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Hi Lauren, Thanks for responding to my e-mail. Here's some more information about the research. Yes, the trawling locations are randomly chosen within a trawl zone (limited by depth). We want to know whether there is a clustering of turtles (presence/absence) AND if there is clustering, where the clustering of high catch numbers is located. Any suggestions you can give would be much appreciated. Thanks! Jessica B.
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02-10-2012
10:13 AM
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When I ran Moran's I, it produced an appropriate z-score and Moran's Index, but the p-value was 0.000000. The html report indicated that the data was strongly clustered, but I've never seen a p-value of zero. I'm concerned that there might be an issue with the dataset/results.
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12-13-2011
12:11 PM
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I have a point dataset for sea turtles. Each point represents a single trawl where 0-10 turtles were collected. There are 4500+ points, most of which have 0 catch. The study area encompasses the southeast. We want to know if 1.) there is clustering of turtles and 2.) if there is clustering of the high catch numbers. We want to know this for the overall area and by region (there are four smaller regions). 1.) Would Moran's I and Hot Spot Analysis be the best tools in the spatial stats toolset to answer these questions? We tried aggregating the data into 1 x 1 min grids, but when we ran the 'Incremental Spatial Autocorrelation' the Z score never peaked and kept going up and up. We ran it again on the individual points, and got a peak. 2.) Is it appropriate to run either of these tools on incident data or would it be better to try to find a finer scale on which to aggregate? Some of the Hot Spot Analysis information I read suggested that for datasets with 3000+ features, it would be advisable to construct a spatial weights matrix file. 3.) How is this better than choosing one of the other spatial relationships listed (e.g. fixed distance)? Thanks!! Jessica B.
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12-06-2011
12:08 PM
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