Raster data, by organizing the data in uniform grids, is useful to analyze continuous phenomena or find some information at the subobject level. We will use continuous elevation and proximity data in this case, and we will look at the subapplicant object level —at the 30 meter-square cell level. You would choose a cell size depending on the resolution of the data source (for example, from sensors roughly 30 meters apart), the roughness of the analysis (regional versus local), and any hardware limitations.
First, let's make a few notes about raster data:
Nodata refers to the cells that are included with the raster grid because a grid can't have completely undefined cells; however, these cells should really be considered off the layer.
QGIS's raster renderer is more limited than in its proprietary competitors. You will want to use the Identify tool as well as custom styles (Singleband Pseudocolor) to make sense of your outputs.
In this example, we will rely heavily on the GDAL...