In this lab, we learned how to perform spatial interpolation to show the amount of rainfall in Los Angeles County. Using the same data, it is clear that the results are different depending on the used methods. I used the Inverse Distance Weight method for my first map set and the Kriging method for my second map set. Both map sets show rainfall throughout Los Angeles County from October 2010 till September 5, 2011. These maps show the normal, seasonal, and difference of rainfall in Los Angeles County. Analyzing the maps, you can see that precipitation levels the mid-eastern area in Los Angeles, particularly in the San Gabriel Valley, were the highest and in the northeast, in the Antelope Valley, were the least. This is because the Los Angeles Forest, having high mountain ranges, is located in the San Gabriel Valley, and in the Antelope Valley, it consists of deserts, proving the reason for those precipitation levels. Looking at the IDW map set, the Normal and Seasonal maps are very similar but with the Kriging method, none of the maps are similar. Comparing the two map sets, I think the IDW method better illustrates the rainfall data, simply because you can see the differences better than compared to the Kriging maps. Also, the IDW maps are easier to understand with the chosen colors. For example, comparing the Seasonal maps from the two methods, the Kriging output shows the colors in a distorted fashion, making it rather difficult to understand. Also, the Kriging maps seem to overlap the precipitation levels, further making it harder to understand and analyze. Lastly, it is harder to predict rainfall levels using the Kriging map sets compared to the IDW maps. Using these methods are definitely beneficial to analyze rainfall but I think the IDW method is the better method because the data is illustrated comprehensively and clearly. With the used data, the IDW method is effective to interpolate the points based on distance and is better suited for what we are trying to illustrate.
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