Types of Spatial Data Query: Spatial and Attribute of Combination (Especially for GATE-Geospatial 2022)

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A spatial query is a special type of database query supported by geodatabases and spatial databases. Spatial data query means to retrieving data by working with map features. There are three types of the spatial data query:

This Diagram Shows Three Types of the Spatial Data Query

1. Feature Selection by Graphics

In spatial data query selection by graphics are different circle, rectangle, etc.

Diagram Shows Circle with a Specified Radius Drawn Around Su …

A circle with a specified radius is drawn around Sun Valley. The circle is then used as a graphic object to select point features within the circular area.

2. Feature Selection by Spatial Relationship

There are four feature selections by spatial relationship:

This Diagram Shows Four Feature Selections by Spatial Relati …

I. Containment

Select features that fall completely within features used for selection. Examples include finding schools within a selected county, and finding state parks within a selected state.

II. Intersect

Selects features that intersect features used for selection. Examples include selecting land parcels that intersect a proposed road, and finding settlements that intersect an active fault line.

iii. Proximity/Adjacency

Selects features that are within a specified distance/no distance of features used for selection. Examples of spatial adjacency include selecting land parcels that are adjacent to a flood zone, and finding vacant lots that are adjacent to a new theme park.

3. Combination of Attribute and Spatial Data Queries

Spatial and attribute queries can easily be combined simply by including the relevant properties for each type of query.

  • A query that extracts features from a layer based on their location, for example, clicking on a point and listing its attribute data is a spatial query.
  • A query that extracts features from a layer based on the value of its attribute data: for example, β€˜select polygons with an unemployment rate greater than 15 %’ would be an attribute query.

Following query is combination of spatial and data attributes. Find gas stations that are within one mile of a freeway exit in southern California and have annual revenue of $ 2 million:

  • Locate all freeway exits in the study area, and draw a circle around each exit with a 1-mile radius. Select gas stations within the circles through spatial data query. Then use attribute data query to find gas stations that have annual revenues exceeding $ 2 million.
  • Locate all gas stations in the study area, and select those stations with annual revenues exceeding $ 2 million through attribute data query. Next, use spatial data query to narrow the selection of gas stations to those within 1 mile of a freeway exit.
Figure Shows Combination of Sptial and Attribute Data Querie …

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