Francisca11
Uploaded by
18 SLIDES
0 VUES
0LIKES

Spatial Point Pattern Analysis.......

DESCRIPTION

point pattern analysis

1 / 18

Télécharger la présentation

Spatial Point Pattern Analysis.......

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. Spatial Point Pattern Analysis Explain the concept of spatial point pattern analysis

  2. Spatial Point Pattern Analysis Spatial point pattern analysis (PPA) is a statistical technique that is used to study the spatial distribution of points. PPA can be used to identify patterns of clustering, dispersion, and regularity in point data. PPA can also be used to model the spatial process that generated the point pattern.

  3. PPA is a powerful tool for a variety of applications, including:

  4. Epidemiology: PPA can be used to identify clusters of disease cases, which can help to identify the source of the outbreak.

  5. Ecology: PPA can be used to study the distribution of plant and animal species, which can help to understand the factors that influence their populations.

  6. Urban planning: PPA can be used to identify areas of high and low crime, which can help to plan for crime prevention measures.

  7. Retail planning: PPA can be used to identify areas of high and low demand for retail goods, which can help to plan for the location of new stores.

  8. Methods of PPA There are a variety of methods that can be used for PPA. Some of the most common methods include:

  9. Descriptive statistics: Descriptive statistics can be used to summarize the basic characteristics of a point pattern, such as its central tendency, dispersion, and density.

  10. Distance-based measures: Distance-based measures can be used to quantify the spatial relationships between points in a point pattern. Some common distance-based measures include the nearest neighbor distance, the Ripley's K function, and the L function.

  11. Density-based measures: Density-based measures can be used to identify areas of high and low point density in a point pattern. Some common density-based measures include the quadrat count, the kernel density estimate, and the Ripley's L function.

  12. Interpretation of PPA Results The results of PPA can be interpreted in a variety of ways. Some common interpretations of PPA results include:

  13. Clustering: Clustering refers to the tendency for points to be located close together. Clustering can be caused by a variety of factors, such as the presence of a common resource or the influence of a spatial process.

  14. Clustering

  15. Dispersion/Random: Dispersion refers to the tendency for points to be spread out over a large area. Dispersion can be caused by a variety of factors, such as the presence of a physical barrier or the influence of a random process.

  16. Dispersion/Random

  17. Regularity: Regularity refers to the tendency for points to be arranged in a regular pattern. Regularity can be caused by a variety of factors, such as the presence of a man-made structure or the influence of a natural process.

  18. Regularity

More Related