21
Spatial Analysis – vector data analysis Lecture 8 10/12/2006

Spatial Analysis – vector data analysis

  • Upload
    teleri

  • View
    121

  • Download
    5

Embed Size (px)

DESCRIPTION

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. - PowerPoint PPT Presentation

Citation preview

Page 1: Spatial Analysis – vector data analysis

Spatial Analysis –vector data analysis

Lecture 810/12/2006

Page 2: Spatial Analysis – vector data analysis

Spatial Analysis tools in ArcToolBoxShapefile & Feature class

Coverage

Raster

Page 3: Spatial Analysis – vector data analysis

Details

Shapefile and feature class Coverage Raster

Page 4: Spatial Analysis – vector data analysis

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

Page 5: Spatial Analysis – vector data analysis

Clip

ff

Page 6: Spatial Analysis – vector data analysis

Select

Page 7: Spatial Analysis – vector data analysis

Split

Page 8: Spatial Analysis – vector data analysis

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

Page 9: Spatial Analysis – vector data analysis
Page 10: Spatial Analysis – vector data analysis
Page 11: Spatial Analysis – vector data analysis
Page 12: Spatial Analysis – vector data analysis
Page 13: Spatial Analysis – vector data analysis
Page 14: Spatial Analysis – vector data analysis
Page 15: Spatial Analysis – vector data analysis

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

Page 16: Spatial Analysis – vector data analysis
Page 17: Spatial Analysis – vector data analysis
Page 18: Spatial Analysis – vector data analysis
Page 19: Spatial Analysis – vector data analysis
Page 20: Spatial Analysis – vector data analysis
Page 21: Spatial Analysis – vector data analysis

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.