Spatial Interpolation

In this lab we were tasked to create a map of precipitation of Los Angeles county. We were given data on total and normal precipitation collected from stations that measuerd rainfall. The first task was to convert the latitude and longitude to decimal degrees and then manually type in the rainfall data. This data was then imported into a GIS and various interpolation techniques were applied.

Inverse distance weighting (IDW)would not be an appropriate interpolation technique because the distribution of rain stations that actually collected both normal and total rain fall was not dense enough to capture an accurate extent of precipitation across Los Angeles county. IDW becomes less accurate as the distance to data points increases so the precipitation map would be accurate at rain station locations and inaccurate for areas in between stations.

Kriging would be a more suitable interpolation technique because it takes into account the fact that precipitation may be spatially correlated. So this method of interpolation should provide a better estimate of the level of precipation across Los Angeles county.

Below is a map of precipitation in Los Angeles County based on IDW and kriging.