1.4. Layers

In Cartographica, data is organized into Layers. A Layer consists of one type of data (point, line, area, or imagery), and contains one or more features of each type. Each of these features usually contains geospatial information (one or more sets of X,Y and possibly Z coordinates) as well as optional reference data that describes characteristics of the features in the layer. It is the attachment of the reference additional data to the geospatial information that makes a GIS like Cartographica so powerful. By using the geospatial data, correlations can be made between information in the reference data, leading to informative maps and insightful data analysis.

Layers Alone and Composited

Figure 1.2. Layers Alone and Composited

1.4.1. Types of Layers

Cartographica uses a number of different types of layers to represent data in MapSet. Each one can be enabled or disabled, and can have various attributes manipulated, as appropriate.  A basic description of each is included here.

Table 1.1. Layer Descriptions

VectorVector layers are comprised of lines, points, or polygons. There are many tools that can use the Vector layers for data analysis and manipulation. Common uses are representing discrete locations (points), roads or rivers (lines), and areas (polygons).
RasterRaster layers are comprised of a grid of individual data cells that can be interpreted many ways. Common uses are representing height or depth data, containing data for frequency or counts of incidents in specific locations, or providing color or false color data from satellite imagery. There are specialized tools in Cartographica to process Raster data, including computing topography, and merging with similar data.
GridGrid layers provide geospatial context to other layers. When added to maps, they render a grid of lines demarcating areas in the Map or Layer reference system.
AnalysisAnalysis layers are specialized Raster layers. They contain not only the resultant raster data from an analysis, but also the parameters used to make that analysis.