1. Intro to advanced GIS and a review of basic GIS
Topic 1

2. Outlines About the class setting Materials to be covered and scheduled
Quick review of GIS basics
First lab (Lab 1)

3. Materials to be covered and scheduled
A review of basic GIS (1)
Spatial data analysis
Vector data analysis (2,3,4)
Raster data analysis (5,6)
Spatial interpolation (7,8)
3-D analysis (12)
Geoprocessing (9,10,11)
Other topics (13)
We do not use one single book, because there is no single book covering all the materials I will cover in the class.
I will assign many ESRI-ebook for you to read
Many papers for you to read.
I will give quiz occasionally to see if you read them or not.
Other policies refer to the syllabus

4. What is GIS ? A computer system for - collecting, - storing,
- manipulating,
- analyzing,
- displaying, and
- querying geographically related information.
GIS is a popular technology, but what exactly is it? What does it do? Basically, a geographic information system (GIS) is a computer-based tool for solving problems. A GIS integrates information in a way that helps us understand and find solutions to problems. Data about real-world objects is stored in a database and dynamically linked to an onscreen map, which displays the real-world objects. When the data in the database changes, the map updates to reflect the changes.
In general, people use a GIS for four main purposes: data creation, data display, analysis, and output. You can display objects according to the data in your database (this is a powerful feature that you'll appreciate later). GIS analysis tools allow you to do things like find out how far your best customers travel to visit your store, which land parcels are within a flood zone, and which soil type is best for growing a particular crop. Output options include cartographic-quality maps as well as reports, lists, and graphs.
Many different definitions of GIS have evolved in different areas and disciplines
the information is always geographic or spatial
Four components of any GIS: input; storage/retrieval; analysis; display
Used in a steadily growing number of fields/disciplines/projects
Origins lie (way back) in thematic maps; manual overlay
“GIS” refers to the application or the software; “doing GIS” refers to increasing number of things
Need understanding of GIScience to do GIS work.

5. In general GIS cover 3 components
Computer system
Hardware
Computer, plotter, printer, digitizer
Software and appropriate procedures
Spatially referenced or geographic data
People to carry out various management and analysis tasks

6. Geographic Data
Geospatial data tells you where it is and attribute data tells you what it is. Metadata describes both geospatial and attribute data.
In GIS, we call geographic data as GIS data or spatial data

7. 1. Geospatial data

8. Traditional method
To represent the geographic data is paper-based maps
Geology map
Topographic map
City street map (we still use it a lot)
...

9. Characteristics of spatial data
“mappable” characteristics:
Location (coordinate system, will be lectured later)
Size is calculated by the amount (length, area, perimeter) of the data
Shape is defined as shape (point, line, area) of the feature
Discrete or continuous
Spatial relationships

10. Discrete and continuous
Discrete data are distinct features that have definite boundaries and identities
A district, houses, towns, agricultural fields, rivers, highways, …
Continuous data has no define borders or distinctive values, instead, a transition from one value to another
Temperature, precipitation, elevation, ...

11. GIS: a simplified view of the real world
Points
Lines
Areas
Networks
A series of interconnecting lines
Road network
River network
Sewage network
Surfaces
Elevation surface
Temperature surface
Discrete features
Continuous features

12. Problems caused by the simplified features may still exist, but let’s live on it
Dynamic nature (not static)
Forest grow
River channel change
City expand or decline
Identification of discrete and continuous features
Road to be a line or a area?
Scale
Some may not fit to any type of features: fuzzy boundaries
Transition area between woodland and grassland
Lets do not worry about these problems now!!! Just keep in mind

13. Points
A point is a 0 dimensional object and has only the property of location (x,y)
Points can be used to Model features such as a well, building, power, pole, sample location ect.
Other name for a point are vertex, node
Point

14. Lines
A line is a one-dimensional object that has the property of length
Lines can be used to represent road, streams, faults, dikes, maker beds, boundary, contacts etc.
Lines are also called an edge, link, chain, arc
In an ArcInfo coverage an arc starts with a node, has zero or more vertices, and ends with a node
Line

15. Areas (Polygons)
A polygon is a two-dimensional object with properties of area and perimeter
A polygon can represent a city, geologic formation, dike, lake, river, ect.
Other name for polygons face, zone
Area

16. Topology needed
A collection of numeric data which clearly describes adjacency, containment (coincidence), and connectivity between map features and which can be stored and manipulated by a computer.
A set of rules on how objects relate to each other
Major difference in file formats
Higher level objects have special topology rules

18. © Paul Bolstad, GIS Fundamentals
Topology
© Paul Bolstad, GIS Fundamentals

19. Two basic data models to represent these features
Raster spatial data model
Define space as an array of equally sized cells arranged in rows and columns. Each cell contains an attribute value and location coordinates
Individual cells as building blocks for creating images of point, line, area, network and surface
Continuous raster
Numeric values range smoothly from one location to another, for example, DEM, temperature, remote sensing images, etc.
Discrete raster
Relative few possible values to repeat themselves in adjacent cells, for example, land use, soil types, etc.
Vector spatial data model
Use x-, y- coordinates to represent point, line, area, network, surface
Point as a single coordinate pair, line and polygon as ordered lists of vertices, while attributes are associated with each features
Usually are discrete features

20. DIGITAL SPATIAL DATA RASTER VECTOR Real World
This is an illustration of transferring a real world geographic area into the raster and vector formats. In the raster format the geographic area is parceled into numerous grid squares and the value that makes up the majority of the square dictates that that entire square gets the value. In the vector format all entities are classified into points, lines, or polygons.
Source: Defense Mapping School
National Imagery and Mapping Agency

21. Raster and Vector Data Models
Real World
600 1 2 3 4 5 6 7 8 9 10 1 B G
Trees
500 2 B G G 3 B
400 4 B G G
Trees
Y-AXIS 5 B G G
300 6 B
G G BK
House 7 B
200 8 B B
River 9 B
100 10 B
100
200
300
400
500
600
X-AXIS
Raster Representation
Vector Representation
Source: Defense Mapping School
National Imagery and Mapping Agency

22. Example: Discrete raster

23. Example: continuous raster
Xie et al. 2005

24. Raster
Real world
Vector
Heywood et al. 2006

25. Effects of changing resolution
Heywood et al. 2006

26. Vector – Advantages and Disadvantages
Good representation of reality
Compact data structure
Topology can be described in a network
Accurate graphics
Disadvantages
Complex data structures
Simulation may be difficult
Some spatial analysis is difficult or impossible to perform

27. Raster – Advantages and Disadvantages
Simple data structure
Easy overlay
Various kinds of spatial analysis
Uniform size and shape
Cheaper technology
Disadvantages
Large amount of data
Less “pretty”
Projection transformation is difficult
Different scales between layers can be a nightmare
May lose information due to generalization

28. GIS data formats (file formats)
Shapefiles
Coverages
TIN (e.g. elevation can be stored as TIN)
Triangulated Irregular Network
Grid (e.g. elevation can be stored as Grid)
Image (e.g. elevation can be stored as image, all remote sensing images)
Vector data
Raster data

29. Shape Files Nontopological Advantages no overhead to process topology
Disadvantages polygons are double digitized, no topologic data checking
At least 3 files .shp .shx .dbf

30. Coverages Original ArcInfo Format Directory With Several Files
Database Files are stored in the Info Directory
Uses Arc Node Topology
Containment (coincident)
Connectivity
Adjacency

31. TIN ©Arthur J. Lembo Cornell University
A triangulated irregular network (TIN) is a data model that is used to represent three dimensional objects. In this case, x,y, and z values represent points. Using methods of computational geometry, the points are connected into what is called a triangulation, forming a network of triangles. The lines of the triangles are called edges, and the interior area is called a face, or facet.
While the TIN model is somewhat more complex than the simple point, line, and polygon vector model, or the raster model, it is actually quite useful for representing elevations. For example a raster grid would require grid cells to cover the entire surface of a geographic area. Also, if we wanted to show great detail we would have to have small grid cells. Now, if the land area is relatively flat, we would still need the small grid cells. However, with a TIN we would not have to include so many points on the flat areas, but could add more points on the steep areas where we want to show greater detail.
The illustration shows how we can create a TIN of the terrain around Ithaca, NY.
First, a series of elevation points are created
Second, a TIN face is created with the elevation data
Third, the faces are shaded in to give the impression of a 3D surface

32. Components of a TIN Nodes Edges Triangles Hull Topology
©Arthur J. Lembo
Cornell University

33. Grid Properties Each Grid Cell holds one value even if it is empty.
A cell can hold an index standing for an attribute.
Cell resolution is given as its size on the ground.
Point and Lines move to the center of the cell.
Minimum line width is one cell.
Rasters are easy to read and write, and easy to draw on the screen.

34. A new data model in ArcGIS
Geodatabase data model
Use a relational database that stores geographic data
A type of database in which the data is organized across several tables. Tables are associated with each other through common fields. Data items can be recombined from different files.
A container for storing spatial and attribute data and the relationships that exist among them
And their associated attributes can be structured to work together as an integrated system using rules, relationships, and topological associations

35. Geodatabase components- vector data and table
Primary (basic) components
- feature classes,
- feature datasets,
- nonspatial tables.
complex components building on the basic components:
- topology,
- relationship classes,
- geometric networks

36. Geodatabase components- Raster data
Raster data referenced only in personal geodatabase
Raster data physically stored in multiuser geodatabse
Raster datasets and raster catalogs
A raster dataset is created from one or more individual rasters. When creating a raster dataset from multiple rasters, the data is mosaicked, or aggregated, into a single, seamless dataset in which areas of overlap have been removed. The input rasters must be contiguous (adjacent) and have the same properties, including the same coordinate system, cell size, and data format. For each raster dataset (.img, grid, JPEG, MrSID, TIFF), ArcGIS creates an ERDAS IMAGINE file (.img).
A raster catalog is defined as a table in the geodatabase which you can view like any other table in ArcCatalog. Each raster in the catalog is represented by a row in the table. It contains a collection of rasters that can be noncontiguous, stored in different formats, and have other different properties. In order to view all the rasters in the catalog, they must have the same coordinate system and a common geographic extent

38. 2. Attribute data
Attribute data is about “what” of a spatial data and is a list or table of data arranged as rows and columns
Rows are records (map features)
Each row represents a map feature, which has a unique label ID or object ID
Columns are fields (characteristics)
Intersection of a column and a row shows the values of attributes, such as color, ownership, magnitude, classification,…

40. examples

41. A database needed
If many fields related to one record (feature-ID), for example, the a soil unit can have over 80 estimated physical and chemical properties, more tables are needed to store all the attributes.
A database management system (DBMS) is needed to manage multiple tables.
A database is a collection of interrelated tables in digital format. There are four types:
Flat file, hierarchical database, network database, relational database
In GIS, we usually use relational database

42. Flat file
Hierarchical
Relational
Network
PIN: Parcel ID number
Zoning (zonecode): 1-residential, 2-commercial
Chang, 2004

43. Relational database
A relational database is a collection of tables, also called relations, which can be connected to each other by keys.
A primary key represents one or more attributes whose values can uniquely identify a record in a table. Its counterpart in another table for the purpose of linkage is called a foreign key
Advantages
Each table in the database can be prepared, maintained, and edited separately from other tables
Efficient data management and processing, since linking tables query and/or analysis is often temporary

44. Four tables linked by keys
Chang, 2004

45. Relationship of those separate tables
One record in one table related to one record in another table
One record in one table related to many records in another table
Many records in one table related to one record in another table
Many records in one table related to many records in another table

46. Join and relate tables
Once tables are separated as relational tables, then two operations can be used to link those tables during query and analysis
Join, brings together two tables based on a common key.
Relate, connects two tables (based on keys) but keeps the tables separate.
Keys do not have to have the same name but must be of the same data type
Join
relate
Join
relate

47. One-to-One Join Employee-id Job Name 1 Digislave Tom 2
Useless Supervisor
Employee-id
name 1
Tom 2
John
Join Employee-id to Employee-id
Employee-id
Job
Name 1
Digislave
Tom 2
Useless Supervisor
John
After join

48. Many-to-One Join After Join on Symbol Polygon Id Symbol 1 Qa 2 3 Pa 4Qe
Symbol
Description Qa
Quaternary Alluvium Qe
Quaternary Eolian Pa
Permian Abo
Polygon ID
Symbol
Description 1 Qa
Quaternary Alluvium 2 3 Pa
Permian Abo 4 Qe
Quaternary Eolian
After Join on Symbol

49. One-to-Many Relates
Symbol
Mineral Qa
Quartz Pa
Gypsum
Feldspar
Formation
Symbol
Quaternary Alluvium Qa
Permian Abo Pa
If the tables are related on Symbol, selecting Polygon-id 1 will select the highlighted areas.

50. Many-to-Many Relates
Symbol
Mineral Qa
Quartz Pa
Gypsum
Feldspar
Formation
Symbol 1 Qa 2
If the tables are related on Symbol, selecting Polygon-id 1 will select the highlighted areas.

51. Tables In ArcGIS GIS
Those separate tables will have one and only one table called spatial table (or layer attribute table), which has spatial location and relationship with the spatial data. Other tables called nonspatial tables, which can be either join or relate to the spatial table.
Join tables when each record in the spatial table has no more than one matching record in the nonspatial table
One to one relation
Many to one relation
Relate tables when each record in the spatial table has more than one record in the nonspatial table
One to many relation
Many to many relation

53. The joined table
The joined table will only preserved within the map document-the tables remain separate on disk-and can be removed at any time

55. Related tables
The related table will only preserved within the map document-the tables remain separate on disk-and can be removed at any time

56. 3. metadata
Meta is defined as a change or transformation. Data is described as the factual information used as a basis for reasoning. Put these two definitions together and metadata would literally mean "factual information used as a basis for reasoning which describes a change or transformation."
In GIS, Metadata is data about the data. It consists of information that describes spatial data and is used to provide documentation for data products. Metadata is the who, what, when, where, why, and how about every facet of the spatial data.
According to the Federal Geographic Data Committee (FGDC), metadata is data about the content, quality, condition, and other characteristics of data.

57. Why use and create metadata
To help organize and maintain an organization's spatial data
- Employees may come and go but metadata can catalogue the changes and updates made to each spatial data set and how each employee implemented them
To provide information to other organizations and clearinghouses to facilitate data sharing and transfer
- It makes sense to share existing data sets rather than producing new ones if they are already available
To document the history of a spatial data set
- Metadata documents what changes have been made to each data set, such as changes in geographic projection, adding or deleting attributes, editing line intersections, or changing file formats. All of these could have an effect on data quality.

58. Metadata Should Include Data about
Date of data collected.
Date of coverage generated.
Bounding coordinates.
Processing steps.
Software used
RMSE, etc.
From where original data came.
Who did processing.
Projection
coordinate System
Datum
Units
Spatial scale
Attribute definitions
Who to contact for more information
Example of non-standard metadata: (source:
THIS COVERAGE HAS BEEN PROJECTED TO THE FOLLOWING PARAMETERS - September 2000:
Projection: UTM Zone: 12
Units: meters
Datum: NAD83 (previously NAD27)
Spheroid: GRS80 (previously Clarke 1866)
THIS DOCUMENT WAS CREATED AT ART, UNIVERSITY OF ARIZONA, September 14, 2001
NAME OF DATASET: QUADS DATA
TYPE: Vector-polygon
DESCRIPTION OF CONTENT: These are the boundary polygons of the four quadrangles for the Santa Rita Experimental Range in southeast Arizona.
FORMAT: Arc/Info
DATA SIZE: Approximate Megabytes: .017
HISTORY: This coverage was originally reselected out of the ART Arizona General Reference Library which contains data originally from ALRIS.
MAINTENANCE: NONE
COLUMN ITEM NAME WIDTH OUTPUT TYPE N.DEC
AREA F
PERIMETER F
QUADS# B
QUADS-ID B
QUAD I
NAME C –
USER ATTRIBUTES
QUAD -- the ALRIS 4 digit quad codes
NAME -- USGS quad sheet name
See an example of non-standard metadata (see)

59. Federal Geographic Data Committee’s (FGDC) Content Standard for Digital Geospatial Metadata (CSDGM)
The FGDC is developing the National Spatial Data Infrastructure (NSDI) in cooperation with organizations from State, local and tribal governments, the academic community, and the private sector. The NSDI encompasses policies, standards, and procedures for organizations to cooperatively produce and share geographic data.
The objectives of the CSDGM are to provide a common set of terminology and definitions for the documentation of digital geospatial data.

60. CSDGM (FGDC-STD-001-1998) Metadata = Identification_Information
Data_Quality_Information
Spatial_Data_Organization_Information
Spatial_Reference_Information
Entity_and_Attribute_Information
Distribution_Information
Metadata_Reference_Information
Identification Information – basic information about the data set. Examples include title, geographic area covered, currentness, and rules for acquiring or using the data.
Data Quality Information − an assessment of the quality of the data set. Examples include positional and attribute accuracy, completeness, consistency, sources of information, and methods used to produce the data.
Spatial Data Organization Information − the mechanism used to represent spatial information in the data set. Examples include the method used to represent spatial positions directly (such as raster or vector) and indirectly (such as street addresses or county codes) and the number of spatial objects in the data set.
Spatial Reference Information − description of the reference frame for, and means of encoding, coordinates in the data set. Examples include the name of and parameters for map projections or grid coordinate systems, horizontal and vertical datums, and the coordinate system resolution.
Entity and Attribute Information − information about the content of the data set, including the entity types and their attributes and the domains from which attribute values may be assigned. Examples include the names and definitions of features, attributes, and attribute values.
Distribution Information − information about obtaining the data set. Examples include contact information for the distributor, available formats, information about how to obtain data sets online or on physical media (such as cartridge tape or CD-ROM), and fees for the data.
Metadata Reference Information - information on the correctness of the metadata information, and the responsible party.
Connect to

61. Metadata tools Metadata editors: - tkme / USGS
- ArcCatalog / ESRI
- SMMS / Intergraph
- FGDCMETA / Illinois State Geological Survey
- xtme / USGS
Metadata utilities (check compliance and export to text, HTML,XML, or SGML):
- mp / USGS
- MP batch / Intergraph
- ArcCatalog powered by mp/ ESRI
Metadata Server
- Isite / FGDC
- GeoConnect Geodata Management Server / Intergraph
- ArcIMS Metadata Server / ESRI
mp: Metadata Parser

62. FGDC Clearinghouse
the FGDC developed a clearinghouse that allows geospatial data creators to share their data
however, the FGDC Clearinghouse is not a data repository. The data contained within the clearinghouse is actually stored on computer servers maintained by individual contributors. This allows contributors to manage their own data.

63. Two Components
The FGDC Clearinghouse consists of 6 gateways and 250 nodes
A gateway is a point of entry into the FGDC Clearinghouse
A clearinghouse node is a database that contains metadata records. Individual contributors maintain nodes
Besides the FGDC Clearinghouse, there are a variety of other communities that use FGDC-compliant metadata as the basis of their data sharing services. These so-called clearinghouse communities are often developed because the participating organizations have data of similar or complementary types.

64. 4. Geodatabase
Before geodatabase, in one GIS project, many GIS files (spatial data and nonspatial data) are stored separated. So for a large GIS project, the GIS files could be hundreds.
Within a geodatabase, all GIS files (spatial data and nonspatial data) in a project can be stored in one geodatabase, using the relational database management system (RDMS)

65. Types of geodatabases
personal
enterprise

66. Personal Geodatabase
The personal geodatabase is given a name of filename.mdb that is browsable and editable by the ArcGIS, and it can also be opened with Microsoft Access. It can be read by multiple people at the same time, but edited by only one person at a time. maximum size is 2 GB.

67. Multiuser Geodatabase
Multiuser (ArcSDE or enterprise) geodatabase are stored in IBM DB2, Informix, Oracle, or Microsoft SQL Server.
It can be edited through ArcSDE by many users at the same time, is suitable for large workgroups and enterprise GIS implementations. no limit of size. support raster data.

68. 3-tier ArcSDE client/server architecture with both
the ArcSDE and Oracle RDBMS running on the
same server, which minimizes network traffic
and client load while increasing the server load
compared to 2-tier system, in which the clients
directly connect to the RDBMS

69. Personal and Multiuser Geodatabase Comparison
source:

70. 5. Lab 1
Getting Started With the Geodatabase

71. About 2 hours

72. About 1 hour

73. COPY the result map of your last step to your home work

74. Copy your exam questions and result to your homework