Neighborhood Land Use Research Articles

Mapping the Land Use Changes in Cultivation Areas of Maize and Soybean from 2006 to 2017 in the North West and Free State Provinces, South Africa

Land use practices face significant pressure due to increased demand and conflicting needs. Several factors contribute to this trend, such as the ever-increasing human population, the increased demand for food production, and the expansion of industrial and agricultural areas. This paper, focused on the cultivation patterns and investigating changes in land use of maize and soybean over time (i.e., both genetically modified and non-genetically modified) in two South African provinces. The objective was to determine whether there was a net increase or decrease in land cover age for these two crops between 2006 and 2017 in the selected study areas. Hence, the study utilized ArcGIS (10.8.1) software to quantify and map the land used for the cultivation of maize and soybean from 2006 to 2017 in Free State and North West provinces. The results show both provinces to have minimal expansion or change in cultivation areas for both maize and soybean between 2006 and 2017. We concluded that both maize and soybean cultivation areas in these provinces, did not expand beyond the current agricultural areas (space), and did not encroach onto new land areas. As a result, both maize and soybean do not currently pose a threat to the surrounding landscape (i.e., natural vegetation) and are not in direct competition with other neighboring land use practices. We recommend that data on the annual planting or cultivation area be consistently gathered, analyzed, and mapped to monitor any alterations that could influence the current findings. This will also assist with any land use planning and management practices.

Traditional homegardens change to perennial monocropping of khat (Catha edulis) reduced woody species and enset conservation and climate change mitigation potentials of the Wondo Genet landscape of southern Ethiopia

Smallholder farmers in the Wondo Genet were forced to switch from long-standing, diverse traditional home gardens to monoculture khat production due to increasing population pressure-induced farmland constraints. The composition of woody species and the biomass carbon stock are thought to drop as homegardens transition from polyculture to monoculture; however there is little quantitative evidence to support this claim. This study was started to assess the effects on woody species, enset, and biomass carbon of converting traditional homegardens to a fast spreading perennial monocropping of khat (Catha edulis Forskal). In 10 m × 10 m (100m2) plots from 43 farms with neighboring land use patterns for each homegarden and khat, woody species and enset were inventoried, the total number of tree, shrub, and enset species counted, as well as the height and diameter of each species measured. To determine the biomass carbon stock of each land use type, both general and species-specific allometric equations are used. Simpson's diversity index, Shannon-Wiener, and Shannon equitability were used to evaluate the diversity of enset and woody species. There were 27 different types of woody species identified, with trees making up 67 % of the total and shrubs accounting for 33 %. Shannon, Simpson, and the richness of woody species all decreased by 46 %, 51 %, and 38 %, respectively, in comparison to residential gardens. For homegardens and khat, respectively, the mean Evenness values were 0.876 and 0.539. In homegardens, Coffea arabica was the most valuable woody species, followed by Cordia africana Lam, Persea americana, Eucalyptus camaldulensis, and Grevillea Robusta. In contrast, Catha edulis was the most valuable woody species in the Khat land use type, followed by Coffea arabica, Croton macrostachyus Del, and Cordia africana. In comparison to homegardens, the above-ground, below-ground, and total biomass carbon reported in khat land use types were reduced by 18 %, 63 %, and 42 %, respectively. Grevillea and Eucalyptus species made up 51 % of the total biomass carbon stock in the homegardens, which suggests that khat and quickly expanding fast-growing plants have displaced native woody species.Understanding the long-term effects of agro-biodiversity loss requires greater research on the implications of the decline in woody species diversity and biomass carbon stock on soil fertility and sustainable farming. This is due to the numerous functions that woody species and enset play.

Urban Space, Mixed Land Use, and Residential Land Prices: A Case Study of Nanjing, China

Residential land price is a critical component of housing prices and affordability, and existing studies of its influencing factors emphasize location and accessibility. This study analyzes the effects of neighborhood land use, especially employment and services, on residential land prices in Nanjing, a subcenter in the Yangtze River Delta region, China. We find that residential land prices are positively associated with producer services, as well as public and commercial services, and negatively associated with manufacturing. Further analysis reveals the spatial heterogeneity of the impact of manufacturing on residential land prices, which become positive in suburban regions. The effects of neighborhood land use on residential land prices are sensitive to the distance to the central business district. The geographically and temporally weighted regression model uncovers the temporal heterogeneity that the positive impacts of public and commercial services on residential land prices have been decreasing while the producer service is playing a more significant role. The results of this study contribute to the literature by shedding light on the impact of neighborhood land use on residential land prices based on spatial-temporal dynamics.

Neighborhood Land Use, Work Participation, and Quality of Life Among Workers in Mid and Late Life: Exploratory Analysis of Singapore’s Public Housing Neighborhoods

Neighborhood environments have been positively associated with older adults’ engagement outcomes. As mid- and late-life work participation gains traction, the scope of productive engagement in later life expands concomitantly. However, current age-friendly neighborhood paradigms remain largely retirement-centric, with minimal applicability for older adults with work aspirations. Therefore, the objective of this research was to examine whether neighborhood land use had significant impact on older adults’ work participation and well-being while working. Neighborhood variables were measured at the postal code level and statistically analyzed in relation to work participation and quality of life (QOL) scores for 850 older adults in Singapore. Significant variables were evaluated again for 28 planning areas, and statistically analyzed in relation to workforce participation rates. The findings suggest that neighborhood spatial attributes are significant for mid- and late-life work participation: Strategic provision of amenities was associated with individual work participation and well-being, while density and distribution of specific land-use types were associated with workforce participation rates. The article concludes with a discussion on the gaps in planning approaches for work-supportive and age-friendly neighborhood paradigms.

Development of transferable neighborhood land use regression models for predicting intra-urban ambient nitrogen dioxide (NO2) spatial variations.

Land use regression (LUR) models have been extensively used to predict air pollution exposure in epidemiological and environmental studies. The lack of dense routine monitoring networks in big cities places increased emphasis on the need for LUR models to be developed using purpose-designed neighborhood-scale monitoring data. However, the unsatisfactory model transferability limits these neighborhood LUR models to be then applied to other intra-urban areas in predicting air pollution exposure. In this study, we tackled this issue by proposing a method to develop transferable neighborhood NO2 LUR models with comparable predictive power based on only micro-scale predictor variables for modeling intra-urban ambient air pollution exposure. Taking Auckland metropolis, New Zealand, as a case study, the proposed method was applied to three neighborhoods (urban, central business district, and dominion road) and compared with the corresponding counterpart models developed using pools of (a) only macro-scale predictor variables and (b) a mixture of both micro- and macro-scale predictor variables (traditional method). The results showed that the models using only macro-scale variables achieved the lowest accuracy (R2: 0.388-0.484) and had the worst direct (R2: 0.0001-0.349) and indirect transferability (R2: 0.07-0.352). Those models using the traditional method had the highest model fitting R2 (0.629-0.966) with lower cross-validation R2 (0.495-0.941) and slightly better direct transferability (R2: 0.0003-0.386) but suffered poor model interpretability when indirectly transferred to new locations. Our proposed models had comparable model fitting R2 (0.601-0.966) and the best cross-validation R2 (0.514-0.941). They also had the strongest direct transferability (R2: 0.006-0.590) and moderate-to-good indirect transferability (R2: 0.072-0.850) with much better model interpretability. This study advances our knowledge of developing transferable LUR models for the very first time from the perspective of the scale of the predictor variables used in the model development and will significantly benefit the wider application of LUR approaches in epidemiological and environmental studies.

How does the length of residence in a neighborhood vary the effects of neighborhood land use on commuting trip time and mode choice?

How does the length of residence in a neighborhood vary the effects of neighborhood land use on commuting trip time and mode choice?

Technical and economic analysis of potential steam supply from waste treatment plants to industries in Aichi Prefecture, Japan

Waste-to-energy treatment is an efficient energy recovery method and an important countermeasure against global warming. The supply of steam from waste treatment plants to industrial sectors presents a higher energy recovery efficiency than traditional waste-to-energy methods. However, its technical potential and economic benefits are not fully understood by policymakers. Furthermore, the regional characteristics and effects of neighboring land use, which affect the heat supply and demand, are not commonly analyzed. Therefore, this study evaluates the spatial steam demand of industries in the Aichi Prefecture by using the steam demand unit value per production shipment and the spatial value of manufactured goods shipments. In addition, this study evaluates the steam supply potential from waste treatment plants to industrial sectors based on the estimated spatial steam demand and the transportable distances. The results show that the steam supply from waste treatment plants to the industries has a great physical potential in Aichi Prefecture. From a cost–benefit perspective, plans considering a 1 km range can be profitable, but the profitability decreases as the distance increases and the no-profitability mesh number increases. To improve the energy recovery efficiency from waste, the location of waste treatment plant should be changed, and the efficiency of steam transport on both supply and demand sides should be increased.

Relationship between neighborhood land use structure and the spatiotemporal pattern of PM2.5 at the microscale: Evidence from the central area of Guangzhou, China

Fine particulate matter (PM2.5) is harmful to human health. Although the relationship between urban land use and PM2.5 has been studied in recent years, there has been little consideration of the relationship between land use structure and PM2.5 spatiotemporal patterns at the microscale. Based on mobile monitoring PM2.5 data and point of interest data, this paper explored their relationship with a classification and regression tree model. The results showed that PM2.5 exhibits spatiotemporal heterogeneity at the microscale. The neighborhoods’ land use structure can explain 60.4% of the PM2.5 spatiotemporal patterns. Transportation and ecology are the two most significant land use types that correlated with PM2.5 spatiotemporal patterns. Fourteen rules of neighborhood land use structures with different land use types are identified land use structure which leads to different spatiotemporal patterns of PM2.5. The higher the PM2.5 risk, the stronger the correlation with neighborhood land use structure is. The classification and regression tree model can be effectively used to judge the relationship between neighborhood land use structure and PM2.5 spatiotemporal patterns. The results provide a basis for developing appropriate measures, based on local conditions, to predict PM2.5 pollution levels at the microscale, and reduce the risk of neighborhood exposure to PM2.5.

Development and implementation of a qualitative framework for the sustainable management of wine companies

A growing number of companies around the world have already adopted sustainable practices as the majority of consumers are increasingly concerned with environmental and health issues. Despite this, lack of knowledge in sustainability can represent a limit to a sustainable conversion of Italian wine companies.This paper focuses on the development and suitability assessment of TERRITORY, a qualitative framework that assists sustainable management of winery farms with respect to biodiversity, neighbouring land use, agrochemical use, soil management, water management, landscape, site selection, heritage-cultural and aesthetic aspects, product quality and safety, human resource management, health of employees, community and consumers, economic repercussion of structures and territories, resource depletion, procurement practices and traceability. 47 wine companies have adopted the framework and its suitability has been tested and validated in a ten years trial. The present work reports the results of TERRITORY framework adoption in a winemaking cooperative, a grape and wine producer and a bottling firm, that respectively performed 76%, 92%, 62% (where 100% is maximum implementation of sustainable practices), with lower adherence in water, landscape and human resources management. The framework has driven wine companies towards improvements implementation: most relevant deal with a more effective communication to local community and consumers about health and safety, protection of biodiversity (towards a deeper knowledge of its territorial features), territorial values enforcement and improved communication. From the results it emerges that the framework guides the structural transformation of wine farms towards sustainable production and management by assisting the wine producers in identifying emerging opportunities in wine sector, such as fostering network with local communities, defining better soil, and water management through a multi-actor approach. Furthermore, it has been adopted in addressing the selection of quantitative indicators to adopt and monitoring campaigns.

A novel cellular automata model integrated with deep learning for dynamic spatio-temporal land use change simulation

Land use change (LUC) exhibits obvious spatio-temporal dependency. Previous cellular automata (CA)-based methods usually treated the LUC dynamics as Markov processes and proposed a series of CA-Markov models, which however, were intrinsically unable to capture the long-term temporal dependency. Meanwhile, such models used only numerical proportion of neighboring land use (LU) types to represent neighborhood effects of LUC, which inevitably neglected the complicated spatial heterogeneity and thus caused inaccurate simulation results. To address these problems, this paper presents a novel CA model integrated with deep learning (DL) techniques to model spatio-temporal LUC dynamics. Our DL-CA model firstly uses a convolutional neural network to capture latent spatial features for complete representation of neighborhood effects. A recurrent neural network then extracts historical information of LUC from time-series land use maps. A random forest is appended as binary change predictor to avoid the imbalanced sample problem during model training.Land use data collected from 2000 to 2014 of the Dongguan City, China were used to verify our proposed DL-CA model. The input data from 2000 to 2009 were used for model training, the 2010 data for model validation, and the data collected from 2011 to 2014 were used for model evaluation. In addition, four traditional CA models of multilayer perceptron (MLP)-CA, support vector machine (SVM)-CA, logistic regression (LR)-CA and random forest (RF)-CA were also developed for accuracy comparisons. The simulation results demonstrate that the proposed DL-CA model accurately captures long-term spatio-temporal dependency for more accurate LUC prediction results. The DL-CA model raised prediction accuracy by 9.3%–11.67% in 2011–2014 in contrast to traditional CA models.

ENVIRONMENTAL SAFETY IN THE AVIATION INDUSTRY: CURRENT PROBLEMS AND SOLUTION WAYS

Experts and specialists from the International Civil Aviation Organization (ICAO Council) and itsmember states, as well as stakeholders, have for 70 years combined their collective knowledge and researchto create a normative framework that has passed the test of time and have to be relevant today. It is worthmentioning that since 1992 Ukraine has been a member of the ICAO Council. That is why the «AviationTransport Strategy of Ukraine for the period up to 2030» provisions stipulate important tasks in thefield of development of domestic aviation, which in turn affects the global (world) development network.Since the 1970s, the environment work of the ICAO Council has been highlighted the value of a global,harmonized approach to addressing the consequences of the dangerous effects of airports on neighboringland use, airspace and integrated work of the ecosystem. The article is devoted to the analysis of the basicprinciples of the ecologically safe land use of aviation transport, as well as the substantiation of modernproblems of environmental safety in this area and ways to solve them. The issue of choosing a suitableland for the construction and operation of a new airport or the formation of existing aviation land-use forexpansion of the airport’s reconstruction is quite serious during the period of globalization and the rapiddevelopment of urbanized territories. Persons who are interested in developing such a project should, firstof all, clearly predict its further ecologically safe activities in compatibility with other adjacent land uses. The basic requirements of compliance with the norms and rules in the formation of the environmental component of efficient, rational land use of aviation transport have been developed.

Park green spaces, public health and social inequalities: Understanding the interrelationships for policy implications

How to reduce neighborhood socioeconomic status- (SES-) related health inequalities has been prioritized in the recent political literature. Park green spaces (PGSs) are essential neighborhood land use assets, as they are beneficial for population health and thus should mitigate SES-related health inequalities. This paper aims to elaborate the knowledge on the complex interrelationships among PGSs, health outcomes and social inequalities through developing a set of mixed indicators in an integrated manner. The data are obtained at the community level (N=8117) for three health outcomes (cardiopathy, chronic pneumonia and hypertension) and five SES variables. The PGS characteristics are described from three dimensions (coverage, quality and accessibility) at two geographical levels (15-minute walking distance (15 WD) neighborhoods and 30-minute walking distance (30 WD) neighborhoods). Spatial regressions reveal the following: 1) socioeconomically disadvantaged communities enjoy fewer PGSs and limited access to parks of high quality; 2) socioeconomically disadvantaged communities present higher incidences of diseases; and 3) PGS coverage within 30 WD neighborhoods and PGS accessibility within 15 WD neighborhoods are related to health outcomes. Structural equation modeling further confirms that PGSs, especially those of higher quality, could mitigate SES-related health inequalities. The findings of this study highlight the necessity of improving the PGS quality within walking distance of socioeconomically disadvantaged communities. We thus argue that land use policy makers should collaborate with social researchers and health professionals; and through health impact assessment, they can translate the professional knowledge into land use planning and consider health promotion into land use policies.

The Relation of Neighbouring Land Use Type and Sedimentary Characteristics of Fluvial Sediments in Tropical Rivers

This study investigates the relationship between land use types and sedimentary characteristics of fluvial bed at three rivers in Selangor, Malaysia; namely Sungai Tengi, Selangor and Langat. The diversity in population density and land development at the adjacent river banks gives associated dominant land use type as forest, agriculture and urban for Tengi, Selangor and Langat, respectively. Field sampling was conducted at consistent spatial locations for Tengi and Selangor, whereas for Langat, the bed sediment was taken at non-uniform spatial points due to limited access. Statistical analysis of the sediment bed mixture shows that forest dominated land gives finer bed sediment size at 650 μm. Correlation analysis proved that there is a relationship between types of land use with the mean sediment size. No distinctive correlation can be observed for sorting, skewness and kurtosis of the sediment with the types of land use.

How reliable is my historical land-use reconstruction? Assessing uncertainties in old cadastral maps

Old maps are a fundamental source for land-use reconstruction frequently used in biodiversity conservation and environmental management. In particular, cadastral maps as one type of old maps, depict both land tenure (discrete category) and land-use (continuous category); thus resulting in uncertainties in determination of individual parcels and their use. These uncertainties pose fundamental questions that are addressed in this paper: (i) to what extent land-use determined the delimitation of parcels?; (ii) how significant did the contrast between two land-use classes have to be to in order to delineate a new boundary? Agroforestry land-use classes were chosen as an example to demonstrate the approaches in the delimitation of parcels among different land-use combinations. We used Franciscan Cadastre, created in the mid-19th century under the Habsburg Monarchy (Central Europe), which depicts up to 10 agroforestry classes, to analyse factors that could influence delimitation of borders between patches (parcels) in old cadastral maps. The study area was located in the rural landscape of N Czechia, where approximately 10% of the agroforestry land area was used. We based our analysis on a detailed database of parcels and their land use type and property information. The novel approach to patch contrast indicator for old map analyses is introduced. The approach is based on statistical testing of the differences between parcel boundaries, separating similar/different owner, similar/different land-use and considering the length of the boundaries. Total number of identified parcels for all districts was 4108. Half of the boundaries length and 60% of boundaries count separated land of different owners. The rest of them separated land of one owner with different owner or with distinct parcels geometry. Our results indicate variable contrast between pairs of neighbouring land use categories. In particular, the contrast between pastures, wood-pastures and forests proved to be very low. Various factors, including land ownership, land-use, as well as landscape patch geometry and configuration were important to delineate a single parcel. We have concluded that these factors have important implications on inaccuracies and uncertainties of land use reconstructions based on old cadastral maps and used as historical baselines for current considerations on land change and environmental management.

A methodological Markov-CA projection of the greening agricultural landscape-a case study from 2005 to 2017 in southwestern Finland.

The aim of the reformed EU Common Agricultural Policy (CAP) 2014-2020 is to enhance greening via an ecological focus area, arable crop diversification, and the maintenance of permanent grasslands. This study tests the greening process in the case of agricultural landscape in southwestern Finland by projecting land use between 2005 and 2017. The study method integrates the quantitative results of Markov chains and spatial features of a cellular automata model. Initially, land use change was recognized by appropriate metrics. The trend of greening following the CAP policy indicated that permanent grassland patches were more persistent with forest patches than agricultural land that lost its vegetated strips to neighboring land use patches. The modeling approach was demonstrated to provide acceptable performance when used as a spatial assessment tool for observing critical patch level changes reflecting the greening agricultural policy.

Talking about density: An empirical investigation of framing

Scholars of cities have presented evidence that increasing the density of urban areas in western countries is key to accomplishing greater sustainability in the built environment. Technical knowledge of sprawl’s negative impacts may well convince local planners of the benefits of denser development, but planners likely face challenges in communicating the benefits of densification to their constituents. When planners cite certain benefits over others, they effectively frame densification in ways that may or may not resonate with the values of their constituents. This paper evaluates the efficacy of seven commonly elicited frames for densification. We evaluate factors impacting constituent reception of densification as presented through each frame including: (1) constituent familiarity with each frame, (2) a variety of demographic and political factors, and (3) neighborhood land use and density in the area where increased density is proposed. We find that planners prompt each of the frames with different associated rates of success or failure across communities of different demographics, and that residential neighborhoods of eight (8) or fewer dwelling units per acre (3.24 or fewer units per hectare) are especially less likely to support densification regardless of the elicited frame. We also find that constituent familiarity with a given frame is always associated with increased support for densification, but occasionally with widespread doubt in planners’ arguments as well.

A comparative approach to modelling multiple urban land use changes using tree-based methods and cellular automata: the case of Greater Tokyo Area

ABSTRACTUrban multiple land use change (LUC) modelling enables the realistic simulation of LUC processes in complex urban systems; however, such modelling suffers from technical challenges posed by complicated transition rules and high spatial heterogeneity when predicting the LUC of a highly developed area. Tree-based methods are powerful tools for addressing this task, but their predictive capabilities need further examination. This study integrates tree-based methods and cellular automata to simulate multiple LUC processes in the Greater Tokyo Area. We examine the predictive capability of 4 tree-based models – bagged trees, random forests, extremely randomised trees (ERT) and bagged gradient boosting decision trees (bagged GBDT) – on transition probability prediction for 18 land use transitions derived from 8 land use types. We compare the predictive power of a tree-based model with multi-layer perceptron (MLP) and among themselves. The results show that tree-based models generally perform better than MLP, and ERT significantly outperforms the three other tree-based models. The outstanding predictive performance of ERT demonstrates the advantages of introducing bagging ensemble and a high degree of randomisation into transition probability modelling. In addition, through variable importance evaluation, we found the strongest explanatory powers of neighbourhood characteristics for all land use transitions; however, the size of the impacts depends on the neighbourhood land use type and the neighbourhood size. Furthermore, socio-economic and policy factors play important roles in transitions ending with high-rise buildings and transitions related to industrial areas.

Incorporating land use and pricing policies for reducing car dependence: Analytical framework and empirical evidence

This article develops an analytical framework to connect the theories of market and planning failures with the reasoning of incorporating land use and pricing policies for reducing driving and car dependence. A multilevel multinomial logit model (MML) is applied to estimate the effects of neighbourhood land use characteristics and price variables on travel mode choice of non-work trips and their interaction effects in the city of Austin, Texas. Results reveal that pricing policies are more efficient for reducing auto travel while land use policies appear better for adjusting non-auto travel. The practical significance of land use policies for reducing car dependence are more reflected in the modified effects of land use on pricing elasticities of driving probability. Pricing policies are more effective for reducing driving in neighbourhoods with a higher sidewalk density and a better accessibility to mixed-use activity centres. These findings validate the theoretical analysis and demonstrate the importance of coordinating land use and pricing policies together in the transportation planning practice.

Neighbourhood land use features, collective efficacy and local civic actions

This paper explores the association between neighbourhood land use features and informal social control. More specifically, we examine the extent to which such features in combination with the socio-demographic context of the neighbourhood facilitate or impede collective efficacy and local civic actions. We achieve this through spatially integrating data from the census, topographic databases and a 2012 survey of 4132 residents from 148 neighbourhoods in Brisbane, Australia. The study creates a new classification of a neighbourhood’s physical environment by creating novel categories of land use features that depict social conduits, social holes and social wedges. Social conduits are features of the neighbourhood that facilitate interaction between individuals, social holes are land uses that create situations where there is no occupancy, and social wedges are features that carve up neighbourhoods. We find some evidence to suggest that residents’ reports of collective efficacy are higher in neighbourhoods with a greater density of social conduits. Density of social conduits is also positively associated with local civic action. However, in neighbourhoods with more greenspace, residents are less likely to engage in local civic actions.

Do Inequalities in Neighborhood Walkability Drive Disparities in Older Adults' Outdoor Walking?

Older residents of high-deprivation areas walk less than those of low-deprivation areas. Previous research has shown that neighborhood built environment may support and encourage outdoor walking. The extent to which the built environment supports and encourages walking is called “walkability”. This study examines inequalities in neighborhood walkability in high- versus low-deprivation areas and their possible influences on disparities in older adults’ outdoor walking levels. For this purpose, it focuses on specific neighborhood built environment attributes (residential density, land-use mix and intensity, street connectivity, and retail density) relevant to neighborhood walkability. It applied a mixed-method approach, included 173 participants (≥65 years), and used a Geographic Information System (GIS) and walking interviews (with a sub-sample) to objectively and subjectively measure neighborhood built environment attributes. Outdoor walking levels were measured by using the Geographic Positioning System (GPS) technology. Data on personal characteristics was collected by completing a questionnaire. The results show that inequalities in certain land-use intensity (i.e., green spaces, recreation centers, schools and industries) in high- versus low-deprivation areas may influence disparities in older adults’ outdoor walking levels. Modifying neighborhood land use intensity may help to encourage outdoor walking in high-deprivation areas.