The Assessment of Spatial Autocorrelation through Constrained Multiple Regression

Most published measures of spatial autocorrelation (SA) can be recast as a (normalized) cross-product statistic that indexes the degree of relationship between corresponding entries from two matrices—one specifying the spatial connections among a set of n locations, and the other reflecting a very explicit definition of similarity between the set of values on some variable x realized over the n locations. We first give a very brief sketch of the basic cross-product approach to the evaluation of SA, and then generalize this strategy to include less restrictive specifications for the notion of similarity between the values on x. Using constrained multiple regression, the characterization of variate similarity basic to any assessment of SA can itself be framed according to the information present in the measure of spatial separation. These extensions obviate the inherent arbitrariness in how SA is usually evaluated, which now results from the requirement of a very restrictive definition of variate similarity before a cross-product index can be obtained.     

The Search for the 1871 Whaling Fleet of the Western Arctic: writing the final chapter

During 2015, the NOAA Office of National Marine Sanctuaries led a systematic seabed mapping survey along the Arctic coast of Alaska in search of whaling ships abandoned in 1871. The purpose of the expedition was to determine if wreckage from these abandoned ships was still present in the survey area, and, if so, to assess and document its location, status and condition. The project mapped approximately 50 km² of seabed using sidescan sonar and magnetometry and identified six sites that contained wreckage from at least two whaling ships. Magnetometry data also suggested that additional wreckage may be buried in the seabed.