Spatial Analytics
Understanding Spatial Relationships and Patterns
Spatial analytics are how we understand our world—mapping
where things are, how they relate, what it all means, and what actions to take.
From computational analysis of geographic patterns to
finding optimum routes, site selection, and advanced predictive modeling,
spatial analysis is at the very heart of geographic information system (GIS)
technology.
o
Where are my offices located? Where are my
delivery trucks? Understanding where is about putting the world in context.
This includes geocoding your data, putting it on a map, and symbolizing it in
ways that can help you visualize and understand your data.
o
How long is the river? How tall is the building?
How large are the coca fields? Measuring size and shape shows how large an
object is or describes a feature in terms of its area, perimeter, length,
height, and volume. It also helps to understand the distribution of multiple
features.
o
Which rivers are within 10 miles of a pipeline?
Have other crimes occurred at this location? Answering spatial questions often
requires an understanding of spatial relationships such as proximity,
coincidence, intersection, overlap, visibility, and accessibility.
o
Whether you're looking for the best route to
travel, the best corridor to build a pipeline, or the best location to site a
new store, spatial analysis helps you make more informed decisions about the
best locations and paths.
o
Where are clusters of high expenditures on
electronic goods? Where are the hot spots of cancer deaths? Detecting and
quantifying patterns in data can be used to find hot spots and outliers, find
natural data clusters, and analyze changes in patterns over time.
o
How will a forest fire spread based on
vegetation and wind? How will store size and travel distance attract or detract
customers? Spatial analytics let you use powerful modeling techniques to make
predictions and better understand our world.
To be continue...
Comments
Post a Comment