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Spatial Analysis – vector data analysis

Spatial Analysis – vector data analysis. Lecture 2. Recap: three data models. Vector Raster Geodatabase (object-oriented data model) Vector data and table feature class is the basis Raster data.

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Spatial Analysis – vector data analysis

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  1. Spatial Analysis –vector data analysis Lecture 2

  2. Recap: three data models • Vector • Raster • Geodatabase (object-oriented data model) • Vector data and table • feature class is the basis • Raster data The real world is complex. Neither discrete (object) nor continuous (field) can perfectly represent some of real world situations. We need combined model: dual, hybrid, or object-oriented approach

  3. Spatial Analysis tools in ArcToolBox Vector data analysis: Shapefile & Feature class/table Raster data analysis

  4. Details Vector

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

  6. Clip XY tolerance: The minimum distance separating all feature coordinates (nodes and vertices) as well as the distance a coordinate can move in X or Y (or both). You can set the value to be higher for data that has less coordinate accuracy and lower for datasets with extremely high accuracy. Learn more from help

  7. Select

  8. Split

  9. Table select

  10. 2. Overlay • Joining two existing sets of features into a single set of features to identify spatial relationships between the input features. • Erase • Identify • Intersect • Spatial Join • Symmetrical difference • Union • Update

  11. 3. Proximity • Identify features that are closest to one another, calculate the distances around them, and calculate distances between them. • Buffer • Create Thiessen Polygon • Generate Near Table • Multiple ring buffer • Near • Point distance

  12. Not dissolved Dissolved

  13. Example

  14. 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 neighbor, 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.

  15. Statistics • Basic statistic to the attribute table • Frequency • Summary statistics

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