Visualizing data for environmental analysis

TL;DR: Several types of statistical maps used for environmental analysis were chosen to show the advantages, disadvantages, and data limitations of each.

Abstract: The Environmental Restoration Project at Los Alamos National Laboratory (LANL) has over 11,000 sampling locations in a 44 square mile area. The sample analyses contain raw analytical chemistry values for over 2,300 analytes and compounds used to define and remediate contaminated areas at LANL. The data consist of 2.5 million records in an oracle database. Maps are often used to visualize the data. Problems arise when a client specifies a particular kind of map without fully understanding the limitations of the data or the map. The ability of maps to convey information is dependent on many factors, though all maps are data dependent. The quantity, spatial distribution, and numerical range of the data can limit use with certain kinds of maps. To address these issues and educate the clients, several types of statistical maps (e.g., choropleth, isarithm, and graduated symbol such as bubble and spike) used for environmental analysis were chosen to show the advantages, disadvantages, and data limitations of each. By examining both the complexity of the analytical data and the limitations of the map type, it is possible to consider how reality has been transformed through the map, and if that transformation accurately conveys the information present.