How do we characterize food stores for public health research?

Kersten, E., B. Laraia, M. Kelly, N. Adler, and I. Yen. 2012. Small food stores and availability of nutritious foods: A comparison of database and in-store measures, Northern California, 2009. Preventing Chronic Disease 9:120023. DOI: http://dx.doi.org/10.5888/pcd9.120023

Small food stores are prevalent in urban neighborhoods, but the availability of nutritious food at such stores is not well known. The objective of this study was to determine whether data from 3 commercially available sources would yield a single, homogenous, healthful food store category that can be used to accurately characterize community nutrition environments for public health research. We conducted in-store surveys in 2009 on store type and the availability of nutritious food in a sample of nonchain food stores (n = 102) in 6 predominantly urban counties in Northern California (Alameda, Contra Costa, Marin, Sacramento, San Francisco, and Santa Clara). We compared survey results with commercial database information and neighborhood sociodemographic data by using independent sample t tests and classification and regression trees. We found that commercial databases alone may not adequately categorize small food stores and the availability of nutritious foods. Alternative measures are needed to more accurately inform research and policies that seek to address disparities in diet-related health conditions. 

Journal Link. Pdf download.

Where will SF Bay wetlands be in 100 years?

Stralberg, D., M. Brennan, J. C. Callaway, J. K. Wood, L. M. Schile, D. Jongsomjit, M. Kelly, V. T. Parker, and S. Crooks. 2011. Evaluating tidal marsh sustainability in the face of sea-level rise: a hybrid modeling approach applied to San Francisco Bay. PLoS ONE 6(11): e27388.

Tidal marshes will be threatened by increasing rates of sea-level rise (SLR) over the next century. Managers seek guidance on whether existing and restored marshes will be resilient under a range of potential future conditions, and on prioritizing marsh restoration and conservation activities. Building upon established models, we developed a hybrid approach that involves a mechanistic treatment of marsh accretion dynamics and incorporates spatial variation at a scale relevant for conservation and restoration decision-making. We applied this model to San Francisco Bay, using best-available elevation data and estimates of sediment supply and organic matter accumulation developed for 15 Bay subregions.

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Cal-adapt is PE&RS cover story

June 2011 cover story on cal-adaptKoy,
 K.,
 S.
 V.
 Wart,
 B. Galey, 
M. 
O’Connor, 
and 
M. 
Kelly. 2011. 
Cal‐Adapt:
 Bringing
 global 
climate 
change 
data 
to 
local
 application. Photogrammetric Engineering and Remote Sensing 77(6): 546-550

June's PE&RS cover story features the Cal-Adapt web application developed by the GIF.  Cal-adapt has been developed to showcase the wealth of innovative climate change research being produced by the scientific community in California, as documented in the 2009 California Climate Adaptation Strategy. Through a combination of locally relevant information, visualization tools, and access to primary data, Cal-Adapt allows users to investigate how the climate is projected to change in their area of interest, and gives them tools to plan for these changes.

Our article can be found here.

Influence of neighborhood food stores on girls’ BMI

Leung, CH, BA Laraia, M Kelly, D Nickleach, NE Adler, LH Kushi, and IH Yen. 2011. Effects of Neighborhood Food Store Availability on Young Girls' Body Mass Index. American Journal of Preventative Medicine 41(1): 43–51

This exploratory study examined the relationship between the presence of neighborhood food stores within a girl’s neighborhood and 3-year risk of overweight/obesity and change in BMI, in girls aged 6 or 7 years at baseline. Availability of convenience stores within a 0.25-mile network  buffer of a girl’s residence was associated with greater risk of overweight/obesity and an increase in BMI z-score. Availability of produce vendors/farmer’s markets within a 1.0-mile network buffer of a girl’s residence was inversely associated with overweight/obesity.

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Pattern metrics for wetland restoration management

Kelly, M., K. Tuxen and D. Stralberg. 2011. Mapping changes to vegetation pattern in a restoring wetland: Finding pattern metrics that are consistent across spatial scale and time. Ecological Indicators 11: 263-273. We sought to identify pattern metrics that are consistent across spatial scale and time – and thus robust measures of vegetation and habitat configuration – for a restored tidal marsh in the San Francisco Bay, CA, USA.

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Predicting bird abundance in tidal marshes

Predicted mean abundance for common yellowthroat at Browns Is. and Sherman Lake

Stralberg, D., M. Herzog, N. Nur, K. Tuxen, S. Siegel and M. Kelly. 2010. Predicting avian abundance within and across tidal marshes using fine-scale vegetation and geomorphic metrics. Wetlands 30: 475-487

We used a blend of fine-scale remote sensing products and field-based survey data via spatial predictive models to aid in monitoring restoring tidal marshes for bird habitat. We developed a suite of 1-m pixel-level spatial metrics describing patterns in marsh vegetation and geomorphology for six sites across a large salinity gradient, and used these to predict avian abundance.

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Historic map analysis: spatial error in the CA VTM dataset

Kelly, M., K. Ueda and B. Allen-Diaz. 2008. Considerations for ecological reconstruction of historic vegetation: Analysis of the spatial uncertainties in the California Vegetation Type Map dataset. Plant Ecology 194 (1): 37-49

Uncertainty surrounding plot centersWe examine the spatial uncertainties associated with 18,000 vegetation plots in the VTM dataset that has been digitized for use in modern ecological analysis. We examine the relationship between plot location error and basemap year, basemap scale, plot elevation, plot slope, and general plot habitat type. Pdf download. Journal link.

Keywords: CART . Historical vegetation data . Spatial error . VTM

Including the spatial relations of objects in classification

Liu, et al. 2008. ISPRS Journal of Photogrammetry and Remote Sensing. We establish a context where objects are areal (not points or lines) and non-overlapping (we call this “single-valued” space), and propose a framework of binary spatial relations between segmented objects to aid in object classification.

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Mapping vegetation colonization in a restoring tidal marsh

Tuxen, et al. 2008. Restoration Ecology. Vegetation colonization in a restored marshWe used NDVI to document vegetation colonization in a restoring salt marsh. This method was effective at detecting change in vegetation over time in a variable tidal marsh environment using imagery that had inconsistent specifications and quality across years.

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Modeling SOD risk in the United States

Kelly, et al. 2007. Computers, Environment and Urban Systems. Risk for SOD in the southeast based on model agreementUsing the locations of P. ramorum in CA we derived a risk map for SOD spread in the conterminous US using 5 environmental niche models: Expert-driven Rule-based, Logistic Regression, Classification and Regression Trees, Genetic Algorithms, and Support Vector Machines.

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