An issue that most researchers tend to have is the problem of getting the data.    At times our data seems so close yet it is so far away. We as researchers often know what type of data we want and we may also know that it already exists.  However, we may not always know how to get the data.  Even more frustrating is finding the data that you need and realizing that it is not in a useable form.  Finding the correct data in a useable form has been my number one problem.  Thankfully a past student has come to my rescue.  She suggested using the National Historical Geographical Information System to access census data.  The NHGIS site provides, free of charge, aggregate census data and GIS-compatible boundary files for the United States between 1970 and 2011.  I intend to carry out a geographical approach to to understand and predict how the local spatial structure of new environmental amenities will influence and shape the way in which environmental justice communities will evolve.  This research aims to develop a novel framework/approach to understand the evolution of environmental justice communities in relation to the incorporation and management of natural amenities.  To achieve this objective I will complete several benchmark activities including:

Observe spatial and temporal variation and patterns of neighborhood characteristics (educational attainment, income, racial composition, household tenure, renters) over a 70-year period

• There are many issues that will arise as I attempt to accomplish this task.  For instance, the temporal resolution of my data will be in 10-year increments, this may not entirely capture the patterns that I will be looking for.
•  Assessing variables temporally will prove to be difficult.  For example, educational attainment is a variable that is not available in all years of the census data.
•  I will also consider how the census tracts and census blocks change over time which could

Quantitatively assess the spatial and temporal variation and patterns of natural amenities over a 70 year period, using satellite imagery and aerial photography.

•  There is a lot of uncertainty that is associated with using aerial photography and satellite imagery.
•  One that I considered using to look at green space in an area is to calculate NDVI, which is the Normalized Difference Vegetation Index.  In short, it is a remote sensing technique to assess whether the target being observed contains live green vegetation or not
• Another technique I am considering is to use an unsupervised k-means classification to explore and assess the change from open/greenspace to impervious surface.

There are a number of things that I still need to consider when trying to carry out this project but, this is a start.  My plans for the next week is to continue to explore my data and run some tools that will help to better describe the distribution of certain neighborhood characteristics.