Special Topics and Open Source Food Deserts Report

      Welcome to the final post for the Special Topics in GIS course. This last portion is dedicated to the report on Food Deserts that has culminated the last few weeks of preparation and analysis. The overall objective for this project was to explore open source GIS software and web mapping applications to create a simple but custom web map to work in concert with standalone maps generated with other open source GIS software, specifically QGIS.
       The culmination of the analysis results is presented in the fully narrated power point presentation linked below. Additionally the independent web map also linked below is embedded into the presentation. For those who do not want to download the full powerpoint as its slightly large (25mb) the result map is below for your convenience.

A Growing Trend: Food Deserts PowerPoint Report

Palm Springs Food Desert Interactive Web Map

        A brief overview: A food desert is an area in or around a city or urban center that is outside of 1 mile from a grocery store that doesn't offer fresh produce or other whole foods. The lack of these fresh foods can led to compounding health issues for those who might not have the means to travel farther to grocery stores with them and are stuck with local potentially unhealthy options. My project involved investigating the city of Palm Springs California for the presence of Food Deserts. The data was investigated at the census tract level, looking at the population information from the 2010 census. The center of the census tracts was evaluated to determine those outside of 1 mile from the grocery stores present. These food deserts were then color coded by population distribution highlighting those most impacted. The interactive web map supplements this information by allowing you to a better visual sense of the neighborhood distribution for the area in relation to the census tracts.

    Overall the analysis resulted in 51% of the population being impacted by food desert conditions. This definitely highlights that there is a problem with food deserts in the area. This data can be used to help inform city planners for future developments of grocery stores or healthy food alternatives closer to impacted neighborhoods. This education about food deserts as followed through the last few weeks is the biggest way to help combat the spread of food deserts, by making the public informed.
    All of this presentation was created utilizing open source information and software (minus a couple cheating moments of using ArcGIS). Open source products are hugely beneficial and with a little bit of time can be employed by just about anyone. This is a wonderful supplement of tools for the masses who might not have access to the more proprietary spatial analysis tools. Thank you for joining me on this journey and I look forward to you following along as I embark on a GIS internship.

Special Topics, Food Deserts and Map Box

Welcome to the continued look at open source GIS with a flavor for fresh food, or lack thereof as is the case for areas identified as food deserts. This is a continuation of the analysis started last week. This week was dedicated to the following objectives:

• Tile Shapefiles for internet usage
• Create a custom basemap with the use of Mapbox
• Utilize web mapping to communicate a subject

    Essentially last week you saw some analysis with premade subject matter for the Pensacola area of Escambia County Florida. Those datasets were already present and being manipulated to discover how to determine areas that are or arent food deserts. This week is about taking my own acquired and generated data sets and feeding them through the processes of making an open source web map. The mediums for this are QGIS, Tilemill, and Mapbox. Mapbox is the new addition to the processing and analysis portions of this week. Specifically tiled layers generated in Tilemill were uploaded to a base map in mapbox. You can see that below.

     This is a very rough product just highlighting that I could take a basemap which is the satellite imagery and add the layers over top, showing grocery stores (red dots) and various effects of food desert census tracts. The visible tracts are food deserts, all other areas should be considered not food desert. These deserts are then color coded by population affected, the darker the more people impacted. Once again this is a rough overview of a capability of adding these in Mapbox. The stylized finish product coming next week will involve much more functionality as it transitions to a full functioning web map through the use of Leaflet. This will be like last weeks map example, only tailored with my personal study area and information. So you might ask what has been done so far?

    My data is for the Palm Springs city area as defined by the US Census Places layer which is a subset of Riverside County California. My boundary files for this area were all derived from the US Census acquired partnership files. The layers obtained include state outline, Riverside County Boundary, Places within Riverside county, and census tracts within riverside county, to include the US Census population data for 2010. The palm springs boundary was clipped from all of the places within Riverside county, then used as the study area to clip the appropriate study area census tracts. Tabular census data was joined to the census tracts by tract ID.
    Locating the pertinent grocery stores was a combination of Google Earth searching, Google searching, and Yellowpages.com to cross reference all available grocery stores including fresh produce and the like. There were 9 of these points that were marked within Google Earth. The KML file was then exported from Google Earth, and within ArcMAP the KML to Layer tool was used. From there I had a problem uploading this point file into Tilemill and having it display appropriately. My workaround was to create a blank point feature class and heads up digitize new points over the existing point using the snap to point feature to ensure that the points were appropriately overlayed. This newly created layer was effectively useable with tilemill for the creation of the mapbox tiles.
     This data is already starting to show trends and pertinent information for the area, but I will save those results for next weeks post. Please stay tuned and thank you.