Module 11 - Google Earth

I chose the east coast of Lake Michigan for the high year round wind power class. This area appears to have very low human habitation so noise and shadow flicker will not be a factor. Bird migration traffic is low for this area and it would appear that environmentally, there would be little impact on landscape. This particular spot is where farmland is close to the lake edge - where building on existing solid ground will have little effect on natural areas along this coast and the wind power density decreases dramatically when moving inland here. Power produced by the windfarm could easily sustain the surrounding towns and farms year round. The golfcourse nearby may be the main source of complaints for this location!

Module 10 - Isohyet Map

I used the manual interpolation method but with the thickness of the contour line and for the sake of my sanity, I approximated the position of it between values. This method was good in the most part but still left a little guesswork but nothing that would alter the line dramatically, I hope! Also, manipulating the lines after drawing them was not much fun but necessary to iron out sharper curves.

Flow Map - Module 9

I chose the Quartic Authalic projection (which I selected in error thinking it was conformal - now I realise there would be better selections!) and deleted Antarctica as, well, they have no emigrants. I also played with the central meridian but Asia was split when I did that so not appropriate. I liked Joe's 'split continent' method but chose the conventional map for simplicity as only 6 values are mapped. Also, with so few values, I decided to create an 'actual value' legend. To me, the hand arrowhead is eye catching and makes me smirk every time I look at it, possibly because it reminds me of Monty Python! The thickest line value was 39pt and the smallest 0.7pt.

Contiguous Cartogram - Module 8

I went to town on this one - 13 iterations. Why? Because only a general recognition is expected of the world so this distortion would seem acceptable, besides, the one in the lecture was distorted moreso! I do not feel an inset map of the world is necessary. Identifying individual countries is not the purpose here, just the spatial pattern of the main contributors to the GDP and to show the differences between adjoining areas.

The most obvious anomaly here is Japan - the 'tongue' of Asia; this perfectly illustrates the impact that this one country has to the GDP and overshadows its neighbors, even accounting for the fact that adjoining countries post good figures too.

I played with various projections but settled for Robinson because of its minimal distortion of area and shape.

'Non-contiguous' Cartogram

Here's my proportional symbol map.....oops sorry, circular non-contiguous cartogram. I did try to create a non-overlapping feature shape cartogram but failed to discover in this instance how to do this or whether it was feasible.

Like the contiguous map, identifying individual countries should not be the intent here but the spatial pattern as described above.

Module 7: Dot Map

I determined the dot value of 2660 from the lowest county housing units value resulting in 2750 dots for the whole state! After some trial and error, I used a dot size of 0.8pt to fill 181 dots within the county with the highest calculated housing density; Pinellas. The basemap and dots were enlarged 160% to fill the width of the page. The dot was inappropriately small to be represented in a legend so the value was simply described. With the limitation of the page size and quality of the jpeg image, it is unlikely that original raw totals could be garnished from the map, however I did maintain a fairly high level of accuracy regarding the clusters where towns and cities are located by using an atlas.