Natural Amenities Research Articles

Does Natural Amenity Matter on the Permanent Settlement Intention? Evidence from Elderly Migrants in Urban China.

This study focuses on the role of natural amenity in spurring the permanent settlement of elderly migrants in China, in the period from 2009 to 2017. Based on a combination of NASA’s Global Annual PM2.5 Grid data, and a nationwide China Migrants Dynamic Survey (CMDS) dataset, a binary logit model was used to investigate the settlement intention of migrants over 60 years old, across 291 cities in China. The empirical results revealed that there was a significant inverted U-shape between the annual temperature and permanent settlement, and prefectures with warmer winters and higher air quality were more attractive to elderly migrants when controlling for the urban endowment and economic conditions. In addition, the coefficient of the interaction term of air quality and precipitation was negative, indicating that the hindrance of precipitation on permanent settlement intention decreased with the enhancement in better air quality. Furthermore, there was significant group heterogeneity in the elderly’s migration reasons. The group of active movers cared more about environmental quality, whereas for the passive group, air quality had no effect on their permanent settlement.

A Spatial Analysis of Access to Physical Activity Infrastructure and Healthy Food in Regional Tasmania.

Prevalence of physical inactivity and obesity continues to increase in regional areas such as North-West (NW) Tasmania and show no signs of abating. It is possible that limited access to physical activity infrastructure (PAI) and healthier food options are exacerbating the low levels of habitual physical activity and obesity prevalence in these communities. Despite a burgeoning research base, concomitant exploration of both physical activity and food environments in rural and regional areas remain scarce. This research evaluated access (i.e., coverage, variety, density, and proximity) to physical activity resources and food outlets in relation to socioeconomic status (SES) in three NW Tasmanian communities. In all three study areas, the PAI and food outlets were largely concentrated in the main urban areas with most recreational tracks and natural amenities located along the coastline or river areas. Circular Head had the lowest total number of PAI (n = 43) but a greater proportion (30%) of free-to-access outdoor amenities. There was marked variation in accessibility to infrastructure across different areas of disadvantage within and between sites. For a considerable proportion of the population, free-to-access natural amenities/green spaces and recreational tracks (73 and 57%, respectively) were beyond 800 m from their households. In relation to food accessibility, only a small proportion of the food outlets across the region sells predominantly healthy (i.e., Tier 1) foods (~6, 13, and 10% in Burnie, Circular Head and Devonport, respectively). Similarly, only a small proportion of the residents are within a reasonable walking distance (i.e., 5–10 min walk) from outlets. In contrast, a much larger proportion of residents lived close to food outlets selling predominantly energy-dense, highly processed food (i.e., Tier 2 outlets). Circular Head had at least twice as many Tier 1 food stores per capita than Devonport and Burnie (0.23 vs. 0.10 and 0.06; respectively) despite recording the highest average distance (4.35 and 5.66 km to Tier 2/Tier 1 stores) to a food outlet. As such, it is possible that both food and physical activity environment layouts in each site are contributing to the obesogenic nature of each community.

Closed‐form solutions of an economic growth model of tourism

The economic growth model for tourism aims at optimizing the quality of life of the residents. The model is studied under the limitations of crowding conditions, environmental, and economic resources. The current value Hamiltonian function is effectively used to determine the necessary first conditions for the optimal values of consumption and number of tourists in the destination. When the necessary conditions are sufficient for optimality, the Arrow sufficient theorem provides the special case. The partial Hamiltonian approach is applied to construct the first integrals of the economic growth model for two cases. These first integrals were utilized to compute the closed‐form solution of the model under consideration. As it is well‐known, different Ramsey‐type models are solved with restrictions on the parameters. The system dynamics were studied mainly by describing the trajectories of the variables and the equilibrium, which is not enough to understand the evolution of any economy. This study is to examine the existence of closed‐form solutions for the growth model of tourism. We apply this newly developed technique to analyze the dynamics of the total income for different initial stock ratios. The effects of natural amenities on the control and state variables were also part of this study. It is also shown that crowding aversion saves the stock of natural resources and services. We offer that for the long‐term growth of the tourism, the optimal number of the tourist at the destination plays an important role.

Traffic Congestion in Rural Tourist Areas and Sustainable Mobility Services. The Case of Ticino (Switzerland) Valleys

ABSTRACT Increased traffic congestion, lower air-quality, and worsening of destination’s image perception are just some of the negative externalities affecting destinations relying on natural amenities and supplying nature-based activities. Adopting a Stated Preference experiment, this research investigates southern Switzerland natural areas’ visitors’ reaction to the hypothetical introduction of sustainable means of transport, and puts forward possible interventions to reduce the share of car users. Results show that the introduction of innovative means of transport, such as a park-and-ride integrated with a shuttle service or a bike-sharing system, might have a strong impact in reducing traffic congestion. From a sample composed by 65% of car users, results show that if innovative sustainable mobility services were introduced, market share of cars would reduce to less than 20%. Furthermore, an increase in parking cost would further decrease the use of private vehicles, in favour to alternative solutions.

Determinants of sustainability and prosperity in Indian cities

Indian cities are facing severe sustainability challenges due to rapid urbanization. In this paper, we examine whether the determinants of sustainability and prosperity of Indian cities are the same using United Nation's City Prosperity Index (CPI) framework. Since there is no Indian city in the CPI record, we construct a CPI database for Indian cities based on the available data. To overcome the drawbacks of CPI, we developed a new prosperity index named CPIx. We further develop a city sustainability index (CSIx), using CPIx methodology. We then use the scores obtained from both CPIx and CSIx to check whether the factors determining sustainability is similar to that of prosperity. Six variables from theoretical and economic geographic perspectives are considered to find their effect on city sustainability and prosperity using regression analysis. The results suggest that while income, public service, and housing have substantial positive impacts on the sustainability of Indian cities, natural amenity, and crime rate have significant negative impacts. Another notable observation from the study is that there is a high positive correlation between prosperity and sustainability of Indian cities.

Counterurbanization: A neglected pathway of forest transition.

Human settlement into rural areas (counterurbanization) is generating new patterns of reforestation, with distinctive features compared to the previously considered pathways of forest transition through “economic development” and “forest scarcity”. Here, we discuss the specific features of this neglected pathway of forest recovery and describe the process with the support of study cases around the world. This pathway includes specific motivations (e.g., natural amenities, outdoor recreation), particular socio-economic processes, conflicts between newcomers and locals, and specific ecological outcomes (e.g., a larger proportion of non-native species in the new forests). Although this pathway locally affects small areas, as a widespread and expanding process around the world, counterurbanization could have a growing global effect, with the potential to modify biodiversity, ecosystem services, and cultural values. These novel characteristics should be further explored to better understand the patterns and processes of forest transitions in a context of a globally connected world.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13280-021-01632-9.

Linking People’s Mobility and Place Livability: Implications for Rural Communities

This study integrates life-course theory and mobility research to explore livability factors that attract migrants in different age groups between rural and urban counties in the United States. Place livability is measured by economy, housing market, natural amenity, neighborhood, civic and social engagement, and health. Migrants are grouped into young, middle-aged, and older adults. Results of Structural Equation Modeling show that, as people age, the attractiveness of place shifts from a focus on the economy and housing market to the neighborhood and engagement. Rural communities, which rank the highest on engagement, attract working aged and older migrants. Natural amenities and lower housing costs also attract migrants moving to rural counties. This study suggests that the natural environment and social environment could make up for the lack of accessible physical design in rural communities. Affordable housing and an inclusive community are key to retaining and increasing the population in rural communities.

Predicting intra‐urban well‐being from space with nonlinear machine learning

AbstractThere is a growing need to analyze welfare at an intra‐urban level because cities often evince stark divisions. It is therefore important to identify inequalities within them. However, data are hardly available – or very expensive. The purpose of this article is to test whether nonlinear machine learning algorithms provide more accurate predictions of intra‐city well‐being than linear models. In addition, we aim to check if freely available and easily accessible data from Open Street Map offer an alternative to high‐resolution daytime satellite images from Google Maps in accurately predicting well‐being on a local level. Inspired by the Local Human Development Index, we construct a well‐being index based on three dimensions: health, education, and welfare. Potential predictors of well‐being include indicators related to the urbanization rate, access to natural amenities, the transportation system, and access to public transport. Four nonlinear machine learning algorithms (support vector regression with polynomial and radial kernel, random forest, and xgboost) are compared with the linear LASSO approach for the 18 districts of Warsaw, Poland. In addition, we apply innovative tools of explainable artificial intelligence (XAI) to identify the most important predictors of well‐being (measuring model‐agnostic feature importance) and to disclose the shape of relationships between well‐being and its most important predictors. We conclude that the application of nonlinear machine learning algorithms to modeling well‐being not only allows us to reach higher predictive accuracy, but also to better identify and explain the impact of its predictors.

Places of well-being in a French region. Lyon residents and their preferences

This paper seeks to reveal the key territorial components of people’s well-being. To this end, a method that makes it possible to (1) identify the components that potentially constitute well-being within a given territory and (2) determine, on the basis of individuals’ reported preferences, those areas that are most or least likely to meet these individuals’ needs has been developed and used. It reveals that natural amenities, access to health services, and safety are the most important factors for Lyon residents’ well-being. Taking as our starting point the preferred territorial components of Lyon residents, we identify the areas where their well-being would be greatest.

Reconstruction of Residential Land Cover and Spatial Analysis of Population in Bursa Region (Turkey) in the Mid-Nineteenth Century

The historic reconstruction of residential land cover is of significance to uncover the human-environment relationship and its changing dynamics. Taking into account the historical census data and cadastral maps of seven villages, this study generated residential land cover maps for the Bursa Region in the 1850s using a model based on natural constraints, land zoning, socio-economic factors and residential suitability. Two different historical reconstructions were generated; one based on a high density residential model and another based on a low density model. The simulated landcover information was used as an ancillary data to redistribute aggregated census counts to fine scale raster cells. Two different statistical models were developed; one based on probability maps and the other applying regression models including Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models. The regression models were validated with historical census data of the 1840s. From regression models, socio-economic and physical characteristics, accessibility and natural amenities showed significant impacts on the distribution of population. Model validation analysis revealed that GWR is more accurate than OLS models. The generated residential land cover and gridded population datasets can provide a basis for the historical study of population and land use.

Natural vegetation cover on private lands: locations and risk of loss in the northwestern United States

AbstractAlthough natural habitats are being lost globally, the extent and fate of natural habitats on private lands in the United States have not been quantified at the resolution relevant for conservation planning. Here we provide information on the locations and risk of loss of areas of natural vegetation cover (NVC) on private lands across the northwestern United States to motivate discussion on needs and opportunities to slow their loss. Specific questions were as follows: (1) Where are the remaining areas of NVC on private lands? (2) Which regions and communities have had the highest loss rates of NVC? and (3) In which socioecological settings is NVC at greatest risk of loss? NVC location and change were mapped using two land cover classifications during 2001–2011, the most recent period with available data. Associations between NVC loss and market proximity, demographic, infrastructure, natural amenity, and climate factors were used to model probability of NVC loss in 2011. We found that NVC covered 64% of the study area in 2011. During 2001–2011, 2.5% of the area of NVC in 2001 was converted to development and croplands. Rates of loss were as high as 12% in some regions (e.g., western Washington). Housing development accounted for the majority of this NVC loss, increasing by 8% while croplands increased by 5%. Conversion of NVC for development and crops during 2001–2011 per capita varied 20–40 fold among “city spheres” (urban areas >10,000 people and 40‐min commuting distance). NVC loss was statistically associated with urban fringe development, forest edge vegetation, proximity to highways, public land, and waterbodies and was associated with New West demographic city spheres. Of the NVC on private lands in 2011, 11% was projected to have >20% probability of future loss over the next decade. We conclude that portions of the northwestern United States, one of the last stronghold for extensive natural habitats in the contiguous United States, are rapidly losing NVC to development, particularly in the New West communities that typically have the highest motivation and capacity to conserve them.

Making the Gold Coast a Smart City—An Analysis

In recent times, there has been a worldwide trend towards creating smart cities with a focus on the knowledge economy and on information and communication technologies. These technologies have potential applications in managing the built and natural environments more efficiently, promoting economic development, and actively engaging the public, thus helping build more sustainable cities. Whilst the interest in smart cities has been widespread predominantly amongst metropolitan cities, several regional cities such as the Gold Coast in Australia have also recently endeavoured to become smart cities. In response to this emerging trend, this study aimed to investigate key opportunities and challenges associated with developing regional cities into smart cities using the Gold Coast as a case study. It identified key factors critical to the planning and development of smart cities. These factors fall under five broad themes: cultural and natural amenities, technology, knowledge and innovation precincts, people and skills, and governance. The factors were applied to the Gold Coast to analyse the key opportunities and challenges for its development into a smart city. Finally, key lessons, which are potentially applicable to other regional cities seeking to develop into smart cities, are drawn from the case study.

Resilience of environmental policy amidst the rise of conservative populism

Sustainability has for long been promoted as a medium for social and economic development, one that focuses on constant availability of natural assets and ecological amenities. By questioning the possibility of reaching a balanced and sustainable state of functioning for social-ecological systems, resilience improves the static framework of sustainability by acknowledging non-linear behavior of complex systems, inevitability of change, and consistent presence of uncertainty. At the core of sustainable development, environmental policy is embedded in the socio-spatial structures that constantly re-organize and breed uncertainty, such as political, economic, and climate uncertainty. These uncertainties create episodes of instability that shock the entire system including the structures of environmental protection. In this article, focusing on the aftermath of 2016 US presidential election and 2018 general election in Brazil, both broadly recognized as political shocks, we highlight the vulnerabilities of environmental protection structures to the rise of conservative populist movements. We attribute these vulnerabilities, partially, to the superiority of market-based instruments, as well as apolitical understandings of resilience under neoliberalism that overlook political instabilities and socio-spatial outcomes of neoliberal restructuring projects. In our assessment, political unpreparedness of sustainability against the right-wing onslaught in the US and Brazil further underlines the need for resilience theory to incorporate sources of political instability in order to protect the environment.

The spatial variation of moderating effects of density and natural amenities on housing prices in Wuhan, China

AbstractAlong with China’s rapid urbanization in major cities, how to provide better housing with amenities that residents prefer in a high‐density environment becomes an important issue for both academia and policy practitioners. The compact city debate on residents’ preferences related to density and amenities is a hot topic in China. This research investigates the moderating effects of density on natural amenity premium and housing prices in Wuhan, China. By collecting housing data through web crawling techniques, we develop regression models with interaction terms and geographically weighted regression models to find that housing prices in Wuhan are a result of the interaction of density and amenities. Negative impacts of density and positive impacts of proximity to the Yangtze and Han Rivers on housing prices lead to the moderating effects of density on the river proximity premium within 800 m from the rivers. In addition, the results show the positive impacts of urban amenities of schools, central business districts (CBDs), and metro stations on housing prices beyond 800 m from the rivers. These findings help planners develop the density approaches and amenity‐oriented land use strategy.

Considerations on Forest Changes of Northwest China in Past Seven Decades

Forests cover four billion hectares (31%) of the Earth’s landmass and contain over 75% of all carbon in vegetation. They provide renewable raw materials and natural amenities, protect land and water resources, harbor biological diversity, and mitigate climate change. However, due to less precipitation, the forest coverage rate is only 5.86% in Northwest China. The forests in these arid areas are mainly distributed in alpine areas, which play a key role in runoff regulation and ensure the ecological and economic development of the middle and lower reaches of the inland basins. In the past several decades, China had experienced large-scale deforestation and reforestation. What were the changes of the few forest areas and growing stock in arid Northwest China? Has forest quality been restored? Changes of that had been analyzed in this article. The results showed that the forest area and growing stock decreased greatly from the 1950s to 1970s; the artificial forest area increased clearly; the natural forest area stabilized from the 1980s, growing stock of forest per unit area was still lower than that in the 1950s; and the forest quality had not yet been restored. Results of the analysis of influencing factors showed that the policy-led human activities in different periods were the efficient cause of forest changes in Northwest China. With the development of forestry science, more and more attention has been paid to forest ecological restoration. “Three-North Shelter Forest Program (TNSFP)” in 1978 had made great progress on forest areas by afforestation, and the ecological benefits and economic benefits also increased remarkably owing to the increase in the artificial forest area. In recent years, great progress on forest areas has been made by afforestation, and the forests also contribute significantly to the ecology and economy. However, large-scale afforestation in the Loess Plateau had caused a phenomenon of large investment and little effect on water conservation in some afforestation areas, which showed that afforestation initiated under different polices, which were not always scientifically based, resulted in unintended consequences. Clear ecological principles should be used to ensure best environmental and forest ecology outcomes.

Understanding Impacts of Environmental Stewardship Programs through Community Geography: Pro-environment Behaviors Cultivated and Reinforced

Author(s): Lopez, Christina W; Weaver, Russell C | Abstract: Environmental Stewardship (ES) is voluntary action on behalf of the environment. ES is typically practiced at environmental nonprofit organizations that offer stewardship programs. Because these programs are managed by individual organizations, relatively little external research exists on their impacts, e.g., diffusing norms and behaviors of ES more broadly across society. Responding to that research gap, this paper studies change in the environmental outlooks and behaviors of participants at two partner nonprofits in Texas using surveys (n=407) and interviews (n=5). Three categories of changes in environmental behavior are assessed: Natural Areas, Environmental Activism, and Water Awareness. Findings demonstrate that participation was linked to pro-environmental changes in all categories for the survey respondents. Follow-up interviews allowed us to capture additional aspects of ES not addressed in the survey. In all, ES can lead to greater uptake in selected pro-environment actions, higher awareness of environmental issues, and greater appreciation for natural amenities.

Drivers of depopulation and spatial interdependence in a regional context

There is a growing consensus on the need to propose specific policies to tackle the ongoing population decline in extensive rural areas of Southern Europe. Developing policies to target this issue requires assessment of the spatial, economic and structural conditions that explain why a municipality experiences depopulation. This study explores the drivers of population growth in the municipalities of the Mediterranean region officially known as the Comunitat Valenciana in Spain. This region is relatively urbanized, so the study allows to explore the spatial interdependence between municipalities that belong to urban and rural areas, some of them subject to significant depopulation. The study's findings, based on a spatial approach, help explain the population growth of municipalities based on their interdependence with neighbouring communities. A population growth model is defined drawing on several dimensions related to population dynamics: accessibility, economic conditions, public facilities and services, natural amenities, and degree of urbanization. The findings show that population dynamics in a given municipality are influenced by its surrounding municipalities, suggesting that policies focusing on clusters of local administrative units can be central to prevent the depopulation of certain areas.

Natural amenities and skill sorting in rural communities: a case study of land conservation policy

Recent research finds evidence that improvements in rural natural amenities can increase median household income in communities close to the amenities. In this paper, a simple theoretical model is sketched out as an explanation of a hypothesized underlying mechanism: improvement in natural amenities can induce skill sorting across rural communities. Using community-level data in the state of Oregon before and after a large federal land conservation program was implemented, we test this hypothesis along with several competing mechanisms. Our empirical results support the hypothesized mechanism of amenity-induced skill sorting. Other mechanisms like the out-migration of the low-income population and the in-migration of the elderly population are not supported. The findings are important for policy discussions about land conservation, development and their distributional impacts.

Modeling fine-scale residential land price distribution: An experimental study using open data and machine learning

Modeling the fine-scale spatiotemporal distribution of residential land prices (RLPs) is the basis for scientifically allocating land resources, managing the residential market and improving urban planning. The accurate mapping of the RLP dynamics require reliable land price prediction models and data with fine spatial and temporal resolution. With the aid of point of interest (POI) data and nighttime light (NTL) images, this paper attempts to explore the ability of machine learning algorithms (MLAs) to model grid-level RLPs using the case of Wuhan in China. Several land price prediction models were built using five MLAs and various geographic variables. The experimental results show that the extra-trees regression algorithm and the radial basis function-based support vector regression algorithm perform best in Period Ⅰ (2010–2014) and Period Ⅱ (2015–2019), respectively; therefore, they were selected to estimate the RLPs of the grids without observations in the corresponding period. Based on the estimated results, we found that the spatial pattern of the RLP in Wuhan transitioned from monocentric to polycentric between the two periods, and RLPs grew rapidly near newly formed urban subcenters and waterscapes. The relative importance of the predictor variables shows that commercial and educational facilities are important determinants of the RLP distribution in Wuhan; moreover, the relative importance of natural amenities and education facilities increased over time, while that of commercial facilities and public transportation decreased slightly. The case of Wuhan confirms the feasibility of MLAs and openly accessible urban data in modeling fine-scale RLP distributions. Our proposed framework provides a new approach to monitor the urban land price dynamics accurately and closely, which is beneficial for improving the infrastructure layout and achieve smart city growth.

The Impact of Natural Amenities on Home Values in Western Colorado

This paper investigates the impact that proximity to natural amenities has on improving home values in Mesa County, Colorado. Controlling for standard home characteristics, the study investigates the value to homes of the proximity to trails, the Colorado National Monument, Bureau of Land Management Land, golf courses, the Colorado/Gunnison River, open space, and public parks, using ordinary least squares, fixed effects (controlling for time and zip codes), and a spatial error model. GIS is used to determine distances for the spatial econometric model. Each amenity is evaluated at 250, 500, and 1000 meters. The results show that homes located within 250 meters of a trail sell for 4.45% more, homes located within 500 meters of BLM land sell for 9.07% more, homes located within 250 meters of a golf course sell for 12.70% more, and homes located within 250 meters of the Colorado National Monument sell for 12.90% more.