Ryan Engstrom

Assessing the carbon balance of circumpolar Arctic tundra using remote sensing and process modeling

This paper reviews the current status of using remote sensing and process-based modeling approaches to assess the contemporary and future circumpolar carbon balance of Arctic tundra, including the exchange of both carbon dioxide and methane with the atmosphere. Analyses based on remote sensing approaches that use a 20-year data record of satellite data indicate that tundra is greening in the Arctic, suggesting an increase in photosynthetic activity and net primary production. Modeling studies generally simulate a small net carbon sink for the distribution of Arctic tundra, a result that is within the uncertainty range of field-based estimates of net carbon exchange. Applications of process-based approaches for scenarios of future climate change generally indicate net carbon sequestration in Arctic tundra as enhanced vegetation production exceeds simulated increases in decomposition. However, methane emissions are likely to increase dramatically, in response to rising soil temperatures, over the next century. Key uncertainties in the response of Arctic ecosystems to climate change include uncertainties in future fire regimes and uncertainties relating to changes in the soil environment. These include the response of soil decomposition and respiration to warming and deepening of the soil active layer, uncertainties in precipitation and potential soil drying, and distribution of wetlands. While there are numerous uncertainties in the projections of process-based models, they generally indicate that Arctic tundra will be a small sink for carbon over the next century and that methane emissions will increase considerably, which implies that exchange of greenhouse gases between the atmosphere and Arctic tundra ecosystems is likely to contribute to climate warming.

Greenness trends of Arctic tundra vegetation in the 1990s: comparison of two NDVI data sets from NOAA AVHRR systems

The primary objective of this study was to compare the sensitivity of two different normalized difference vegetation index (NDVI) time series derived from Local Area Coverage (LAC) and Global Areal Coverage (GAC) data sets of the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) satellite system. This comparison was conducted in the context of analysing spatiotemporal patterns of Arctic tundra vegetation greenness change in the 1990s within the North Slope of Alaska. A second objective was to examine patterns of greenness change with respect to the distribution of vegetation association types. An 8 km spatial resolution NDVI series was produced by the Global Inventory Modeling and Mapping Studies (GIMMS) group at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center based on a GAC data set and corrected for stratospheric aerosol effects from the eruption of Mt Pinatubo. The LAC (1 km spatial resolution) NDVI time series was generated through recalibration and fine‐tuning of image registration of a twice‐monthly time series produced by the US Geological Survey, and was cross‐calibrated with the GIMMS data set to reduce stratospheric aerosol effects from the Mt Pinatubo eruption. While the general patterns of pixels exhibiting significant increase in seasonally integrated NDVI over the 1990s were similar from both data sets, many of the more localized areas of more rapidly increasing greenness (i.e. ‘hotspots’) between 1990 and 1999 were lost with the product from the GIMMS data set. The majority of the ‘hotspots’ of greenness increase within the North Slope region are located in the southern portions of the foothills physiographic province and within vegetation units composed primarily of prostrate or dwarf shrubs with a mixture of graminoid species. Notably fewer hotspots of greenness increase were detected in Arctic tundra areas of the Seward Peninsula and none in the Chukotka Peninsula of the Russian Far East, an area that had not experienced the same warming trend in the 1990s and preceding decades as the Alaskan Arctic.

Connecting the Dots Between Health, Poverty and Place in Accra, Ghana

West Africa has a rapidly growing population, an increasing fraction of which lives in urban informal settlements characterized by inadequate infrastructure and relatively high health risks. Little is known, however, about the spatial or health characteristics of cities in this region or about the spatial inequalities in health within them. In this article we show how we have been creating a data-rich field laboratory in Accra, Ghana, to connect the dots between health, poverty, and place in a large city in West Africa. Our overarching goal is to test the hypothesis that satellite imagery, in combination with census and limited survey data, such as that found in demographic and health surveys (DHSs), can provide clues to the spatial distribution of health inequalities in cities where fewer data exist than those we have collected for Accra. To this end, we have created the first digital boundary file of the city, obtained high spatial resolution satellite imagery for two dates, collected data from a longitudinal panel of 3,200 women spatially distributed throughout Accra, and obtained microlevel data from the census. We have also acquired water, sewerage, and elevation layers and then coupled all of these data with extensive field research on the neighborhood structure of Accra. We show that the proportional abundance of vegetation in a neighborhood serves as a key indicator of local levels of health and well-being and that local perceptions of health risk are not always consistent with objective measures.

Relationship between AVHRR surface temperature and NDVI in Arctic tundra ecosystems

A negative, linear relationship between thermal emissions and a spectral vegetation index has been demonstrated for numerous mid‐latitude ecosystems. In this study, it is hypothesized that the relationship between surface temperature and the normalized difference vegetation index (NDVI) will be linear, but positive in Arctic tundra ecosystems due to the contrast between warm vegetation and the cold soil/moss background. This hypothesis is tested using Advanced Very High Resolution Radiometer (AVHRR) data collected over the North Slope of Alaska on three days during the summer of 1999. Results of the study generally provide support for this hypothesis. However, a consistent relationship observed across two contrasting physiographic provinces on one study day was shown to change the following day and could not be readily explained by differences in satellite zenith angle or observed air temperature. Surface temperatures are shown to respond directly to spatial and temporal variations in air temperature.

Primary Care Spatial Density and Nonurgent Emergency Department Utilization: A New Methodology for Evaluating Access to Care

OBJECTIVE To determine the spatial and demographic characteristics of pediatric patients who make nonurgent visits (NUVs) to an urban pediatric emergency department (ED). We hypothesized that the rate of NUVs would be inversely associated with the spatial density of primary care providers (PCPs). METHODS A retrospective, cross-sectional analysis was conducted for all visits to Washington, DCs principal pediatric ED between 2003 and 2006. NUVs were defined by a unique algorithm combining resource allocation, ambulatory-sensitive diagnoses, and billing data. Multivariate linear regression analysis was used to determine the association of PCP density and demographic variables on the spatial rate of NUVs. RESULTS Over the 4-year period, 35.1% (52,110) of the 148,314 ED visits by Washington, DC, residents were nonurgent. NUVs were most associated with neighborhood median household income <

Spatial accessibility to providers and vaccination compliance among children with medicaid.

40,000 and low spatial density of PCPs. For every 1-unit increase in PCP density, the spatial rate of NUVs decreased by 9%. The odds of a visit being nonurgent were significantly higher for African Americans and Hispanics than for whites (odds ratio [OR] 2.4, 95% confidence interval [CI] 2.19-2.64; and OR 2.6, 95% CI 2.36-2.86, respectively), for patients using public insurance versus private (OR 1.46, 95% CI 1.42-1.50), and for patients age <5 years (OR 2.66, 95% CI 2.60-2.72). CONCLUSIONS Low spatial density of primary care is strongly associated with nonurgent ED utilization. Improving spatial distribution of primary care may decrease ED misuse and improve access to the medical home.

Defining neighborhood boundaries for urban health research in developing countries: a case study of Accra, Ghana

OBJECTIVE: We examined the relationship between spatial accessibility to pediatric immunization providers and vaccination compliance in a low-income, urban population of children. METHODS: In 2007, we accessed the Washington, DC, Immunization Information System (IIS) to collect data on the immunization statuses and residential addresses of children who were aged 19 to 35 months and had Medicaid insurance. In addition, we calculated each childs spatial accessibility to pediatric vaccination providers by assessing the provider-to-population ratio at each residential address. Spatial accessibility was divided into tertiles (low, medium, and high) of access. The relationship between spatial accessibility to providers and vaccination compliance was examined by using logistic regression analysis adjusting for age, type of vaccination provider, and enrollment in child care status. RESULTS: Overall for our cohort of 4195 children, 80.5% of the children were up-to-date with vaccinations. Vaccination coverage ranged from 61.6% to 100% (median: 79.2%) among different neighborhoods. Having the highest level of access to pediatric vaccination providers was associated with 36% higher odds of being up-to-date as compared with having the lowest level of access. The middle tertile of access was associated with 25% higher odds of being up-to-date. CONCLUSIONS: Within our low-income, urban population, children with higher spatial accessibility to pediatric vaccination providers were more likely to be up-to-date with vaccinations. This association may guide future studies and efforts to ensure adequate immunization coverage for children regardless of where they live.

The Relationship Between Soil Moisture and NDVI Near Barrow, Alaska

The neighborhood has been used as a sampling unit for exploring variations in health outcomes. In a variety of studies census tracts or ZIP codes have been used as proxies for neighborhoods because the boundaries are pre-defined units for which other data are readily available. However these spatial units can be arbitrary and do not account for social-cultural behaviors and identities that are significant to residents. In this study for the city of Accra, Ghana, our goal was to create a neighborhood map that represented the boundaries generally agreed upon by the residents of the city using the smallest available census unit, the enumeration area (EA), as the base unit. This neighborhood map was then used as the basis for mapping spatial variations in health within the city. The first step in demarcating the boundaries was to identify features that limit a persons movement including the major roads, drainage features, and railroad tracks that people use to partially define their neighborhood boundaries. Once an initial set of boundaries were established, they were iteratively modified by walking the neighborhoods, talking to residents, public officials, and others. The resulting neighborhood map consolidated 1723 EAs into 108 neighborhoods covering the entire Accra metropolitan area. Results indicated that the team achieved 71% accuracy in mapping neighborhoods when the neighborhood keyed to the survey EA was compared with the response given by the interviewees in the 2008–2009 Womens Health Survey of Accra when asked which neighborhood they lived in.

Do the Most Vulnerable People Live in the Worst Slums? A Spatial Analysis of Accra, Ghana

Ice-wedge polygons and drained thaw lake basins cover large portions of the Barrow Peninsula of Alaska. These landforms lead to variations in topography in the relatively flat coastal plain. These variations in topography, while small, lead to large variations in soil moisture, which have a substantial impact on carbon, water, and energy fluxes in these systems. In this study, we hypothesize that the spatial patterns of soil moisture control variations in vegetation production, and hence remotely sensed greenness. We investigate the relationship between soil moisture and a remotely sensed measure of vegetation greenness, the normalized difference vegetation index (NDVI). Soil moisture was measured in the summer of 2000 in the fetch of an eddy flux tower (0.5 km2 footprint), and NDVI data were collected using an aerial digital multispectral camera system. Results indicate that the relationship between soil moisture and NDVI was significant in areas dominated by high-centered polygons and troughs, and where the general slope of the terrain promoted the redistribution of soil moisture. However, in areas with little to no relief, the correlation between soil moisture and NDVI was not significant.

Determining the Relationship Between Census Data and Spatial Features Derived From High-Resolution Imagery in Accra, Ghana

Slums are examples of localized communities within third-world urban systems representing a range of vulnerabilities and adaptive capacities. This study examines vulnerability in relation to flooding, environmental degradation, social status, demographics, and health in the slums of Accra, Ghana, by utilizing a place-based approach informed by fieldwork, remote sensing, census data, and geographically weighted regression (GWR). The study objectives are threefold: (1) to move slums from a dichotomous into a continuous classification and examine the spatial patterns of the gradient, (2) to develop measures of vulnerability for a developing world city and model the relationship between slums and vulnerability, and (3) to assess if the most vulnerable individuals live in the worst slums. A previously developed slum index is utilized, and four new measures of vulnerability are developed through principal components analysis (PCA), including a novel component of health vulnerability based on child mortality. Visualizations of the vulnerability measures assess spatial patterns of vulnerability in Accra. Ordinary least squares (OLS), spatial, and GWR model the ability of the slum index to predict the four vulnerability measures. The slum index performs well for three of the four vulnerability measures, but is least able to predict health vulnerability, underscoring the complex relationship between slums and child mortality in Accra. Finally, quintile analysis demonstrates the elevated prevalence of high vulnerability in places with high slum index scores.