Tuesday, April 3, 2012

DEM

    
     A Digital Elevation Model (DEM) is a data set containing elevation values either in raster data form or in a Triangular Irregular Network (TIN).  These data sets are commonly created through remote sensing techniques but can also be made through land surveying.  This data is also regularly used in a GIS and is the basis for relief maps. The example shown above is the DEM of the contiguous United States. With this DEM, we are able to observe the commonly known mountain ranges of the U.S. (the Rocky Mountains in the west and the Appalachain Mountains along the east coast).

Black and White Aerial Photos

    


     Black and white aerial photography is data gathered in the visible spectrum rather than in the infrared.  In this part of the electromagnetic spectrum, black and white color values are exactly what we see in the visible spectrum. This aerial imagery allows us to analyze large areas of either developed or undeveloped land in a variety of different spatial resolutions. This black and white aerial example shows the reconstruction of Johnstown, PA in 1891; two years after it was flooded.

Infrared Aerial Photo


Infrared aerial photos are very useful to reflect the health of vegetation and also bodies of water. It can track temperature to monitor dangerous conditions in areas such as chemical plants and coal mines. Anything that gives off a heat signature can be shown on these amazing images. This image shows field-unit geometries in front of the background of color-infrared aerial photographics.

Cartographic Animations


     Cartographic animations are an important way of displaying results and falls with geovisualization.  Having a time series of information can inform the viewer of things that aren't necessarily apparent when looking from image to image without the assistance of an animation. Trends become distinct as we see images before and after a single frame. This can even allow us to make predictions and forecasts based off of previous behavior. This animation is of Hurricane Andrew that struck in 1992. The animation shows the progression of the hurricane as it traveled across the state of Florida.

Dot Distribution Maps



     These types of maps are an easy way to depict density of whatever variable is being plotted. The visual clustering of dots shows a high density of the variable occurring while large spacing inbetween the dots shows low density values. This example shows earthquake locations for events between 1965 and 1995. The red dots are shallow earthquakes, the green are intermediate depth, and the blue and purple are deep.

Digital Raster Graphic (DRG)




     A DRG is a digital image resulting from scanning a paper USGS topographic map so that it could be used on a computer. The raster image usually includes the original border information (also known as the map collar). The map file is then UTM projected and georeferenced to the surface of the earth. These are commonly used in GIS applications, also. This particular example is a DRG of an area in West Virginia.

Public Land Survey System (PLSS)


     A PLSS is a reference scheme for recording property ownership by section, township, range, and aliquot parts in the United States. It is surveying method used historically over the largest fraction of the United States to survey and spatially identify land parcels before designation of eventual ownership, particularly for rural, wild or undeveloped land. The system divides up the land into relatively equal partition which is easier to manage. It also helped  to facilitate the urbanization of areas by using a square block system for the road design. the example shown is a portion of the Minnesota's statewide PLSS base map; this view is a small part of the 1:100,00 scale Worthington quadrangle. This example makes it very clear to see the different numbered sections showing which land parts belong to which section.

DOQQ

    
     A Digital Orthophoto Quarter-Quadrangle (DOQQ) is an image that has been geometrically corrected so that the distance between two point is the true distance. They are recognized as one of several critical geo-spatial data sets needed to effectively manage and use geographic information systems in statewide, regional and local databases and spatial applications. This example shown about is part of the Farmville NE DOQQ. Maps of this type are often put into a GIS and are used to make vector data files.






DLG


      A digital line graph (DLG) is a cartographic map feature represented in digital vector form that is distributed by the U.S. Geological survey (USGS). DLGs are collected from USGS maps and are then distributed in various scales, and can have up to nine different categories of features depending on the chosen scale. This DLG example shows a section of Ottawa, Canada transformed into a digital vector form. This type of graph can be put into a GIS and used to maintain databases of relevant information.

Doppler Radar


     Doppler radar is a tool that makes use of the doppler effect to track objects at a distance. This type of technology is most commonly used in meteorology; more specifically used in tracking storms. Doppler radar allows us to pick up a storms size and speed; it can give us this information even days before it hits and area. The doppler radar shown above shows the size and speed of Hurricane Ivan before it hit the Gulf coast. The colors represent the intensity of the storm with red being the strongest.

Univariate Maps


     A univariate choropleth map is a type of thematic map in which the non-location data is all of the same kind; they only display a single variable. Population density, annual rainfall, and birth rates are all examples of univariate data. This map example shown represents the percentage of Americans living in poverty in different rural countries within the United States in 2008; people in the south seem to have higher poverty rates than those living in the north.

Unstandardized Choropleth Maps


     Unstandardized choropleth maps are thematic maps which contain data that has not been areally-averaged, though it still allows comparison between variables. This example shows the predictions of the 2008 Presidential Election. It displays the number of electoral votes of each state and is colored (red for republicans, blue for democrats) to indicate which candidate those electoral votes are predicted to go to.

Bivariate Choropleth Map


     A bivariate choropleth map is a thematic map that displays two variables or statistics by using two different sets of symbols or colors in order to illustrate a relationship between the two variables. This example shows the population density and percentage change in that population over a period of time in Russia. This is is considered a bivariate choropleth map because it is displaying the relationship between two variables, population density and percentage population change, and a different color scheme is being used for each variable.

Unclassed Choropleth Map

    

    

     Unclassed choropleth maps are similar to classed choropleth maps; however, unclassed choropleth maps do not have an averaged statistic towards each particular color. If you wish to create a map that maintains the data relation, unclassified data theoretically does a better job than classified data because unclassified data allows us to maintain the numerical relations between data. This means that the color shades on an unclassified map are directly proportional to the values of each enumeration unit; there are many shades of each color to show the diversity of the statistics. This unclassified map contrasts the democrats (blue) from the republicans (red). Most states are not completely republican or democratic so there are many shades of the combined blue and red which make a purple hue.


 

Classed Choropleth Maps



     This type of map allows a variable within different areas to be mapped; this helps with understanding the spatial distribution of this variable over larger distances. The variables that can be measured with this method are limitless. This classed choropleth map was created to show the population of Hispanic people per square kilometer in each state.

Standardized Choropleth Maps

 

     Standardized choropleth maps normalize data according to a certain area. They analyze data in the form of a percent so that areas of varying size can be compared to one another. In the choropleth map catagory, the standardized map is a better mapping technique for analyzing data because of the modifiable areal unit problem (MAUP). This example shows the population per square kilometer that is represented for an area divided into multiple areas. This map is standardized because it shows areas of different (population) sizes and depicts them by color so that they can be compared to one another. The darkest areas indicate locations with a higher population.