Residential Parcels Research Articles

The Combined Use of Remote Sensing and Social Sensing Data in Fine-Grained Urban Land Use Mapping: A Case Study in Beijing, China

In light of the need for fine-grained, accurate, and timely urban land use information, a per-field classification approach was proposed in this paper to automatically map fine-grained urban land use in a study area within Haidian District, Beijing, China, in 2016. High-resolution remote sensing imagery and multi-source social sensing data were used to provide both physical and socioeconomic information. Four categories of attributes were derived from both data sources for urban land use parcels segmented by the OpenStreetMap road network, including spectral/texture attributes, landscape metrics, Baidu Point-Of-Interest (POI) attributes, and Weibo attributes. The random forests technique was adopted to conduct the classification. The importance of each attribute, attribute category, and data source was evaluated for the classification as a whole and the classification of individual land use types. The results showed that a testing accuracy of 77.83% can be achieved. The approach is relatively good at classifying open space and residential parcels, and poor at classifying institutional parcels. While using solely remote sensing data or social sensing data can achieve equally high overall accuracy, their importance varies in terms of the classification of individual classes. Landscape metrics are the most important for open space parcels. Spectral/texture attributes are more important in identifying institutional and residential parcels. The classification of business parcels relies more on landscape metrics and social sensing data, and less on spectral/texture attributes. The classification accuracy can be potentially improved upon the acquisition of purer parcels and the addition of new attributes. It is expected that the proposed approach will be useful for the routine update of urban land use information and large-scale urban land use mapping.

On the association between land system architecture and land surface temperatures: Evidence from a Desert Metropolis—Phoenix, Arizona, U.S.A

The relationship between the characteristics of the urban land system and land surface temperature (LST) has received increasing attention in urban heat island and sustainability research, especially for desert cities. This research generally employs medium or coarser spatial resolution data and primarily focuses on the effects of a few classes of land-cover composition and pattern at the neighborhood or larger level using regression models. This study explores the effects of land system architecture—composition and configuration, both pattern and shape, of fine-grain land-cover classes—on LST of single family residential parcels in the Phoenix, Arizona (southwestern USA) metropolitan area. A 1m resolution land-cover map is used to calculate land architecture metrics at the parcel level, and 6.8m resolution MODIS/ASTER data are employed to retrieve LST. Linear mixed-effects models quantify the impacts of land configuration on LST at the parcel scale, controlling for the effects of land composition and neighborhood characteristics. Results indicate that parcel-level land-cover composition has the strongest association with daytime and nighttime LST, but the configuration of this cover, foremost compactness and concentration, also affects LST, with different associations between land architecture and LST at nighttime and daytime. Given information on land system architecture at the parcel level, additional information based on geographic and socioeconomic variables does not improve the generalization capability of the statistical models. The results point the way towards parcel-level land-cover design that helps to mitigate the urban heat island effect for warm desert cities, although tradeoffs with other sustainability indicators must be considered.

Beyond affordable shelters: Subsidized housing and surrounding environments for pedestrian safety

Beyond the provision of affordable housing itself, planners and policymakers have raised concerns as to whether subsidized housing developments provide “suitable living environments” for the nation's poor. Despite numerous concerns regarding unfavorable living environments and the neighborhood context of subsidized housing, we have limited understanding as to whether built environments around subsidized housing ensure pedestrian safety. This study addressed this gap by examining how built environments around Low Income Housing Tax Credit (LIHTC) sites affect pedestrian-vehicle crashes in Austin, Texas. We employed the two-level negative binomial regression to clarify the impacts of street segment-level and neighborhood-level built environments on pedestrian crashes around LIHTC complexes. We found that higher speed roads, traffic-generating land uses, higher transit stop densities, and higher four-or-more-leg intersection densities may hinder pedestrian safety. Conversely, local roads as well as single-family residential parcels and connected sidewalks along street segments may enhance pedestrian safety around LIHTC complexes. Our results may inform planners and policymakers on how to enhance pedestrian safety for subsidized housing by modifying surrounding environments and how to provide better site selection considerations for subsidized housing to ensure pedestrian safety.

Social and Built Environmental Correlates of Predicted Blood Lead Levels in the Flint Water Crisis.

To highlight contextual factors tied to increased blood lead level (BLL) risk following the lead-in-water contamination in Flint, Michigan. Using geocoded BLL data collected in 2013 and 2015 and areal interpolation, we predicted BLLs at every residential parcel in the city. We then spatially joined social and built environmental variables to link the parcels with neighborhood-level factors that may influence BLLs. When we compared levels before and during the water crisis, we saw the highest estimates of predicted BLLs during the water crisis and the greatest changes in BLLs in neighborhoods with the longest water residence time in pipes (μ = 2.30 µg/dL; Δ = 0.45 µg/dL), oldest house age (μ = 2.22 µg/dL; Δ = 0.37 µg/dL), and poorest average neighborhood housing condition (μ = 2.18 µg/dL; Δ = 0.44 µg/dL). Key social and built environmental variables correlate with BLL; such information can continue to guide response by prioritizing older, deteriorating neighborhoods with the longest water residence time in pipes.

The drinking water contamination crisis in Flint: Modeling temporal trends of lead level since returning to Detroit water system

Since Flint returned to its pre-crisis source of drinking water close to 25,000 water samples have been collected and tested for lead and copper in >10,000 residences. This paper presents the first analysis and time trend modeling of lead data, providing new insights about the impact of this intervention. The analysis started with geocoding all water lead levels (WLL) measured during an 11-month period following the return to the Detroit water supply. Each data was allocated to the corresponding tax parcel unit and linked to secondary datasets, such as the composition of service lines, year built, or census tract poverty level. Only data collected on residential parcels within the City limits were used in the analysis. One key feature of Flint data is their collection through two different sampling initiatives: (i) voluntary or homeowner-driven sampling whereby concerned citizens decided to acquire a testing kit and conduct sampling on their own (non-sentinel sites), and (ii) State-controlled sampling where data were collected bi-weekly at selected sites after training of residents by technical teams (sentinel sites). Temporal trends modeled from these two datasets were found to be statistically different with fewer sentinel data exceeding WLL thresholds ranging from 10 to 50μg/L. Even after adjusting for housing characteristics the odds ratio (OR) of measuring WLL above 15μg/L at non-sentinel sites is significantly >1 (OR=1.480) and it increases with the threshold (OR=2.055 for 50μg/L). Joinpoint regression showed that the city-wide percentage of WLL data above 15μg/L displayed four successive trends since the return to Detroit Water System. Despite the recent improvement in water quality, the culprit for differences between sampling programs needs to be identified as it impacts exposure assessment and might influence whether there is compliance or not with the Lead and Copper Rule.

Multi-scale heterogeneity in vegetation and soil carbon in exurban residential land of southeastern Michigan, USA.

Exurban residential land (one housing unit per 0.2-16.2ha) is growing in importance as a human-dominated land use. Carbon storage in the soils and vegetation of exurban land is poorly known, as are the effects on C storage of choices made by developers and residents. We studied C storage in exurban yards in southeastern Michigan, USA, across a range of parcel sizes and different types of neighborhoods. We divided each residential parcel into ecological zones (EZ) characterized by vegetation, soil, and human behavior such as mowing, irrigation, and raking. We found a heterogeneous mixture of trees and shrubs, turfgrasses, mulched gardens, old-field vegetation, and impervious surfaces. The most extensive zone type was turfgrass with sparse woody vegetation (mean 26% of parcel area), followed by dense woody vegetation (mean 21% of parcel area). Areas of turfgrass with sparse woody vegetation had trees in larger size classes (> 50cm dbh) than did areas of dense woody vegetation. Using aerial photointerpretation, we scaled up C storage to neighborhoods. Varying C storage by neighborhood type resulted from differences in impervious area (8-26% of parcel area) and area of dense woody vegetation (11-28%). Averaged and multiplied across areas in differing neighborhood types, exurban residential land contained 5240±865g C/m2 in vegetation, highly sensitive to large trees, and 13 800±1290g C/m2 in soils (based on a combined sampling and modeling approach). These contents are greater than for agricultural land in the region, but lower than for mature forest stands. Compared with mature forests, exurban land contained more shrubs and less downed woody debris and it had similar tree size-class distributions up to 40cm dbh but far fewer trees in larger size classes. If the trees continue to grow, exurban residential land could sequester additional C for decades. Patterns and processes of C storage in exurban residential land were driven by land management practices that affect soil and vegetation, reflecting the choices of designers, developers, and residents. This study provides an example of human-mediated C storage in a coupled human-natural system.

Inferring Spatial Scale Change in an Isopleth Map

This study reunites areal interpolation with the isopleth mapping process to construct an inferred larger scale isopleth map. Intelligent areal interpolation is used to construct two types of population density surfaces that are used as inputs for pycnophylactic interpolation of an isopleth surface. One is a target zone population density surface (TZPDS) and the other is a control zone population density surface (CZPDS). Results suggest that an inferred isopleth map with remote sensing control data is a better surface depiction than an isopleth map without any control data, and the quality of such an isopleth map is further improved by enhancing the remote sensing data with residential parcel information. A CZPDS-derived intelligent isopleth map also has more peaks and variations in population distribution patterns than does a TZPDS-derived one due to the larger scale of the control data.

Road Network Accessibility and Socio-economic Disadvantage Across Adelaide Metropolitan Area

Transport mobility is important in defining the population’s accessibility to services and facilities. Few studies have investigated the relationship between geographical accessibility of urban services for the population living in residential areas and socio-economic parameters. In this paper, the distribution of residential parcels is analyzed from a rarely explored angle—that is, its location in relation to services and facilities. The aims of this study are first to develop an index of the accessibility of various urban resources to each residential parcel in a metropolitan area of Adelaide using spatial data analysis in Geographical Information Systems and then to develop a relationship with socio-economic and land use attributes of statistical areas using ordinary least squares (OLS) and geographically weighted regression analysis. As expected the ‘Distance to CBD’ variable has a positive relationship with metropolitan Accessibility/Remoteness Index of Adelaide (metro-ARIA) meaning that the farther away statistical areas have lower accessibility to services. In the case of population density variable, the relationship is mostly negative except few areas in the far south, west and northern areas, which showed a positive relationship. When similar results for median family income were studied, in some of the southernmost parts of Adelaide, it showed a strong positive relationship with metro-ARIA. This research will not only provide new insight into spatial differences between metropolitan areas but also potentially help in assessing the impact of the changes in services on land use. The findings of this paper, therefore, have important implications for service provision and social infrastructure investment.

Measuring the Externality Effects of Commercial Land Use on Residential Land Value: A Case Study of Seoul

Two contrasting theories purport to explain the effects of neighborhood non-residential use on residential property values. In traditional zoning theory, separating land from commercial land use is considered to protect residential environments from negative externalities such as noise, litter, and congestion. By contrast, contemporary planning principles including Smart Growth emphasize positive impacts of mixed land use on residential environment, which lead to more walkable and sustainable communities. This study attempts to empirically investigate how positive and negative externalities of commercial land use, referred to as “proximity effects” and “disamenity effects” respectively, affect residential land values. Using data gathered in Seoul, we pay attention to two particular aspects of commercial land use: spatial concentration and neighborhood scale. Spatial concentration is determined by the number of commercial employees present in the buffer zone around an individual residential parcel. We model four geographically distinct neighborhood scales as we compare spatial concentrations in and across commercial zones. Quadratic regression analyses of our data show the trade-off relationship that a higher spatial concentration of commercial land use in a neighborhood initially results in increased residential land values, but drops off beyond a threshold level by excessive noise or crowding.

Looking for logic: The zoning—land use mismatch

In this paper, we investigate the disconnect between a parcel's actual land use and its corresponding zoning designation, focusing in particular on how single-family residential parcels are zoned. Using a unique set of detailed parcel information, we quantify the extent to which single-family land use is zoned as multi-family in the city of Phoenix, AZ. We carry out local spatial autocorrelation analysis, spatial regression, and regression models for proportions to analyze the pattern and associated explanatory factors for the fraction of single-family land use acreage by census tract that was zoned as multi-family. We find that the basic driver of mis-matched parcels at the tract scale is socio-economic, not physical or planning goal oriented.

Exploiting temporal information in parcel data to refine small area population estimates

Temporal analysis of small-area demographic data commonly relies on areal interpolation methods to create temporally consistent and compatible areal units. In this study, cadastral (parcel) data are used to identify residential land and to dasymetrically refine census tracts, with the goal of achieving more accurate small-area estimates. The built date recorded for residential parcel units is used to create residential land layers for two different time points used in the areal interpolation. Three different areal interpolation methods are employed with and without dasymetric refinement, including areal weighting (AW), target density weighting (TDW) and pycnophylactic modeling (PM). The methods interpolate tract-level population counts in Hennepin County, Minnesota, in 2000 into census tract boundaries from the year 2010. The mean absolute error, median absolute error, root mean square error and the 90th percentile of absolute error are calculated for each of the methods, and spatial variation in the interpolations are displayed in maps. Parcel-based refinements are also compared with refinements using the National Land Cover Dataset (NLCD).Results show that spatial refinement using residential parcels has the potential to improve the accuracy of areal interpolation for temporal analysis. Parcel-refined TDW out-performs the other tested methods, as well as the NLCD-refined TDW in this example. Parcel data identify residential land more reliably in rural areas. However, parcel units can have very large extents potentially biasing residential area delineation and population counts. Parcel-based refinement has the potential to further advance demographic change analysis over long time periods and large areas where the built date attribute is included in the dataset.

Privacy Considerations for Duplicate Points in Masked Geodata

GIScience 2016 Short Paper Proceedings Privacy Considerations for Duplicate Points in Masked Geodata D. E. Seidl 1 Department of Geography, San Diego State University – UC Santa Barbara, 5500 Campanile Drive, San Diego, CA 92182 Email: dseidl@mail.sdsu.edu Abstract Reversal of a geomasking procedure can stem from the decryption of just a few points in a data set. This study explores the risks to privacy from the existence of duplicate data coordinates, and how such points are treated differently according to masking technique. Analysis of duplicates is conducted on a sample of urban foreclosure data, though the presence of duplicates should be considered on a case-by-case basis before releasing a masked data set. A nearest neighbour distance calculation for multi-unit parcels is recommended for weighting displacement distances in masking procedures on geodata with duplicate coordinates. 1. Introduction Geomasking techniques, which alter point distributions to protect privacy, are seeing increased use in public-facing applications. The citizen science site, iNaturalist, for instance, allows users to upload species observations with coordinates randomized within a 0.2 by 0.2 degree area (http://www.inaturalist.org/pages/help) (retrieved May 10, 2016). With wider use of masked geographic data, there is greater potential for users to decrypt masking techniques and ascertain original locations. The presence of duplicate sets of points at the same coordinates can pose differential risks to privacy when those points are masked. Early on in geomasking studies, researchers warned that releasing multiple versions of masked data could result in the reversal of the masking procedure (Armstrong, Rushton, and Zimmerman 1999). Zimmerman and Pavlik (2008) later demonstrated that the release of multiple masked data sets increases reverse engineering probability, since randomized points converge around original locations. Others have noted that if an adversary is able to determine the distance threshold used in masking point data, it might be possible to re- identify original locations (Zhang et al. 2015). A less-explored possibility is that multiple releases of points within a single data set—i.e. duplicate points—could reveal additional information about housing type, which could subsequently be used to uncover household identities. This is particularly true if that housing type is rare, or an anomaly in the study area. This study explores the privacy risks associated with the presence of duplicate points in a geographic data set and summarizes how the treatment of duplicate points varies by masking technique. For example, data representing different households may be matched to the same latitude and longitude if the data subjects live in the same apartment building or residential parcel. Foreclosure data are an example of how sensitive data about disparate households may be tied to the same coordinates. Multiple foreclosures in the same building will generally geocode to the same location. The treatment of duplicate points by a masking technique can adversely impact cluster detection, or increase the risk of household re-identification. Figure 1 demonstrates how maintaining a set of duplicates together when masked impacts the privacy risk when a map user is informed of auxiliary housing geodata. Duplicate points in the masked data would suggest a common origin in the same housing parcel, and if there is only a single multi-unit residential parcel nearby, an adversary may make an educated guess

Patterns of Wastewater Infrastructure along a Gradient of Coastal Urbanization: A Study of the Puget Sound Region

The aim of this paper is to explore patterns of wastewater infrastructures (sewers vs. septic tanks) in urbanizing watersheds across a coastal metropolitan region. This research combines an urban-rural gradient with spatial metrics at the patch and watershed scale (proportion of parcels on a treatment system, septic density, lot size and percent imperviousness) to analyze wastewater patterns in the Puget Sound, WA, USA. Results show that most urban residential parcels are hooked up to a sewer, although there remain urban residences on a septic tank with small lots. I find a complex arrangement of wastewater treatment in suburban watersheds representing a patchwork of parcels on sewers and septic tanks. Sewers dominate in total numbers, while the density of septic tanks is highest in this portion of the urban gradient. Lot size decreases from rural to urban; however, it varies depending on the type of wastewater treatment system. In urban watersheds, lots on septic tanks are significantly smaller than lots in suburban and rural watersheds and of a similar size compared to lots on sewers. I also find a significant difference in the amount of impervious surfaces in watersheds dominated by sewers vs. septic tanks. In the urban portion of the gradient, the amount of paved surfaces in parcels with septic tanks is also similar in level as parcels with sewers. I discuss how these patterns emerge from the interplay of biophysical, socio-economic and technological factors and how different regulatory regimes for septic tanks and sewers may further induce these patterns.

Micro-scale urban surface temperatures are related to land-cover features and residential heat related health impacts in Phoenix, AZ USA

With rapidly expanding urban regions, the effects of land cover changes on urban surface temperatures and the consequences of these changes for human health are becoming progressively larger problems. We investigated residential parcel and neighborhood scale variations in urban land surface temperature, land cover, and residents’ perceptions of landscapes and heat illnesses in the subtropical desert city of Phoenix, AZ USA. We conducted an airborne imaging campaign that acquired high resolution urban land surface temperature data (7 m/pixel) during the day and night. We performed a geographic overlay of these data with high resolution land cover maps, parcel boundaries, neighborhood boundaries, and a household survey. Land cover composition, including percentages of vegetated, building, and road areas, and values for NDVI, and albedo, was correlated with residential parcel surface temperatures and the effects differed between day and night. Vegetation was more effective at cooling hotter neighborhoods. We found consistencies between heat risk factors in neighborhood environments and residents’ perceptions of these factors. Symptoms of heat-related illness were correlated with parcel scale surface temperature patterns during the daytime but no corresponding relationship was observed with nighttime surface temperatures. Residents’ experiences of heat vulnerability were related to the daytime land surface thermal environment, which is influenced by micro-scale variation in land cover composition. These results provide a first look at parcel-scale causes and consequences of urban surface temperature variation and provide a critically needed perspective on heat vulnerability assessment studies conducted at much coarser scales.

The Influence of Land Cover, Vertical Structure, and Socioeconomic Factors on Outdoor Water Use in a Western US City

To help inform urban water conservation and planning, we evaluated spatial patterns and correlative relationships among physical land cover properties, socioeconomic and demographic characteristics, and single-family outdoor residential water use in Aurora, Colorado, a rapidly-growing suburb in the semi-arid Colorado Front Range. Using high resolution land cover maps and lidar-derived vertical structural data, we quantified land cover composition and vertical structural characteristics for detached, single-family residential parcels. These data were combined with socioeconomic and demographic datasets from the 2010 US Census and local government agencies and used in Random Forest analyses of outdoor water use estimated from residential water meter records, with separate analyses conducted using parcels and census block groups as sampling units. Conditional variable importance measures from Random Forest analyses and comparisons of the predictive accuracy of models developed using subsets of explanatory variables were used to assess the relative importance of physical and socioeconomic variables in predicting outdoor water use. Models developed using the subset of land cover variables had the highest predictive accuracy, followed by vertical structural variables, and lastly, socioeconomic/demographic variables. At both the parcel and census block group scale, there was significant spatial clustering in outdoor water use as indicated by various spatial statistical analyses. Our approach demonstrates the value of high resolution land cover and structure data for understanding urban water use patterns and can be used for targeting water conservation efforts.

A Dual-rate Property Tax: Exploring the Potential for Moderating the Effects of Sprawl on Development

This research evaluates the effectiveness of a dual-rate property tax on moderating sprawl, focusing particularly on how land-development decisions accumulate over space and affect changes in spatial patterns of development. A spatial process model of landowners’ conversion decisions links the effects of a dual-rate property tax on parcel-level land conversion through ex ante simulations. We conclude that the dual-property tax helps reduce the mean nearest neighbor of residential parcels and thus promotes the development of land around existing infrastructure more than land distant from existing infrastructure; however, the dual-property tax alone does not completely mitigate sprawl.

Rethinking Locational Outcomes for Housing Choice Vouchers: A Case Study in Duval County, Florida

This study examines locational patterns of housing choice vouchers in Duval County, Florida, using the Housing Suitability Model (HSM), a newly developed geographic information system–based model that evaluates residential land parcels and neighborhoods in terms of their suitability for affordable housing. The HSM was used to characterize voucher locations and other residential parcels across the county in terms of opportunity and accessibility. The analysis explores the tradeoffs between opportunity and accessibility inherent in many neighborhoods throughout the county. It finds that voucher holders' locations lag substantially behind other residential locations in terms of opportunity measures but are more comparable in terms of accessibility. Further analysis finds differences in opportunity and accessibility among subgroups of voucher holders by various demographic characteristics. The study recommends the incorporation of opportunity and accessibility for voucher holders into local housing planning, including the implementation of proposed rules for Affirmatively Furthering Fair Housing.

The effects of produce gardens on neighborhoods: A test of the greening hypothesis in a post-industrial city

Researchers have found that gardens and landscaping designs can diffuse throughout neighborhoods. In the present study, we extend this research by examining if produce gardens on reclaimed vacant lots can have a radiating and positive, linear effect on the surrounding residential parcels. If well-maintained parcels tend to cluster together then we would expect that parcels proximal to a well-maintained produce garden would have better maintenance than parcels near an undeveloped vacant lot. We refer to this transformative process as the Greening Hypothesis. In the present study, we investigate yard maintenance observations of residential properties located near a produce garden, compared with those near an undeveloped vacant lot while controlling for residents’ neighborhood perceptions and census demographic data. Our study area was urban and residential with higher than normal levels of property abandonment and urban blight. Our results, supporting the greening hypothesis, indicated that residential parcels proximal to produce gardens were better maintained than parcels near undeveloped vacant lots. Study implications support policies and programs which include greening initiatives as part of community development strategies.

Hydropedological Assessments of Parcel-Level Infiltration in an Arid Urban Ecosystem

Soil morphology and correspondent hydrologic data can contribute to qualifying and quantifying urban soil suitability and capacity to cycle stormwater runoff. We put particular emphasis on the possibility that residential parcels may manage their own stormwater on pervious yard areas. We assessed the morphology of Aridisol pedons (as deep cores to approximately the 3.6-m depth) via soil taxonomy, performed in situ measurements of infiltration, and measured subsoil hydraulic conductivity in two desert parks, four residential parcels, and three dual-purpose park–stormwater retention basins in the Phoenix, AZ, metropolitan area. Infiltration rates overall ranged between 0.4 and 1.7 cm h⁻¹. We used borehole hydraulic conductivity as a proxy for drainage, which ranged from a low of 0.0 to 13 cm h⁻¹. Representing a baseline, or set of “natural” hydrologic processes, native desert sites exhibited a relatively high capacity to infiltrate and redistribute rainfall, which, depending on storm intensity, may drain to washes or ephemeral streambeds via subsurface runoff. Simulations of stormwater runoff on residential parcels showed that when rooftop runoff is directed to pervious patches, rainfall is entirely infiltrated and redistributed, which predicts good potential for parcel-level stormwater management. Our observation of an accumulation of fine sediments in retention basin surface soils was corroborated with local observations that drawdown times in the retention basins had increased with time. Although further assessment is needed on a wider variety of semiarid landscapes, our results suggest a positive role for residential parcels in detaining stormwater on site and perhaps easing the wet-weather burden on centralized stormwater infrastructure in semiarid urban ecosystems.

Mapping the Cost of a Balanced Diet, as a Function of Travel Time and Food Price

We present a new method for analyzing spatial variation in the cost of a balanced diet, as an alternative to food desert classification. Our specific hypothesis is that the cost of a balanced diet varies according to where one lives, as a function of travel and food item costs. We collected price data for the USDA Thrifty Food Plan from approximately 30 percent of food retail outlets of various kinds in the three Gulf Coast counties of Mississippi, and these prices were extrapolated to the remaining stores. Transportation costs were calculated for both driving by automobile and the combination of walking and public transportation by bus, accounting for both the shoppers' time and the cost of automobile mileage. We developed a traveling purchaser problem algorithm to estimate the lowest-cost combination of travel and food costs for purchasing all items in the Thrifty Food Plan for each residential parcel in the study area, and mapped the resulting costs and examined their variation. Estimated costs varied more because of transportation costs than food prices, and ranged from US$109 to US$215 for automobile travel and from US$111 to US$439 for a combination of walking and public transportation. In general, costs were lowest in the more populated areas near the coast and higher in more rural areas further inland. Results of this analysis demonstrate that the cost of acquiring a balanced diet varies considerably and more or less continuously. Food is not equally cheap for all; it depends on where one lives. For any given location, an estimate of the cost of a balanced diet, including both food price and transportation, is more useful than a classification as food desert or not in understanding access issues and needs. Furthermore, policy alternatives that are intended to influence access should be evaluated based on how much they influence costs, and for whom, depending on where people live.