Running IDW for Fish & Salt

FISH
Our first attempt at interpolating was with the tilapia fish data.We examined what exactly we are interpolating. We felt that by separating the catch of fish per year it would give us a more narrow result for the sake of interpolating. We were hoping that interpolations would give us a result in which the number of fish per point would project come out to an average. Because we were working with year-round data, the number of fish varied per pull date. We felt that the results, regardless of the wide range of numbers, may still give us a good idea of the fish distribution throughout the lake in correlation to salinity.

SALT
We ran interpolations for each year of salinity, and the results were similarly radical to the interpolations for the fish data. Going back to examine the attribute data, I looked at the different Salinity fields in the 2003 layer. Since we had to create a new Salinity field due to the integer type, our N/A values were converted to 0. putting the fields next to each other, it is evident that the zero values are because of the N/A values. This means that perhaps the reason why each interpolation has a radical and not similar result could be in part of those zeros making the numbers skewed. This definitely helps us narrow down what we are interpolating in terms of salt. When it comes to fish data, the zeros represent no fish.

Our next step is to go back into the five layers we originally exported per year, choose the fields in which the Salinity is above zero, and interpolate them all over again.