##### DC-03 - Global Positioning System

- Explain how GPS receivers calculate coordinate data
- Discuss the relationship of GPS to the Global Satellite Navigation System
- Explain “selective availability,” why it was discontinued in 2000, and what alternatives are available to the U.S. Department of Defense
- Explain the relationship of the U.S. Global Positioning System with comparable systems sponsored by Russia and the European Union and the Global Navigation Satellite System
- Discuss the role of GPS in location-based services (LBS)
- Specify the features of a GPS receiver that is able to achieve geometric accuracies on the order of centimeters without post-processing
- Explain the relevance of the concept of trilateration to both GPS positioning and control surveying
- Perform differential correction of GPS data using reference data from a CORS station
- List, define, and rank the sources of error associated with GPS positioning
- Distinguish between horizontal and vertical accuracies when using coarse acquisition codes/standard positioning service (C-codes) and precision acquisition codes/precise positioning service (P-codes)

## AM-22 - Global Measures of Spatial Association

Spatial association broadly describes how the locations and values of samples or observations vary across space. Similarity in both the attribute values and locations of observations can be assessed using measures of spatial association based upon the first law of geography. In this entry, we focus on the measures of spatial autocorrelation that assess the degree of similarity between attribute values of nearby observations across the entire study region. These global measures assess spatial relationships with the combination of spatial proximity as captured in the spatial weights matrix and the attribute similarity as captured by variable covariance (i.e. Moran’s I) or squared difference (i.e. Geary’s C). For categorical data, the join count statistic provides a global measure of spatial association. Two visualization approaches for spatial autocorrelation measures include Moran scatterplots and variograms (also known as semi-variograms).