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Spatial Analysis – vector data analysis

Spatial Analysis – vector data analysis. Lecture 8 10/12/2006. Spatial Analysis tools in ArcToolBox. Shapefile & Feature class. Coverage. Raster. Details. Coverage. Shapefile and feature class. Raster. Extract.

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Spatial Analysis – vector data analysis

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  1. Spatial Analysis –vector data analysis Lecture 8 10/12/2006

  2. Spatial Analysis tools in ArcToolBox Shapefile & Feature class Coverage Raster

  3. Details Coverage Shapefile and feature class Raster

  4. Extract • To create a new subset from the input (features and attributes in a feature class or table) based on spatial intersection or an attribute query. • Clip • Select • Split • Table select only

  5. Clip • ff

  6. Select

  7. Split

  8. Overlay • Joining two existing sets of features into a single set of features to identify spatail relationships between the input features. • Erase • Identify • Intersect • Symmetrical difference • Union • Updata

  9. Proximity • Identify features that are closest to one another, calculate the distances around them, and calculate distances between them. • Buffer • Multiple ring buffer • Near • Point distance

  10. How to form Thiessen polygons • Also known as 'Voronoi networks' and 'Delaunay triangulations', Thiessen polygons were independently discovered in several fields of study, including climatology and geography. They are named after a climatologist who used them to perform a transformation from point climate stations to watersheds. • Thiessen polygons can be used to describe the area of influence of a point in a set of points. If you take a set of points and connect each point to its nearest neighbour, you have what's called a triangulated irregular network (TIN). If you bisect each connecting line segment perpendicularly and create closed polygons with the perpendicular bisectors, the result will be a set of Thiessen polygons. The area contained in each polygon is closer to the point on which the polygon is based than to any other point in the dataset.

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