Intro to advanced GIS and a review of basic GIS

Topic 1

Outlines

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

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.

1. I will assign many ESRI-ebook for you to read

2. Many papers for you to read.

3. I will give quiz occasionally to see if you read them or not.

4. Other policies refer to the syllabus

What is GIS ?What is GIS ?

• A computer system for

- collecting,

- storing,

- manipulating,

- analyzing,

- displaying, and

- querying geographically related information.

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

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

1. Geospatial data

Traditional method

To represent the geographic data is paper-based maps

Geology map Topographic map City street map (we still use it a lot) ...

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

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, ...

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

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

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

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

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, zoneArea

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

Topology

© Paul Bolstad, GIS Fundamentals

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

DIGITAL SPATIAL DATA

• RASTER

• VECTOR

• Real World

Source: Defense Mapping School National Imagery and Mapping Agency

Raster and Vector Data Models

Vector RepresentationX-AXIS

500

400

300

200

100

600500400300200100

Y-AXIS

River

House

600

Trees

Trees

BB

B BB

BBB G

GBK

BBB

G

G

G GG

Raster Representation

1 2 3 4 5 6 7 8 9 1012345

67

8910

Real World

G G

Source: Defense Mapping School National Imagery and Mapping Agency

Example: Discrete raster

Xie et al. 2005

Example: continuous raster

Raster Real world Vector Heywood et al. 2006

Effects of changing resolutionHeywood et al. 2006

Vector – Advantages and Disadvantages

Advantages 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

Raster – Advantages and Disadvantages

Advantages 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

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

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

Coverages

Original ArcInfo Format Directory With Several Files Database Files are stored in the Info

Directory Uses Arc Node Topology

Containment (coincident) Connectivity Adjacency

TIN 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

©Arthur J. LemboCornell University

Components of a TIN Nodes Edges Triangles Hull Topology

©Arthur J. LemboCornell University

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.

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

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

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

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,…

examples

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

Flat file Hierarchical

NetworkRelational

PIN: Parcel ID number

Zoning (zonecode): 1-residential, 2-commercial Chang, 2004

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

Four tables linked by keys

Chang, 2004

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

Join and relate tables

Join

Join

relate

relate

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

One-to-One Join

Employee-id Job

1 Digislave

2 Useless Supervisor

Employee-id name

1 Tom

2 John

After join

Employee-id Job Name

1 Digislave Tom

2 Useless Supervisor John

Join Employee-id to Employee-id

Many-to-One JoinSymbol Description

Qa Quaternary Alluvium

Qe Quaternary Eolian

Pa Permian Abo

Polygon Id Symbol

1 Qa

2 Qa

3 Pa

4 Qe

Polygon ID Symbol Description

1 Qa Quaternary Alluvium

2 Qa Quaternary Alluvium

3 Pa Permian Abo

4 Qe Quaternary Eolian

After Join on Symbol

One-to-Many Relates

Formation Symbol

Quaternary Alluvium

Qa

Permian Abo Pa

Symbol Mineral

Qa Quartz

Pa Quartz

Qa Gypsum

Pa Feldspar

If the tables are related on Symbol, selecting Polygon-id 1 will select the highlighted areas.

Many-to-Many Relates

Formation Symbol

1 Qa

2 Qa

Symbol Mineral

Qa Quartz

Pa Quartz

Qa Gypsum

Pa Feldspar

If the tables are related on Symbol, selecting Polygon-id 1 will select the highlighted areas.

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

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

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

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.

Why use and create Why use and create metadatametadata

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.

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

See an example of non-standard metadata (see)

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 andshare geographic data.

The objectives of the CSDGM are to provide a common set of terminology and definitions for the documentation of digital geospatial data.

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

Connect to http://www.fgdc.gov/metadata/csdgm/

Metadata toolsMetadata 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

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.

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.

http://clearinghouse1.fgdc.gov/

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)

Types of geodatabases

personal enterprise

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.

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.

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 loadcompared to 2-tier system, in which the clientsdirectly connect to the RDBMS

Personal and Multiuser Geodatabase Comparison

source: www.esri.com

5. Lab 1

Getting Started With the Geodatabase

About 2 hours

About 1 hour

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

Copy your exam questions and result to your homework