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5

If you want to use Census tracts the good people at Brown University have already done the hard work for you: Brown University Longitudinal Tract Database This resource contains tract-level variables from 1970-2000 interpolated to 2010 boundaries, facilitating longitudinal analysis.


5

Usually, you can get "average household size" for an area (or at least comparable area) from statistics agencies. I'd suggest using that. It really depends on which part of the world we are talking about. http://factfinder.census.gov/servlet/SAFFFacts suggests a value of 2.59 for the U.S. This would be an acceptable value if it's save to assume that most ...


4

Even within the US there is substantial variation in the mean number of persons per household (and even more variation in persons per address). Data are readily available in most developed countries. This histogram of 1999 data (as supplied by ESRI, using Census Bureau data) shows that the county average varies by more than a factor of 2. As you might ...


3

I don't think BLS unemployment data is available by ZIP. The MelissaData source does not actually report unemployment by ZIP code, it tells you the unemployment of the county in which the entered ZIP code is located. For example, a search for 02451, a small ZIP code in Waltham, MA (population 60k) returns 826k people in the labor force. This number must be ...


3

Not specifically demographic mapping, but the UN Food and Agricultural Organization folks have produced a number of publications with mappings at a world scale. The 2003 Environment and Natural Resources Working Paper No. 10 - "Towards a GIS-based analysis of mountain environments and populations" (B. Huddleston, E. Ataman, L Fe d'Ostiani)) may have some ...


3

You can find a series of papers with Google Scholar


2

OK, so you have points representing the centroids of the zip codes, but not the full boundaries of the zip codes themselves, right? I'm not sure how you would go about this in Ruby, and I think this may be more processing than you want to do, but a common way to do this in GIS software would be Voroni Polygons ...


2

Not exactly the same thing (nothing pre-configured) but most or much of this data (for the US) is in census data for free. You'd have to extract it and configure it yourself, although in some cases that's done for you, i.e. American Community Survey and the like. I also see on their home page that the census has mobile apps. Not the easiest site to ...


2

The Census Bureau provides this type of information. However, the amount of specificity you are asking about is more than what they are willing to provide (for privacy reasons). The closest table is B27015 which covers general insurance status by household income category at the Census Tract level. Oh, and for reference, the Census Tract level is the lowest ...


2

The only area in the US I could find is based in California by the Healthcare Workforce Development Division (HWDD). They collect GIS data in terms of: Medical Service Study Areas Health Professional Shortage Areas Medically Underserved Areas / Medically Underserved Population And other miscellaneous data The site contains shapefiles, PDF maps and Excel ...


2

I have used this kind of socio-economic data for a number of projects. It can be very helpful to break out of the district polygons by laying a square grid over the area (side length based on either metres or minutes), and then using a script, calculate a score for each grid cell (e.g. if a grid cell straddles two districts, then calculate a cell value ...


2

Regarding the correlation between zips and counties. The zip code boundaries are generally stable, assuming the post office doesn't close a ton of offices like some people think they need to do. The big problem is that many zip code areas cross political boundaries. Some small cities can be entirely within a larger zip code. While it is possible to match ...


1

Full Disclosure: I work for Caliper Corporation. I wouldn't normally try to sell anybody a product here, but this is a good fit. The Maptitude GIS Product from Caliper offers many of the tools and datasets that Community Analyst offers. Maptitude comes with the Census datasets included, including Zip code boundaries. The Maptitude website shows a list ...


1

I have recently been doing something like this (I work in health research) and I did not find the learning curve for QGIS exceptionally steep. I also used Google's free geocoding service with great results. Its usage limits shouldn't be a problem for you, especially if you only need neighbourhood-level accuracy and can de-duplicate your data. But I was using ...


1

I don't think you can get income data at block level for privacy issues. For blocks, you can only get population and households. As far as I know, the lowest level of geography you can get income data for is block groups. Block groups typically contain between 600 and 3000 people, have an optimal size is ∼1500 people and ∼30 blocks, though in Miami-Dade BGs ...


1

Be warned, joining census data to census tigerline shapefiles is a bit more complicated than a simple join. Downloading 2010 or 2000 Census Blocks is simple enough and can be found here: http://www.census.gov/geo/www/tiger/tgrshp2010/tgrshp2010.html When you select the file type you want there will be an option to download either the 2010 or 2000 ...


1

Well if you were doing it in ArcGIS then it would probably be easier to do it in the opposite order. There is US Census data freely available. Boundary files are here: http://www.census.gov/geo/www/cob/ Then you just need to append the data onto the attribute table. If you already have the average household income data with Census Tract IDs attached, it's ...


1

As others have said, it is a little unclear, but if I understand you correctly, you have polygon data with a population count attribute. You want to specify a centre and radius of a circle to find the approximate population under that circle. If that's the case, then the broad steps I'd use are: Calculate the population density of each polygon by dividing ...



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