The Geodatabase. A. Michelle Lawing Ecosystem Science and Management Texas A&M University College StaMon, TX

Transcription

1 The Geodatabase A. Michelle Lawing Ecosystem Science and Management Texas A&M University College StaMon, TX

2 EvoluMon of the acronym GIS

3 SpaMal Thinking IdenMfying, analyzing, and understanding the locamon, scale, payerns, and trends of the geographic and temporal relamonships among data, phenomena, and issues. - Joseph Kerski

4 SpaMal Thinking What is your definimon of spamal thinking?

5 What is a Database?

6 What is a Geodatabase? A spamal relamonal database management system that stores geographic and related data. Central repository for spamal data storage and management.

7 EvoluMon of database systems

8 Geometry Data Type All 2D mapping can generally be accomplished with three geometry types Points, polylines, and polygons

9 RelaMonships among features Topological Determines adjacency and connecmvity among features Shared and coincident geometry types SpaMal Network Simple edges and juncmons Complex edges and juncmons General

10 Topology

11 Geometric Network The storage of network informamon Several components Simple edges and juncmons Complex edges Complex juncmons

12 Geometric Networks To build a network Sources and sinks ConnecMvity rules Edge- juncmon rules Edge- edge rules Perform a network analysis Trace Flow direcmon

13 The parts of a geodatabase Geographic dataset Feature classes, a collecmon of features with the same type of geometry RelaMonship classes, a table that stores the relamonships between two feature classes Object classes A feature class table A non- spamal ayribute table

14 The parts of a geodatabase

15 Example Geodatabase

16 Making your own geodatabse Design your data model Evaluate your data Define database structure Add data Understand your spamal reference Choose a coordinate system SpaMal domain Precision Modify your spamal domain if necessary

17 Benefits of using a geodatabase Store a rich collecmon of spamal data in a centralized locamon Apply sophismcated rules and relamonships to the data Define advanced geospamal relamonal models (e.g., topologies, networks) Maintain integrity of spamal data with a consistent, accurate database

18 Benefits of using a geodatabase Work within a mulmuser access and edimng environment Integrate spamal data with other IT databases. Easily scale your storage Support custom features and behavior

19 Two types of Geodatabes in ArcGIS

20 Personal geodatabase May be read by mulmple people Only edited by 1 person at a Mme Max size 2 GB Currently stores only vector data Raster stored as catalogs

21 MulM- user geodatabase Suitable for large workgroups and enterprise GIS implementamons May be read and edited by mulmple users simultaneously Requires ArcSDE and a DBMS Supports both raster and vector formats

22 A geodatabase extends a database Provides the framework for defining and managing the GCS for a set of data Models topologically integrated sets of feature Defines general and arbitrary relamonships between objects and features

23 A geodatabase extends a database Enforces the integrity of ayributes through domains and validamon rules Binds the natural behavior of features to the tables that store features Stores mulmple versions so that many users can edit the same data

24 SpaMal Query What is a spamal query? Name three examples of a spamal query

25 SpaMal Query OperaMons Search ThemaMc search Search by region Search by classificamon LocaMon analysis Buffer Corridor Overlay

26 SpaMal Query OperaMons Terrain analysis Slope/aspect Catchment Drainage network Flow analysis ConnecMvity Shortest path

27 SpaMal Query OperaMons DistribuMon Change detecmon Proximity Nearest neighbor SpaMal analysis/stamsmcs PaYern Centrality AutocorrelaMon Indices of similarity Topology Hole descripmon

28 SpaMal Query OperaMons Measurements Distance Perimeter Shape Adjacency DirecMon

29 Architecture of a SpaMal Database

30 Core features of a DBMS Persistence Some data are transient Some are persistent TransacMons Map a database from one consistent state to another All or abort Many transacmons executed concurrently

31 Space Taxonomy OrientaMon, DirecMon, Topological relamonships (adjacent, next to, inside) MulMtude of descripmons available to organize space

32 Data Model Vector Points Polylines Polygons Fields Raster, uniform grid imposed on underlying space TIN, triangulated irregular networks Contour lines Point grids

33 Data Model Example

34 Data Model Example

35 Data Model Example

36 Structured Query Language (SQL) DeclaraMve language User specifies the result Example: Find all land parcels next to my house. SELECT M.address FROM land_parcel L, city_name M WHERE Adjacent (L,M) AND M.address = MYHOUSE

37 Types of queries Range (select all points within 10 km of the city limits) Join (combine two tables on a common ayribute)

38 SQL Examples Join SpaMal Join

39 File organizamon and indices Programmer s Point of View Database Manager s Point of View Finite Infinite Infinite

40 Ordering mulmdimensional data SpaMal data can be sorted and ordered, but then data loose spamal proximity. Row Order Z Order

41 B- tree Stands for Balanced index structure Most widely used indexing for DBMS

42 B- tree Depends on an order in the indexing field DrasMcally cut down on processing Mme

43 R- tree is an extension of B- tree

44 Data mining SystemaMc search of potenmally useful informamon embedded in digital data Hot topic of research inside and outside of academia BIG DATA

45 Big Data Landscape

46 Ecosystem Science and Management Texas A&M University (c) 2014, A. Michelle Lawing SpaMal data are Big Data ESSM/GEOG 462: Advanced GIS

47 SpaMal data mining Find payerns in data with respect to geography Not new in GIS, but methods are smll in their infancy Up to 80% of digital data is spamal in nature!

48 SpaMal data mining A spamal database specialist can leverage expermse to Design search algorithms to hand large amounts of data Extend SQL with mining methods Random sampling commonly used in data mining Because of spamal autocorrelamon, other techniques might need to be employed (spamal stamsmcs)

49 SpaMal databases Important for management of spamal and related data Important for the query of spamal data to extract both spamal and related data

50 Don t Forget the Seminar! Michael Goodchild Space, Place, and GIS 3-4pm, Koldus 110 TODAY! No meemng this Thursday