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Lecture 7

by: Sierra

Lecture 7 FNR 210


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About this Document

GIS Models
Natural Resource Information Management
Ningning N. Kong
Class Notes
Natural Resources, information management, forestry
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This 29 page Class Notes was uploaded by Sierra on Friday March 4, 2016. The Class Notes belongs to FNR 210 at Purdue University taught by Ningning N. Kong in Spring 2016. Since its upload, it has received 17 views. For similar materials see Natural Resource Information Management in Agriculture and Forestry at Purdue University.

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Date Created: 03/04/16
GIS Models 1  Topics we learned in previous weeks: ◦ Symbol & Maps, GIS Data Models, Spatial Data Editing, Georectification, Creating Spatial Database Data & Display GIS Analysis 2  The process of using combinations of commands to answer questions about spatial phenomena.  Is a set of interacting, ordered map operations that act on raw data, to simulate a spatial decision- making process. 3  Cartographic models  Spatio-temporal models  Network models  Others 4  Application of spatial operations such as buffers, interpolation, reclassification, and overlay to solve problems ◦ Often temporally static (features represented at a fixed period of time) ◦ It may include a temporal component when it compares change through time (comparing vegetation in 1990 to vegetation in 2000) ◦ Input data/values don’t change during the model 5  Ranking sites by suitability for home construction using four criteria ◦ Slopes should not be too steep. Steep slopes may substantially increase costs or may preclude construction. ◦ A southern aspect is preferred, to enhance solar warming. ◦ Soils suitable for on-site septic systems are required. There is a range of soil types in the study area, with a range of suitable soils for septic system installation. ◦ Sites should be far enough from a main road to offer some privacy, but not so far as to be isolated. 6 7 8  Finding features by attributes/locations - Query  Spatial manipulation - Overlay, buffer, etc.  Terrain analysis  Raster modeling  Spatial interpolation  Many other spatial models, such as pattern detection, clustering, etc. 9  Refers to GIS operations that manage and analyze your GIS data.  In software – it includes tools that perform analysis and managing your spatial data.  A tour of geoprocessing ◦ Geoprocessing menu – demo ◦ ArcToolbox ◦ Search window ◦ Tool dialog box ◦ Results window ◦ Backbround processing 10  Query – week 8 (next week) ◦ Attribute based query ◦ Location based query  Simple spatial analysis – week 9 ◦ Buffer ◦ Overlay  Today’s lecture – prepare your attribute data for analysis 11  Fields – ◦ Unique identifier field for vector data – FID field in shapefile, or ObjectID field in geodatabase file. ◦ Shape field: required geometry field – Polygon, Polyline, Point 12 • Each field in the table has a “Type”. When creating new field in a vector attribute table, you can choose one of these types: • Integer: Short, long • Decimal: float, double • Text • Date • Blob • GUID • Check “Properties” for existing field type.  Sort field  Statistics  Summarize Generate new table to generalize attribute for selected fields.  Add field  Field calculator  Attribute T able (spatial) geospatial datasetins information about specific features in a 1 record for each feature  can have multiple fields  Stand Alone T able (non-spatial) A table that is independent of the geographic data in the map  The data may come from a Excel spreadsheet, field work, etc.  Need a OID (Object Identification numbers) field. Spatial vs. Non-Spatial data The connection between spatial and non-spatial data are made through databastables  T ables can be joined or related to each other by using a common field (column) Two methods to associate tables in ArcMap based on a common field Join appends the attributes from one onto the other ◦ Label or symbolize features using joined attributes Relate defines a relationship between two tables  Cardinality: how data relate to each other • 1 to 1 relationship - each record (row) in the destination table has a match in the source table • Many to 1 - each record in the destination has multiple matches in the source tables • 1 to Many - each record in the destination table match a single record in the source table One parcel One parcel Many parcels Many parcels has one owner has many owners have one owner have many owners or  Associate tables with common column key values ◦ Must be same data field types  Must know table relationships (cardinality) Additional Feature attribute table attribute table Example: Associating county attribute table with separate table of poverty estimates by county for WV  Common field  Records with the same value are matched  Some cleaning necessary Must remove dashes! Copyright – Kristen S. Kurland, Carnegie Mellon University Appends the attributes of two tables Assumes one-to-one or many-to-one cardinality County Attributes (before Join) WV_Poverty98 One-to-one County Attributes with joined poverty data (virtual table after Join)  Joining a table has a direction  Direction is important because it defines what the resulting data table might be used  There is a SOURCE table and a DESTINATION table  The source database represents the database that will be associated with another database (the data that will be joined)  The destination or target database is the data location where a source database will be associated (the data that will have something added)  The join item or join field is the common attribute between databases that will guide record or spatial entity matching  Joining in this way yields a table capable of being mapped; reversing the source and destination labels yields only a stand alone table.  Why? Define relationship between two tables Tables remain independent Additional cardinality choices ◦ One-to-many ◦ Discovers any related rows 2) Open related table 1) Make selection Example: Relate WV county attributes to table of coal production statistics for 1986 - 1998 One linked to Many table violates the rule of joining  Join and relate brings spatial and non-spatial tables together in a temporary manner that doesn’t alter the original structures of the tables involved.  When two databases are joined, the visual affect is as if the databases are physically joined (they appear as one database)  When two databases are related, no physical link appears to exist yet records selected in one of the databases (either through attribute or spatial queries) will also selected in the linked database


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