Selection and Optimization of Regional Economic Industrial Structure Based on Fuzzy k-Means Clustering Algorithm.

Learning about the regional business model is essential for the sustainable development of the regional economy. From the perspective of urban renewable energy, city A is the product of energy development. This paper analyzes the current situation and existing problems of the industrial model of city A through fuzzy k-means clustering algorithm. The results show that although the optimization of industrial structure in city A has achieved some results, the more intuitive problems mainly include low labor productivity of the primary industry, strong resource dependence, insufficient extension of industrial chain, and slow development of technology intensive industries. This paper uses fuzzy k-means clustering algorithm to select the leading industries from the perspective of the current situation of leading industries, urban development pattern, and regional policies in city A. The results show that, as a renewable resource-based city, the leading industries suitable for the current development of city A include manufacturing, power, alkali gas and water production and supply, transportation, warehousing and postal industry, leasing, and business services. The results of fuzzy k-means clustering algorithm are quite excellent, and the accuracy rate is 93.3%. This paper uses the grey dynamic linear programming model to predict the future development of the Urban A business model and combines the selection of key functions to obtain the best business model: deep and efficient technical equipment as a good goal, achieved through regional logistics, transportation, new services, etc., to enhance the output value of the tertiary industry in city A and optimize the internal structure of the secondary industry in city A.

A street-view-based method to detect urban growth and decline: A case study of Midtown in Detroit, Michigan, USA.

Urban growth and decline occur every year and show changes in urban areas. Although various approaches to detect urban changes have been developed, they mainly use large-scale satellite imagery and socioeconomic factors in urban areas, which provides an overview of urban changes. However, since people explore places and notice changes daily at the street level, it would be useful to develop a method to identify urban changes at the street level and demonstrate whether urban growth or decline occurs there. Thus, this study seeks to use street-level panoramic images from Google Street View to identify urban changes and to develop a new way to evaluate the growth and decline of an urban area. After collecting Google Street View images year by year, we trained and developed a deep-learning model of an object detection process using the open-source software TensorFlow. By scoring objects and changes detected on a street from year to year, a map of urban growth and decline was generated for Midtown in Detroit, Michigan, USA. By comparing socioeconomic changes and the situations of objects and changes in Midtown, the proposed method is shown to be helpful for analyzing urban growth and decline by using year-by-year street view images.

The persistence of ancient settlements and urban sustainability.

We propose a dedicated research effort on the determinants of settlement persistence in the ancient world, with the potential to significantly advance the scientific understanding of urban sustainability today. Settlements (cities, towns, villages) are locations with two key attributes: They frame human interactions and activities in space, and they are where people dwell or live. Sustainability, in this case, focuses on the capacity of structures and functions of a settlement system (geography, demography, institutions) to provide for continuity of safe habitation. The 7,000-y-old experience of urbanism, as revealed by archaeology and history, includes many instances of settlements and settlement systems enduring, adapting to, or generating environmental, institutional, and technological changes. The field of urban sustainability lacks a firm scientific foundation for understanding the long durée, relying instead on narratives of collapse informed by limited case studies. We argue for the development of a new interdisciplinary research effort to establish scientific understanding of settlement and settlement system persistence. Such an effort would build upon the many fields that study human settlements to develop new theories and databases from the extensive documentation of ancient and premodern urban systems. A scientific foundation will generate novel insights to advance the field of urban sustainability.

Negative responses to urban residential noise as a social rebound effect of increasing population density: Legislative challenges and auditory territoriality.

Populations in cities are projected to increase globally, densifying urban residential environments with both positive and negative effects. Positive social effects are offset by negative health effects however; urban residential noise has been identified in a large number of studies as a significant contributor to social unrest as well as a risk to physiological and psychological health caused by stress, making this topic highly relevant to the discussion on sustainability urban growth. Focusing on the psychological rebound effect of urban residential noise, this paper attempts to explain how and why auditory aspects of the spatial environment negatively influences urban residents. To provide context and to indicate areas in need of improvement, the legislative challenges to be faced are considered, with Sweden as a prime example of a first world country grappling with the effects of increased urban density. Existing building legislation regarding residential noise is considered in relation to studies investigating the effects of residential noise on psychological and physiological health, outlining areas in need of future development. Then, health responses to residential noise are placed in a broader evolutionary context by considering how these effects might be the result of triggered evolutionary mechanisms for keeping population size optimal. Further, the spatial dimension of hearing is discussed with reference to theories of territoriality in environmental psychology and the concept of auditory territoriality is described.

Identification of urban land use efficiency by indicator-SDG 11.3.1.

Inefficiency in urban land use is one of the problems caused by rapid urbanization. The UN Sustainable Development Goals (SDGs) indicator 11.3.1 is designed to test urban land use efficiency. This study employed geospatial and statistical data to compute land use efficiencies from 1990 to 2015 with five 5-year and ten 15-year intervals in Wukang, center of Deqing County, China. A flowchart was designed to extract the built-up lands from multiple data sources. The produced built-up lands were demonstrated to provide good accuracy by constructing an error matrix between the extracted and manually interpreted built-up lands as classified and reference images, respectively. By using the model provided by UN metadata to calculate SDG 11.3.1, the land use efficiencies from 1990 to 2015 were identified in Wukang. Our results indicate that the land use efficiency in Deqing County center is lower than the average of cities around the world, primarily because our in-situ study focused on a county center with larger rural regions than urban areas. Over the long term, urban land use becomes denser as the population grows, which will have a positive impact on the sustainability of urban development. This work is helpful for the local government to balance urban land consumption and population growth.

Coastal restoration evaluated using dominant habitat characteristics and associated fish communities.

Increasing coastal populations and urban development have led to the loss of estuarine habitats for fish and wildlife. Specifically, a decline in complexity and heterogeneity of tidal marshes and creeks is thought to negatively impact fish communities by altering the function of nursery grounds, including predator refuge and prey resources. To offset these impacts, numerous agencies are restoring degraded habitats while also creating new ones where habitat has been lost. To improve understanding of what contributes to a successful restoration, six quarterly sampling events using two gear types to collect small- and large-bodied fishes were conducted to compare the fish community structure and habitat characteristics at three natural, three restored, and three impacted (i.e. ditched) areas along the coast of Tampa Bay, Florida. Overall, impacted sites had significantly lower small-bodied and juvenile fish diversity than natural and restored areas, while restored sites harbored a greater number of fish species than impacted sites for both large- and small-bodied fish. Habitat features such as shoreline slope differentiated impacted and restored from natural areas. Although we did not find a direct correlation, habitat heterogeneity likely played a role in structuring fish communities. These findings provide guidance for future coastal restoration or modification of existing projects. Specifically, the habitat mosaic approach of creating a geographically compact network of heterogenous habitat characteristics is likely to support fish diversity, while decreasing shoreline slope in a greater amount of area within coastal wetland restorations would more closely mimic natural areas.

The role of personal factors in attitudes toward the adoption of new consumption behaviors in developing food systems.

Through dual-period surveys in urban China, administered in the years 1996 and 2013, this study investigates changes in the relationship among personal factors and the attitudes toward the adoption of new food consumption patterns as food systems develop. A structural equation model (SEM) is used to measure the association among three personal factors (traditionalism, do-it-yourself [DIY] propensity, and time scarcity) and attitudes toward three new food consumption behaviors (use of processed food, eating out, and convenience shopping). The results reveal complex relationships between personal factors and attitudes toward the adoption of new food shopping behaviors, indicating that supply-side models of retailing development are insufficient to adequately predict changes in food systems.

Gentrification And The Health Of Low-Income Children In New York City.

Although the pace of gentrification has accelerated in cities across the US, little is known about the health consequences of growing up in gentrifying neighborhoods. We used New York State Medicaid claims data to track a cohort of low-income children born in the period 2006-08 for the nine years between January 2009 and December 2017. We compared the 2017 health outcomes of children who started out in low-income neighborhoods that gentrified in the period 2009-15 with those of children who started out in other low-income neighborhoods, controlling for individual child demographic characteristics, baseline neighborhood characteristics, and preexisting trends in neighborhood socioeconomic status. Our findings suggest that the experience of gentrification has no effects on children's health system use or diagnoses of asthma or obesity, when children are assessed at ages 9-11, but that it is associated with moderate increases in diagnoses of anxiety or depression-which are concentrated among children living in market-rate housing.

Urban sustainability in an age of enduring inequalities: Advancing theory and ecometrics for the 21st-century city.

The environmental fragility of cities under advanced urbanization has motivated extensive efforts to promote the sustainability of urban ecosystems and physical infrastructures. Less attention has been devoted to neighborhood inequalities and fissures in the civic infrastructure that potentially challenge social sustainability and the capacity of cities to collectively address environmental challenges. This article draws on a program of research in three American cities-Boston, Chicago, and Los Angeles-to develop hypotheses and methodological strategies for assessing how the multidimensional and multilevel inequalities that characterize contemporary cities bear on sustainability. In addition to standard concerns with relative inequality in income, the article reviews evidence on compounded deprivation, racial cleavages, civic engagement, institutional cynicism, and segregated patterns of urban mobility and organizational ties that differentially connect neighborhood resources. Harnessing "ecometric" measurement tools and emerging sources of urban data with a theoretically guided framework on neighborhood inequality can enhance the pursuit of sustainable cities, both in the United States and globally.

Analysis of land suitability for urban development in Ahwaz County in southwestern Iran using fuzzy logic and analytic network process (ANP).

The ever-increasing development of cities due to population growth and migration has led to unplanned constructions and great changes in urban spatial structure, especially the physical development of cities in unsuitable places, which requires conscious guidance and fundamental organization. It is therefore necessary to identify suitable sites for future development of cities and prevent urban sprawl as one of the main concerns of urban managers and planners. In this study, to determine the suitable sites for urban development in the county of Ahwaz, the effective biophysical and socioeconomic criteria (including 27 sub-criteria) were initially determined based on literature review and interviews with certified experts. In the next step, a database of criteria and sub-criteria was prepared. Standardization of values and unification of scales in map layers were done using fuzzy logic. The criteria and sub-criteria were weighted by analytic network process (ANP) in the Super Decision software. Next, the map layers were overlaid using weighted linear combination (WLC) in the GIS software. According to the research findings, the final land suitability map was prepared with five suitability classes of very high (5.86 %), high (31.93 %), medium (38.61 %), low (17.65 %), and very low (5.95 %). Also, in terms of spatial distribution, suitable lands for urban development are mainly located in the central and southern parts of the Ahwaz County. It is expected that integration of fuzzy logic and ANP model will provide a better decision support tool compared with other models. The developed model can also be used in the land suitability analysis of other cities.

Nonzero-Sum Relationships in Mitigating Urban Carbon Emissions: A Dynamic Network Simulation.

The "stove-pipe" way of thinking has been mostly used in mitigating carbon emissions and managing socioeconomics because of its convenience of implementation. However, systems-oriented approaches become imperative in pursuit of an efficient regulation of carbon emissions from systems as complicated as urban systems. The aim of this paper is to establish a dynamic network approach that is capable of assessing the effectiveness of carbon emissions mitigation in a more holistic way. A carbon metabolic network is constructed by modeling the carbon flows between economic sectors and environment. With the network shocked by interventions to the sectoral carbon flows, indirect emissions from the city are accounted for under certain carbon mitigation strategies. The nonzero-sum relationships between sectors and environmental components are identified based on utility analysis, which synthesize the nature of direct and indirect network interactions. The results of the case study of Beijing suggest that the stove-pipe mitigation strategies targeted the economic sectors might be not as efficient as they were expected. A direct cutting in material or energy import to the sectors may result in a rebound in indirect emissions and thus fails to achieve the carbon mitigation goal of the city as a whole. A promising way of foreseeing the dynamic mechanism of emissions is to analyze the nonzero-sum relationships between important urban components. Thinking cities as systems of interactions, the network approach is potentially a strong tool for appraising and filtering mitigation strategies of carbon emissions.

A century of sprawl in the United States.

The urban street network is one of the most permanent features of cities. Once laid down, the pattern of streets determines urban form and the level of sprawl for decades to come. We present a high-resolution time series of urban sprawl, as measured through street network connectivity, in the United States from 1920 to 2012. Sprawl started well before private car ownership was dominant and grew steadily until the mid-1990s. Over the last two decades, however, new streets have become significantly more connected and grid-like; the peak in street-network sprawl in the United States occurred in ∼ 1994. By one measure of connectivity, the mean nodal degree of intersections, sprawl fell by ∼ 9% between 1994 and 2012. We analyze spatial variation in these changes and demonstrate the persistence of sprawl. Places that were built with a low-connectivity street network tend to stay that way, even as the network expands. We also find suggestive evidence that local government policies impact sprawl, as the largest increases in connectivity have occurred in places with policies to promote gridded streets and similar New Urbanist design principles. We provide for public use a county-level version of our street-network sprawl dataset comprising a time series of nearly 100 y.

The effectiveness of conservation interventions to overcome the urban-environmental paradox.

Globally, urbanization is rapidly growing cities and towns at a historically unprecedented rate, and this rapid urban growth is influencing many facets of the environment. This paper reviews the effectiveness of conservation interventions that are designed to increase urban sustainability. It presents evidence for an apparent urban-environmental paradox: while the process of urban growth converts natural habitat to other land covers and degrades natural resources and ecosystem function, the increase in human population can increase demand for natural resources and ecosystem services. The fundamental problem that many conservation interventions try to address is that most facets of the environment are common or public goods, and are hence undervalued in decision making (market failure). The paper presents a threefold classification of conservation interventions in cities: conservation in the city (protecting biodiversity), conservation by the city (reducing per capita resource and energy use), and conservation for cities (projects that maintain or enhance ecosystem services). It ends by discussing methods for spatially targeting conservation interventions of all three types and for quantifying the effectiveness of interventions retrospectively.

Geospatial quantification and analysis of environmental changes in urbanizing city of Kolkata (India).

Over the past five decades, the fragile wetland ecosystem surrounding the city of Kolkata has witnessed extensive changes in the name of urban development. In this study, we elaborate relationships among biophysical parameters and land surface temperature (LST) in Kolkata city and nearby surrounding areas where rapid urbanization has occurred. LST and associated surface physical characteristics were assessed using Landsat images acquired for the years 1989, 2006, and 2010. The satellite data was used to study the spatiotemporal urban footprint and correlation among normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI) and LST. Land use land cover (LULC) maps prepared using supervised classification had overall accuracy of 90, 88, and 86 % and kappa coefficient of 0.8726, 0.8455, and 0.8212 for 1989, 2006, and 2010, respectively. The spatial expansion as a consequence of increasing urban population is 108.94 km(2) over past two decades. The urban built-up in and around the city extends up to 88.71 km(2) in 1989, 144.64 km(2) in 2006, and 197.65 km(2) in 2010. These changes have attributed in elevating surface temperature in the study region. Analysis of biophysical parameters shows LST and NDBI having a positive correlation, LST and NDVI having negative correlation, while NDBI and NDWI having a perfectly negative correlation. Satellite estimated temperatures of the surface show a warming trend evident from increasing mean surface temperature values from 27.36 °C in 1989 to 30.025 °C in 2006 and 33.023 °C in 2010. The magnitude and extent of the estimates of LST are consistent with the urbanization pattern throughout the city and adjoining areas.