Exploring geomasking methods for geoprivacy: a pilot study in an environment with built features

This study discusses the ethical use of geographical information systems (GIS) data with a focus on geomasking for upholding locational privacy. As part of a pilot study in Jeddah City, Saudi Arabia, we used open-source geomasking methods to ensure geoprivacy while examining built environment features that determine the quality of life among individuals with type-II diabetes. We employed the open-source algorithms Maskmy.XYZ and NRand-k for geomasking 329 data points. The results showed no differences between global and city-level spatial patterns, but significant variations were observed with respect to local patterns. These findings indicate the promising potential of the chosen geomasking technologies with respect to ensuring locational privacy but it was noted that further improvements are needed. We recommend developing enhanced algorithms and conducting additional studies to minimize any negative impact of geomasking in spatial analysis with the overall aim of achieving a better understanding of ethical considerations in GIS sciences. In conclusion, application of geomasking is straightforward and can lead to enhanced use for privacy protection in geospatial data analysis.

Energy Retrofitting for the Modern Heritage Enhancement in Weak Real Estate Markets: The Olivetti Housing Stock in Ivrea

The enhancement of Modern Heritage buildings is nowadays a challenging issue as they are often degraded or abandoned and their historical value is not well acknowledged by potential buyers and their owners. Moreover, they are usually energy inefficient and obsolete, but investments for energy retrofit interventions are not always convenient, especially in socio-economic contexts characterized by weak real-estate market dynamics. This paper aims to study the influence of intrinsic and extrinsic characteristics on housing prices and, in particular, to understand whether elements of building cultural connotations or some housing green features are monetized by the real estate market. The UNESCO site “Ivrea, industrial city of the 20th century”, located in the weak real-estate context of the Eporediese territorial area, was selected as an emblematic case study and two data samples of property listings were built to perform spatial regression analyses. The results showed that the green features of housing, such as the heating type and the EPC level, have a greater influence on property prices than those characteristics related to the cultural connotations of a building, such as the Olivettian context. Therefore, the current incentive-based policies for energy efficiency can represent great opportunities that can be exploited both to preserve and to improve the condition of this valuable Modern Heritage.

Exploring Spatio-Temporal Patterns of Urban Village Redevelopment: The Case of Shenzhen, China

The redevelopment of urban villages is a prominent part of urban renewal in China, which has attracted much attention from the academic community. However, the understanding of when and where the redevelopment of urban villages occurs is still limited partly because of the lack of empirical analysis. Through exploratory spatial data and overlay analyses, this study examines the spatio-temporal distribution characteristics based on data from 277 urban village redevelopment projects in Shenzhen, China, between 2010 and 2018. Results demonstrate that the redevelopment of urban villages occurs in central and suburban areas but rarely occurs in the periphery of the city. The overall spatial distribution is spatially clustered, having become increasingly significant from 2010 to 2018. In the beginning, the redevelopment of urban villages was dispersed in diverse areas and partly expanded into adjacent neighbourhoods. A majority of redevelopment took place in areas near the planning urban centres and the planning subway stations, which are almost in Density Zones I–III. The findings of this study contribute to new spatio-temporal perspectives in the global process mechanism of urban village redevelopment and call for special attention to the significant influences of state intervention, which is an informative reference for future sustainable urban development.

Geodemographies of Breastfeeding Support

BACKGROUND

Mother-to-mother breastfeeding support organizations provide important information and guidance for helping mothers initiate and maintain breastfeeding, postpartum. However, the availability of this support is limited by a constellation of barriers, including race, culture, socioeconomic status, and geography.

RESEARCH AIMS

To identify the geodemographic composition of communities where breastfeeding support was available from the mother-to-mother support organizations Breastfeeding USA and La Leche League, identify underlying issues of equity, and highlight locations where more support resources may be needed.

METHODS

The locations of mother-to-mother support meetings were collected by ZIP code (N = 180) and were combined with a geodemographic database and exploratory spatial data analysis to explore the compositional characteristics of communities served (N = 1,173).

RESULTS

Significant gaps in the geographic distribution of breastfeeding support existed. While many metropolitan areas benefited from numerous mother-to-mother support groups and peer counselors, the geographic footprint of this support favored communities that were white, affluent, and suburban.

CONCLUSION

Spatial analytics combined with geodemographic analysis provide a unique perspective into the diverse landscape of mother-to-mother breastfeeding support groups at a local level. Our results highlighted inequities in the distribution of support provided and prescriptive guidance regarding where more resources may be needed.

The Optimization Strategy of the Existing Urban Green Space Soil Monitoring System in Shanghai, China

High concentrations of potentially toxic elements (PTE) create global environmental stress due to the crucial threat of their impacts on the environment and human health. Therefore, determining the concentration levels of PTE and improving their prediction accuracy by sampling optimization strategy is necessary for making sustainable environmental decisions. The concentrations of five PTEs (Pb, Cd, Cr, Cu, and Zn) were compared with reference values for Shanghai and China. The prediction of PTE in soil was undertaken using a geostatistical and spatial simulated annealing algorithm. Compared to Shanghai’s background values, the five PTE mean concentrations are much higher, except for Cd and Cr. However, all measured values exceeded the reference values for China. Pb, Cu, and Zn levels were 1.45, 1.20, and 1.56 times the background value of Shanghai, respectively, and 1.57, 1.66, 1.91 times the background values in China, respectively. The optimization approach resulted in an increased prediction accuracy (22.4% higher) for non-sampled locations compared to the initial sampling design. The higher concentration of PTE compared to background values indicates a soil pollution issue in the study area. The optimization approach allows a soil pollution map to be generated without deleting or adding additional monitoring points. This approach is also crucial for filling the sampling strategy gap.

EPC Labels and Building Features: Spatial Implications over Housing Prices

The influence of building or dwelling energy performance on the real estate market dynamics and pricing processes is deeply explored, due to the fact that energy efficiency improvement is one of the fundamental reasons for retrofitting the existing housing stock. Nevertheless, the joint effect produced by the building energy performance and the architectural, typological, and physical-technical attributes seems poorly studied. Thus, the aim of this work is to investigate the influence of both energy performance and diverse features on property prices, by performing spatial analyses on a sample of housing properties listed on Turin’s real estate market and on different sub-samples. In particular, Exploratory Spatial Data Analyses (ESDA) statistics, standard hedonic price models (Ordinary Least Squares—OLS) and Spatial Error Models (SEM) are firstly applied on the whole data sample, and then on three different sub-samples: two territorial clusters and a sub-sample representative of the most energy inefficient buildings constructed between 1946 and 1990. Results demonstrate that Energy Performance Certificate (EPC) labels are gaining power in influencing price variations, contrary to the empirical evidence that emerged in some previous studies. Furthermore, the presence of the spatial effects reveals that the impact of energy attributes changes in different sub-markets and thus has to be spatially analysed.

Spatial analysis and GIS mapping of regional hotspots and potential health risk of fluoride concentrations in groundwater of northern Tanzania

Safe drinking water supply systems in naturally contaminated hydrogeological environments require precise geoinformation on contamination hotspots. Spatial statistical methods and GIS were used to study fluoride occurrence in groundwater and identify significant spatial patterns using fluoride concentrations. The global and local Morans I indices were used. While the significant positive global Morans I index indicated spatial structure in fluoride occurrence, the significant spatial clusters were identified using local Morans I index and mapped at p-value of 0.05. The spatial clusters demonstrated patterns of drinking water sources with fluoride concentrations below or above WHO guideline and Tanzania standard for drinking water and were considered as 'regional fluoride cool spots' and 'regional fluoride contamination hotspots', respectively. Two regional fluoride contamination hotspots were identified and mapped around the Stratovolcano Mountains in the north-east and south-west of the study area; and along the Neogene Quaternary volcanic formations and Palaeo-Neoproterozoic East African Orogen (Mozambique Belt). The two largest regional fluoride cool spots dominated the major and minor rift escarpments in the west and east of the study area respectively while the small ones emerged around the volcanic mountains in the north and south. Furthermore, significant spatial outliers emerged at the boundary of regional fluoride hotspots and cool spots as an indication of the spatial processes controlling the mobilization of fluoride in groundwater. While all water sources in the cool spots had fluoride concentrations below 1.5 mg/L, some had extremely low concentrations below 0.5 mg/L which is not safe for human consumption. For hotspots, 96% of water sources had fluoride concentrations above 1.5 mg/L. The probability of having safe source of drinking water varied from one geological unit to another with sources in the Neogene Quaternary volcanic formations having least probabilities.

Placement of Infrastructure for Urban Electromobility: A Sustainable Approach

Over the last few years, electric vehicles (EVs) have turned into viable urban transportation alternatives. Charging infrastructure is an issue, since high investment is needed and there is a lot of demand uncertainty. Seeking to fill gaps in past studies, this investigation proposes a set of procedures to identify the most adequate places for implementing the EV charging infrastructure. In order to identify the most favorable districts for the installation and operation of electric charging infrastructure in São Paulo city, the following public available information was considered: the density of points of interest (POIs), distribution of the average monthly per capita income, and number of daily trips made by transportation mode. The current electric vehicle charging network and most important business corridors were additionally taken into account. The investigation shows that districts with the largest demand for charging stations are located in the central area, where the population also exhibits the highest purchasing power. The charging station location process can be applied to other cities, and it is possible to use additional variables to measure social inequality.

Urban Vibrancy: An Emerging Factor that Spatially Influences the Real Estate Market

Urban vibrancy is defined and measured differently in the literature. Originally, it was described as the number of people in and around streets or neighborhoods. Now, it is commonly associated with activity intensity, the diversity of land-use configurations, and the accessibility of a place. The aim of this paper is to study urban vibrancy, its relationship with neighborhood services, and the real estate market. Firstly, it is used a set of neighborhood service variables, and a Principal Component Analysis is performed in order to create a Neighborhood Services Index (NeSI) that is able to identify the most and least vibrant urban areas of a city. Secondly, the influence of urban vibrancy on the listing prices of existing housing is analyzed by performing spatial analyses. To achieve this, the presence of spatial autocorrelation is investigated and spatial clusters are identified. Therefore, spatial autoregressive models are applied to manage spatial effects and to identify the variables that significantly influence the process of housing price determination. The results confirm that housing prices are spatially autocorrelated and highlight that housing prices and NeSI are statistically associated with each other. The identification of the urban areas characterized by different levels of vibrancy and housing prices can effectively support the revision of the urban development plan and its regulatory act, as well as strategic urban policies and actions. Such data analyses support a deep knowledge of the current status quo, which is necessary to drive important changes to develop more efficient, sustainable, and competitive cities.

Spatially exploring the intersection of socioeconomic status and Canadian cancer-related medical crowdfunding campaigns

OBJECTIVES

Medical crowdfunding is a rapidly growing practice where individuals leverage social networks to raise money for health-related needs. This practice has allowed many to access healthcare and avoid medical debt but has also raised a number of ethical concerns. A dominant criticism of this practice is that it is likely to increase inequities in access to healthcare if persons from relatively wealthy backgrounds, media connections, tech-savvy and educational attainments are best positioned to use and succeed with crowdfunding. However, limited data has been published to support this claim. Our objective in this paper is to assess this concern using socioeconomic data and information from crowdfunding campaigns.

SETTING

To assess this concern, we present an exploratory spatial analysis of a new dataset of crowdfunding campaigns for cancer-related care by Canadian residents.

PARTICIPANTS

Four datasets were used: (1) a medical crowdfunding dataset that included cancer-related campaigns posted by Canadians, (2) 2016 Census Profile for aggregate dissemination areas, (3) aggregate dissemination area boundaries and (4) forward sortation area boundaries.

RESULTS

Our exploratory spatial analysis demonstrates that use of crowdfunding for cancer-related needs in Canada corresponds with high income, home ownership and high educational attainment. Campaigns were also commonly located near city centres.

CONCLUSIONS

These findings support concerns that those in positions of relative socioeconomic privilege disproportionately use crowdfunding to address health-related needs. This study was not able to determine whether other socioeconomic dimensions such as race, gender, ethnicity, nationality and linguistic fluency are also correlated with use of medical crowdfunding. Thus, we call for further research to explore the relationship between socioeconomic variables and medical crowdfunding campaigning to explore these other socioeconomic variables and campaigns for needs unrelated to cancer.

Community Rates of Breastfeeding Initiation

BACKGROUND

Breastfeeding initiation rates vary considerably across racial and ethnic groups, maternal age, and education level, yet there are limited data concerning the influence of geography on community rates of breastfeeding initiation.

OBJECTIVE

This study aimed to describe how community rates of breastfeeding initiation vary in geographic space, highlighting "hot spots" and "cool spots" of initiation and exploring the potential connections between race, socioeconomic status, and urbanization levels on these patterns.

METHODS

Birth certificate data from the Kentucky Department of Health for 2004-2010 were combined with county-level geographic base files, Census 2010 demographic and socioeconomic data, and Rural-Urban Continuum Codes to conduct a spatial statistical analysis of community rates of breastfeeding initiation.

RESULTS

Between 2004 and 2010, the average rate of breastfeeding initiation for Kentucky increased from 43.84% to 49.22%. Simultaneously, the number of counties identified as breastfeeding initiation hot spots also increased, displaying a systematic geographic pattern in doing so. Cool spots of breastfeeding initiation persisted in rural, Appalachian Kentucky. Spatial regression results suggested that unemployment, income, race, education, location, and the availability of International Board Certified Lactation Consultants are connected to breastfeeding initiation.

CONCLUSION

Not only do spatial analytics facilitate the identification of breastfeeding initiation hot spots and cool spots, but they can be used to better understand the landscape of breastfeeding initiation and help target breastfeeding education and/or support efforts.

Exploring the mechanisms of ecological land change based on the spatial autoregressive model: a case study of the Poyang Lake Eco-Economic Zone, China

Ecological land is one of the key resources and conditions for the survival of humans because it can provide ecosystem services and is particularly important to public health and safety. It is extremely valuable for effective ecological management to explore the evolution mechanisms of ecological land. Based on spatial statistical analyses, we explored the spatial disparities and primary potential drivers of ecological land change in the Poyang Lake Eco-economic Zone of China. The results demonstrated that the global Moran's I value is 0.1646 during the 1990 to 2005 time period and indicated significant positive spatial correlation (p < 0.05). The results also imply that the clustering trend of ecological land changes weakened in the study area. Some potential driving forces were identified by applying the spatial autoregressive model in this study. The results demonstrated that the higher economic development level and industrialization rate were the main drivers for the faster change of ecological land in the study area. This study also tested the superiority of the spatial autoregressive model to study the mechanisms of ecological land change by comparing it with the traditional linear regressive model.

Spatial statistical methods in health

The study of the geographical distribution of disease incidence and its relationship to potential risk factors (referred to here as "geographical epidemiology") has provided, and continues to provide, rich ground for the application and development of statistical methods and models. In recent years increasingly powerful and versatile statistical tools have been developed in this application area. This paper discusses the general classes of problem in geographical epidemiology and reviews the key statistical methods now being employed in each of the application areas identified. The paper does not attempt to exhaustively cover all possible methods and models, but extensive references are provided to further details and to additional approaches. The overall aim is to provide a picture of the "current state of the art" in the use of spatial statistical methods in epidemiological and public health research. Following the review of methods, the main software environments which are available to implement such methods are discussed. The paper concludes with some brief general reflections on the epidemiological and public health implications of the use of spatial statistical methods in health and on associated benefits and problems.