1 / 8

GEOGRAPHICAL STATISTICS GE 2110

GEOGRAPHICAL STATISTICS GE 2110. Zakaria A. Khamis. Spatial Descriptive Statistics. Descriptive measures of spatial data are important in understanding and evaluating such fundamental geographic concepts  accessibility and dispersion

jerome-grimes
Télécharger la présentation

GEOGRAPHICAL STATISTICS GE 2110

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. GEOGRAPHICAL STATISTICSGE 2110 Zakaria A. Khamis

  2. Spatial Descriptive Statistics • Descriptive measures of spatial data are important in understanding and evaluating such fundamental geographic concepts  accessibility and dispersion • E.g. it is important to locate public facilities so that they are accessible to defined populations • Spatial measures of centrality applied to the location of individuals in the population will result in geographic locations that are in some sense optimal with respect to accessibility to the facility Zakaria Khamis

  3. Spatial Descriptive Statistics • Similarly, it is important to characterize the dispersion of events around a point • It is useful to summarize the spatial location of individuals around a hazardous waste site • Are the individual with a particular disease less dispersed around the site than are people without the disease? If so, this could indicate that there is increased risk of disease at location near the site

  4. Mean Center • This is the most common used spatial measure of central tendency • For point data, x and y coordinates of the mean center are found by simply finding the mean of the x coordinates and the mean of y coordinates • For areal data, the mean center can be found by using the centroids of each area. It is often useful to attach weights to the x and y coordinates

  5. Mean Center • For instance, to find the center a population, the weights are taken as the number of people living in each subregion • The weighted mean of x coordinates and y coordinates then provides the location of the mean center of population

  6. Mean Center • Where the wi are the weights (e.g. population in region i) and xi and yi are the coordinates of the centroid in region i • Conceptually, this is identical to assume that all individuals living in a particular sub-region live at a pre-specified point  centroid • E.g. the mean center of population in the USA has migrated west and south over time

  7. Standard Distance • Aspatial measures of variability, such as variance and standard deviation, characterize the amount of dispersion of data points around the mean • Similarly, the spatial variability of locations around a fixed central location may be summarized • The standard distance is defined as the square root of the average squared distance of points to the mean center (Bachi 1963)

  8. Standard Distance • Where dic is the distance from point i to the mean center • The square root can be taken out from the equation because, distance is absolute

More Related