the aftermath of the 2004 Tsunami in Phang-nga Province, Thailand, was conducted using geoinformatics technologies, field observations, and living-related parameters from basic minimum need (BMN) data retrieved from the Ministry of Interior. In the results, 29 permanent housing projects were mapped, classified into five sizes (very small, small, medium, large, and very large), and overlaid with the tsunami-inundated zone visually interpreted from satellite images. Thirteen out of twenty-nine projects were reconstructed in the inundation zone (in situ), while the rest were relocated to higher ground. Permanent houses were rebuilt in 18 communities in three patterns: single-story or one-story houses (511 houses), single-story and raised-basement houses (58 houses), and two-story houses (712 houses). The selected BMN’s living-related parameters, such as sufficient water for household consumption (dimension: dwelling), employment of people between 15 and 60 years old (dimension: economy), and participation in communities’ activities (dimension: participation), which covered 2002–2015 at the community-based level, were compared annually to its criterion and indicated as passing or not passing the standard. The reconstructed communities recovered (passing the requirements) within four years of transferring to the reconstructed houses.

Demand for continuous and reliable power supply has significantly increased, especially in this Industrial Revolution 4.0 era. In this regard, adequate planning of electrical power systems considering persistent load growth, increased integration of distributed generators (DGs), optimal system operation during N-1 contingencies, and compliance to the existing system constraints are paramount. However, these issues need to be parallelly addressed for optimum distribution system planning. Consequently, the planning optimization problem would become more complex due to the various technical and operational constraints as well as the enormous search space. To address these considerations, this paper proposes a strategy to obtain one optimal solution for the distribution system expansion planning by considering N-1 system contingencies for all branches and DG optimal sizing and placement as well as fluctuations in the load profiles. In this work, a hybrid firefly algorithm and particle swarm optimization (FA-PSO) was proposed to determine the optimal solution for the expansion planning problem. The validity of the proposed method was tested on IEEE 33- and 69-bus systems. The results show that incorporating DGs with optimal sizing and location minimizes the investment and power loss cost for the 33-bus system by 42.18% and 14.63%, respectively, and for the 69-system by 31.53% and 12%, respectively. In addition, comparative studies were done with a different model from the literature to verify the robustness of the proposed method.

Air pollution and the urban heat island effect are consistently linked to numerous respiratory and heat-related illnesses. Additionally, these stressors disproportionately impact low-income and historically marginalized communities due to their proximity to emissions sources, lack of access to green space, and exposure to other adverse environmental conditions. Here, we use relatively low-cost stationary sensors to analyze PM2.5 and temperature data throughout the city of Richmond, Virginia, on the ten hottest days of 2019. For both hourly means within the ten hottest days of 2019 and daily means for the entire record for the year, the temperature was found to exhibit a positive correlation with PM2.5. Analysis of hourly means on the ten hottest days yielded a diurnal pattern in which PM2.5 levels peaked in the early morning and reached their minima in the mid-afternoon. Spatially, sites exhibiting higher temperatures consistently had higher PM2.5 readings, with vulnerable communities in the east end and more intensely developed parts of the city experiencing significantly higher temperatures and PM2.5 concentrations than the suburban neighborhoods in the west end. These findings suggest an uneven distribution of air pollution in Richmond during extreme heat events that are similar in pattern but less pronounced than the temperature differences during these events, although further investigation is required to verify the extent of this relationship. As other studies have found both of these environmental stressors to correlate with the distribution of green space and other land-use factors in cities, innovative and sustainable planning decisions are crucial to the mitigation of these issues of inequity going forward.

Land&ndash, sea interaction dynamics are physiologically regulated by an exchange of matter (and energy) between the anthropic system and the natural environment. Therefore, the appropriate management of land&ndash, sea interaction (LSI)contexts should base on those planning approaches which can holistically support coastal development, such as Maritime Spatial Planning (MSP) and Climate Adaptation Planning (CAP). One of the main limiting factors for this integration is the fragmentation of existing databases and information sources, which compose the territorial knowledge framework. Investigations have sought to address the representation and assessment of &ldquo, wicked&rdquo, and interconnected coastal problems. The present research focuses on the production of the necessary information to fill sectorial knowledge gaps and to merge the available data into a single framework. The research methodology is based on remote sensing assessment techniques and is designed to be replicated in other coastal areas to integrate CAP and MSP. The output maps are a result of the empirical application of the integration of the assessment techniques and are meant to support local decision-making processes. The result aims at illustrating and highlighting the relationships between climate change impact vulnerabilities their spatial relation to marine resources and maritime activities. This can support effective actions aimed at environmental and urban protection, the organization of the uses of the sea and adaptation to climate impacts. The application of the assessment techniques is developed on a case study in the north Adriatic Basin. The Gulf of Trieste constitutes a representative case study for the Mediterranean Basin due to its transboundary nature. The relationship and the ongoing projects between Slovenia and Italy make the case study an interesting context in which to test and train the proposed integrated planning approach. Therefore, the study investigates local vulnerability to climate impacts, i.e., Urban Heat Island (UHI) and urban runoff, and the existing relationship between the urban fabrics and the marine environment.

Sustainable conservation aims to ensure the sustained conservation of landscape multi-functionality which in turn requires ensuring ecosystem service (ES) and habitat quality (HQ) sustainability with inclusive landscape-scale conservation planning. This study proposes a landscape conservation planning (LCP) framework for landscape-scale ES-HQ conservation and sustainability. Spatially explicit hotspots for five ESs and HQs are identified via InVEST and LISA software. Spatiotemporal changes in ES-HQ hotspots, in terms of stability and resilience, are delineated. The Zonation technique is applied to prioritize areas for conservation based on ES-HQ hotspot stability and resilience maps. High priority conservation areas are identified and are used as reserve area inputs for land use modeling with CLUE-S software to simulate future land use change under climate change scenarios. This study reports that varied rainfall and climate are major driving factors of ES-HQ sustainability disturbance in the study area. Furthermore, our proposed conservation Strategy 2 demonstrates that a larger extent of landscape multi-functionality can be sustained when the existing conservation area includes the total area of identified ES-HQ resilient hotspots. This study effectively identifies the stability and resiliency of ES-HQ hotspot areas affected by disturbances for high priority landscape conservation requirements to ensure ES-HQ sustainability and landscape multi-functionality in the study area.

The urban planning development process in urban territories has multiple consequences, not only in spatial structure but also in land valuation patterns. The economic value of land encompassed in municipal planning-which is associated with a certain urbanized use-increases as the planning processes evolve over these lands. For economic land valuation to comply with the required parameters of urban and territorial sustainable development, it is pivotal that in the determination of land value there are no expectations of difficult or impossible realizations, in order to eliminate any speculative element from the valuation. The land valuation model presented in the current study complies with this premise, proposing a sustainable land valuation model based on the evolution of urban planning development, achieving maximum value when it is fully urbanized. The main objective of the present work is to analyze how land value increases as municipal planning develops and to suggest a sustainable valuation model for land with urban use. Contextually, through a case study analysis, the development of municipal planning has been divided over time into four urban states: (i) land without detailed planning; (ii) land with detailed planning; (iii) land with re-parceling; and (iv) urbanized land. In this regard, the gradual evolution of land value which has reached different states over time has been determined, as has scenarios where the value has increased up to the value of urbanized land. © 2018 by the author.

Environmental deprivation is an issue influencing the urban wellbeing of a city. However, there are limitations to spatiotemporally monitoring the environmental deprivation. Thus, recent studies have introduced the concept of “Smart City” with the use of advanced technology for real-time environmental monitoring. In this regard, this study presents an improved Integrated Environmental Monitoring System (IIEMS) with the consideration on nine environmental parameters: temperature, relative humidity, PM2.5, PM10, CO, SO2, volatile organic compounds (VOCs), UV index, and noise. This system was comprised of a mobile unit and a server-based platform with nine highly accurate micro-sensors in-coupling into the mobile unit for estimating these environmental exposures. A calibration test using existing monitoring station data was conducted in order to evaluate the systematic errors. Two applications with the use of the new system were also conducted under different scenarios: pre- and post-typhoon days and in areas with higher and lower vegetation coverage. Linear regressions were applied to predict the changes in environmental quality after a typhoon and to estimate the difference in environmental exposures between urban roads and green spaces. The results show that environmental exposures interact with each other, while some exposures are also controlled by location. PM2.5 had the highest change after a typhoon with an estimated 8.0 μg/m³ decrease that was controlled by other environmental factors and geographical location. Sound level and temperature were significantly higher on urban roads than in urban parks. This study demonstrates the potential to use IIEMS for environmental quality measurements under the greater framework of a Smart City and for sustainability research.

Urban strategies and the way cities are planned have changed throughout history, adapting to the needs of the inhabitants, infrastructure requirements, and advances in technology. Uses and customs of people and cities are changing and can evolve much faster than in the past, with the result that urban planning is often too slow to adequately meet the current needs of society. In this context, the development of pop-up environments for temporary developments could be a solution to meet the needs of flexibility, adaptation, and resilience of a city. This allows the urban planner to consider systems from a short-term perspective, fulfilling current needs without compromising the development of potentially different activities in the future. The purpose of this research work is to outline the general requirements of pop-up environments in urban developments that allow for adequate integration into urban planning strategies. Based on an extensive evaluation of the existing literature and a series of case studies, the paper analyzes the key elements that define the framework conditions of urban planning strategies for temporary developments that generate a positive impact on the overall urban system.