# assign14 - Assignment 14 Spatial Autocorrelation See...

This preview shows pages 1–3. Sign up to view the full content.

1 Assignment 14. Spatial Autocorrelation See Mitchell, The ESRI Guide to GIS Analysis , vol. 2, Spatial Measurements & Statistics ; Fotheringham et al., Geographically Weighted Regression ; GeoDa, instructions; CrimeStat , instructions. Conceptual Issues & Basic Measures § Always check for possible data errors (e.g., sum “Race,” gender, and housing tenure categories to make sure that they amount to the appropriate totals). § “Spatial statistics let you compare the spatial distribution of a set of features to a hypothetical random spatial distribution…” (Mitchell, 19). Alternatively, they compare local empirical distributions to average empirical distributions across the study area. o Null hypothesis: the features are evenly distributed across the study area. o “To the extent that your distribution differs from a random distribution, there is a trend or pattern in the data” (Mitchell, 19). Alternative hypothesis: there is a trend or pattern in the distribution of the features across the study area. § A pattern may vary according to the geographic scale of the study area and its borders : o Dispersed within a small study area but clustered within a larger area, or vice versa; or it may vary in other ways. o Study area borders can bias results; perhaps use border buffer to exclude border points from analysis or give higher weight to border points (which tend to have fewer neighbors). § How the data are represented influences the results of spatial statistics (Mitchell, pages 184-89): o Distance measures are straightforward for point data but not for line data (e.g., is distance measured at the midpoint, endpoint, or a randomly selected point on a line? is the line continuous or a series of short lines?). o For areas, centroid-to-centroid distance or distance between nearest locations on the boundaries are used, but centroids should be used only if areas are roughly the same size and shape and merged areas will alter distance calculations. o For raster data, smaller cell size creates many features (cells) with the same or very similar sizes and hence exaggerates spatial dependence. o Buffering a boundary area and excluding observations within it may compensate for the tendency of boundary observations to have fewer neighbors. Giving boundary observations higher weighting may also do the same. I § Measuring the pattern formed by the locations of features: quadrant analysis & nearest neighbor § Quadrant analysis : assess a feature’s spatial distribution by overlaying a grid and measuring the density of features (i.e. the number of features per unit

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
2 area). E.g., for small tight clusters of events such as burglaries, emergency 911 calls, earthquakes, but not for features that have direct interaction with each other. o Quadrant analysis does not consider the proximity or relationship among features.
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### What students are saying

• As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

Kiran Temple University Fox School of Business ‘17, Course Hero Intern

• I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

Dana University of Pennsylvania ‘17, Course Hero Intern

• The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

Jill Tulane University ‘16, Course Hero Intern