GIS Principles, Elements of Maps.

GIS Principles, Elements of Maps

GIS Principles Geographic information
Is information about places—spatial dimension 80% of all information include spatial component - how should one embed location in data Knowledge about both where something is and what it is - with query capability in both directions Geographic resolution very detailed information about the locations of all buildings in a city information about individual trees in a forest very coarse climate of a large region population density of an entire country

Characteristics Often relatively static-- e.g., GPS coordinates of fixed features Natural features and many features of human origin don't change rapidly Static information is easier to portray on a static paper map Very voluminous A terabyte (1012 bytes) of data is sent from a single satellite in one day Gigabytes (gigabyte = 109 bytes) of data are needed to describe the US street network.

Abstraction--Geometrical Representation
Model the boundaries of spatial objects (vector data models) Point--a single location is enough MBTA Stops Is Taj Mahal a point?--At different scales or for different purposes, Taj Mahal could be a point or polygon. Line--only one dimension needs to be represented Street centerline, MBTA Railroad track, ridgeline, bux route How does it matter if street is modeled as centerline or as void between blocks? Polygon--2D planar surfaces Agra border,<![endif]> central square boundary, census tract, parcel, ... What about river boundary, edge of ocean (at high tide?) Beyond planar surfaces - terrain models, 3D CAD models,

Model the space that contains things (raster data models)
30m x 30m grid cells for Landsat image - classified based on predominate land use within each cell 6 inch pixels for color orthophotos developed from aerial photography 3 km x 3km x 1 km (height) volumes for meterological modeling

Five examples to view and discuss which GIS are. What to learn
Five examples to view and discuss which GIS are? What to learn? How to add your own data/analyses? Private sector mapping services Mapquest or Google-Maps to find a location and generate a street map. , maps.google.com Google-Earth (and Keyhole, Digital Earth, etc.) to navigate and 'fly' over the earth: earth.google.com Spatial analysis using commercial GIS software ArcGIS to analyze the demographics and economic development potential of Appalachia - ArcGIS Web services using open-source (LAMP) tools commute sheds and labor sheds for a community location-based services: tracking WiFi usage on campus: iSpots, Wireless Technology at College

Geographic information systems
Definition GIS is a computer-based information system that enables capture, modeling, manipulation, retrieval, analysis and presentation of geographically referenced data. (Worboys, 1997) Other definitions of GIS. A container of maps in digital form. A computerized tool for solving geographic problems. A spatial decision support system. A tool for revealing what is otherwise invisible in geographic information A tool for automatically performing operations on geographic data.

Components of GIS Hardware, Software, Data, People, Procedure, Network (Internet) GIS hardware is like any other computer (nothing special about the hardware) keyboard, display monitor (screen), cables, Internet connection with some extra components perhaps large monitor, disk drive, RAM maps come on big bits of paper need specially big printers and plotters to make map output from GIS need specially big devices (digitizers, scanners,...) to scan and input data from maps to GIS

Software ESRI ( Intergraph Corporation ( Autodesk ( Caliper: GIS Software, Mapping Software ( What is important is the kind of information that's stored and analyzed Representing and managing information about what is where The contents of maps and images Special functions that work on geographic information, functions to: Display on the screen Edit, change, transform Measure distances, areas, proximity, adjacency Combine maps of the same area together

Useful functions can be much more sophisticated
Keep inventories of what is where Properties, facilities Judge the suitability of areas for different purposes Help users make decisions about places, to plan Make predictions about the future

Example GIS Applications
Resources inventory (what is available at where?) Network Analysis (How to get to a place in the shortest amount of time?) Location Analysis (Where is the best place to locate a shopping mall?) Terrain Analysis (What is the danger zone for a natural disaster? Visibility analysis) Spatio-Temporal Analysis (Land use: what has changed over the last twenty years, and why?)

Transportation applications
A state department of transportation needs to Store information on the state of pavement everywhere on the state highway network Maintain an inventory of all highway signs Analyze data on accidents, look for 'black spots' A traveling salesperson needs A system in the car for finding locations, routes A delivery company, e.g. Federal Express, UPS, needs to Keep track of shipments, know where they are Plan efficient delivery routes A school bus operator needs to Plan efficient collection routes A transit authority needs to Know where transit vehicles are at all times Studies have shown substantial savings when routes and schedules are managed using GIS

Public Policy applications
Education Health and Safety Public Service Land Use and Transportation interactions Term Project Example: Measuring Diversity of Land Use Pattern and its Relation to Transportation Mode Choice

Systems, science and studies
What does it mean to be "doing GIS"? Using the tools of Geographic Information Systems to solve a problem Such as those in the previous examples A GIS project might have the following stages: Define the problem Acquire the software (and the hardware?) Acquire the data Clean the database Perform the analysis Interpret and present the results Data models and database management Storing/retrieving/manipulating attributes of spatial objects Spatial analyses can be complex and computing-intensive with enormous amounts of data

Geographic Information Studies
helping to build the tools adding to existing geographic information technologies helping to invent or develop new ones studying the theory and concepts that lie behind GIS and the other geographic information technologies thus GIS = Geographic Information Science Forer and Unwin (1997) add a fourth variant Geographic Information Studies are studies of the societal context of geographic information the legal context issues of privacy, confidentiality economics of geographic information

Elements of the Map Scale
Scale (Distance on the map compared with distance on the earth) Symbolization Projection Scale Ratio Scale, 1:10,000, or 1:100,000 or 1/100,000 Verbal Scale: One inch represents 2,000 feet (1:24,000). One centimeter represents 20 kilometers (1:2,000,000) Graphic Scale: Scale bar: Less precise but easily interpreted (for constant scale map projections) Particular useful for publishing maps in newspapers, magazines or online.

Symbolization Reality vs. Representation
Visual Variables: Size, color, shape, orientation, texture Use contrasting symbols to portray geographic differences For qualitative differences--Use shape, texture and hue (e.g., land use types). For quantitative differences--Use size to show variation in amount or count (e.g., population, No. of crime), Use graytone or hue to show differences in ratio or intensity - (e.g., proportion of household in poverty, population density).

Geographic Reference System & Projection
Geographic Reference System: Latitude and Longitude In North America, it is called North American Datum of 1983 (NAD83) What do Latitude and Longitude mean? Two points on the same longitude, separated by one degree of latitude are 1/360 of the circumference of earth apart, or about 111 km apart. One minute latitude is 6 km—nautical mile One-second latitude is 30 m. For the same latitude, one degree of longitude corresponds to different distance depends on the latitude. Map Projections Map projections transform the curved, 3-D surface of the planet onto a flat, 2-D plane. Map projections distort map scale but can preserve area, or angles, etc. (for small areas).

Map 'Layouts' include 'metadata' needed to interpret the map:
Title, Legend, Scale Bar, North Arrow, Data sources, Name or organization Date

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GIS Principles & Methods

General Approach Understand the “What.” Think about the “Why.”
What phenomena are we interested in studying? –Learning and discovering. Think about the “Why.” Why are 'spatial analysis' and GIS tools relevant? –Critical thinking. Master the “How.” How do we solve the problem? – decompose a question into spatial analysis and visualization components that can be handled by the data and software.

How to distinguish different geographic information?
How do we represent geographic location? How do we represent objects in space? Are all maps equal? (Scale or level of geographic detail) Must geographic information be mappable? (Shortest path algorithm) Data, Information and Knowledge - where does GIS fit in? Data – Raw geographic facts, context free. Information – the interpretation of data. Knowledge – interpreted information based on a particular content, experience and purpose.

Why Spatial information is special?
80% of all information includes spatial component Data, Information and Knowledge - relevant at every level. Urban planning is inherently spatial. Spatial relationships are as relevant as spatial location. It takes spatial analysis to understand their relationship. Spatial data are usually voluminous.

Presentation as a map often takes a huge amount of data.
Visualization and data consistency require use of particular map projections and spatial reference system Distinguish among: images of a place (streetscape), aerial photo of a place (orthophoto), and a cartographic map of the same place (Mapquest) Distinguish among: Mapquest, NOAA hurricane map, NOAA data buoy center , EPA's Enviromapper, College OrthoTools, traffic reports, ..., and ArcGIS Where is knowledge of geographic location, spatial analysis/ manipulation/ visualization capability

Other definitions of GIS
What is GIS? GIS is a computer-based information system that enables capture, modeling, manipulation, retrieval, analysis and presentation of geographically referenced data. (Worboys, 1997) Other definitions of GIS A container of maps in digital form. A computerized tool for solving geographic problems. A spatial decision support system. A tool for revealing what is otherwise invisible in geographic information A tool for automatically performing operations on geographic data.

Components of GIS Hardware, Software, Data, People, (humanware)
Procedure, Network (Internet).

Evolution of GIS: A Timeline from 1970s to now

GISytems, GIScience, GIStudies, and GIServices
GISystems – A computerized tool that helps solve geographic problems. GIScience – A scientific approach to the fundamental issues arising from geographic information. GIStudies – the systematic study of society’s use of geographic information, including institutional, organizational and procedural issues. GIServices – The business of providing GIS data and analysis tools to GIS users. These concepts are derived from Longley, e al, (2001)

Some Examples of GIS Applications
Resources inventory (what is available at where?) Network Analysis (How to get to a place in the shortest amount of time?) Location Analysis (Where is the best place to locate a shopping mall?) Terrain Analysis (What is the danger zone for a natural disaster? Visibility analysis) Spatio-Temporal Analysis (What has changed at what locations over the last twenty years, and why?)

Overview of ArcGIS software
What are the various parts of ArcGIS and what do they do How is ArcMap organized Understanding the 'vector' and 'raster' data models underlying ArcGIS 'Vector' data models for geospatial location Geometry model: boundary representation 'vector' model points (sales), lines (streets), and polygons (block groups) assign spatial feature ID to each spatial object Attribute data model relational tables linked to spatial features via ID graphical interface to utilize geometry/attribute links

Complications islands, lakes, overpasses share edges?, move links when you move points? ambiguity: summer/winter wetland boundaries scale, generalization, conflation, slivers Coordinate systems and projections Thematic mapping - tip of iceberg regarding GIS applications Symbology many options review 'symbology' page of layer properties review ArcGIS help files for symbology Different classification schemes (show help page): Equal Interval Natural Breaks Quantile Standard Deviation Normalization: people or population density - Why do we care? (show examples)

Raster vs. vector data models
regular grid on top of spatial features (instead of encoding boundary) pixel brightness in orthophoto of Taj Mahal Vector: points, lines, polygons Coverages: old Arc/Info a directory per layer, plus INFO files Shapefiles: .shp, .shx, .dbf files (and possibly others) Spatial Database Engine (SDE): retrieved dynamically from a database server Raster: orthophotos scanned maps, grids orthophoto has been 'unwarped' and registered to a coordinate system ortho can be treated as raster coverage layer where darkness of pixel is proportional to attribute of interest ArcGIS has 'spatial analyst' extensions to create and manipulate raster data layers and combine them via 'map algebra'

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More GIS Principles and Methods: Projections and
Coordinate Systems

Elements of the Map Scale
Ratio Scale, 1:10,000, or 1:100,000 or 1/100,000 Verbal Scale: One inch represents 2,000 feet (1:24,000). One centimeter represents 20 kilometers (1:2,000,000) Printout vs. onscreen: 10 foot pixel + 72 pixels per inch onscreen ==> One inch represents 720 feet (1:8,600) But some screens have higher/lower pixel densities; not all screens have square pixels; also, screendump to printer will change scale since printer will have different dot-density than the screen Beware! Good GIS software will try to match screen and printer properties to software settings so screen and printouts will show appropriate scale and show correct scalebars. For the scale to be meaningful, display units and hardware choices must be properly identified.

Large Scale or Small Scale
In general, Large scale: >= 1:24,000 ( ood for *small* area representation - city block) Small scale: <= 1:500,000 (good for *large* area representation - metro area) But scale is relative, depends on the applications. Large-scale maps are more detailed than small-scale maps.

Typical Scales Used In Metric System: 1:10,000 or 1:25,000 1:50,000
1:100,000 In American System: 1:9,600 (one inch represents 800 feet) 1:24,000 (one inch represents 2000 feet) 1:62,500 (one inch represents (slightly less than) one mile)

Six Principal Visual Variables

Use contrasting symbols to portray geographic differences
For qualitative differences Use shape, texture and hue (e.g., land use types). For quantitative differences Use size to show variation in amount or count (e.g., population, No. of crime), Use graytone or hue to show differences in ratio or intensity (e.g., proportion of household in poverty, population density).

Thematic mapping - simplest display of spatially varying phenomena
Note use of ArcMap 'help files' regarding thematic map types & classification choices Different classification schemes: Equal Interval Natural Breaks Quantile Standard Deviation Number of classes, color scheme, etc. Normalization: Why do we care? Exclusion options: no data vs. zero value Layouts: Features of a good map (lots more to good cartography–see references) Title, Legend, Scale Bar, North Arrow, Data sources, Your name or organization Other feature labels and annotations

Geographic Reference System: Latitude and Longitude
Projections Geographic Reference System: Latitude and Longitude Axis: the center of earth rotation. Equator: The plane through the center of mass perpendicular to the axis. Longitude: lines slicing the earth parallel to the axis, and perpendicular to the plane of equator. The line goes through Greenwich has 0 longitude. Range from 0 to 360 degrees, or 180 degree west (-) to 180 degree east (+).

Latitude Latitude is defined based on ellipsoid representing the shape of the earth. WG84 (the World Geodetic System of 1984) is a standard ellipsoid. In North America, the most recent ellipsoid data it is called the North American Datum of 1983 (NAD83) (the earlier version is NAD27). Latitude definition: A line drawn through a point of interest perpendicular to the ellipsoid at that location, the angle made by this line with the plane of Equator is the latitude of that point. Ranges from 90 degree south (-) to 90 degree north (+).

What do Latitude and Longitude mean?
Two points on the same longitude, separated by one degree of latitude are 1/360 of the circumference of earth apart, or about 111 km apart. One minute latitude is 6 k . One second latitude is 30 . For the same latitude, one minute of longitude separation corresponds to different distances depending on the latitude (111 km at equator, nothing at the poles!). Nowadays, latitude/longitude often expressed in decimal degrees.

Distance calculation using latitude and longitude
Arc distance between two points on the earth surface (spherical): Rcos-1[sinØ1sinØ2+cosØ1cosØ2cos(λ1-λ2)] R is the radius of the spherical earth Cartesian Coordinate System Assign two coordinates to every point on a flat surface.

Map Projections Map projections transform the curved, 3-D surface of the planet into a flat, 2-D plane. Note, that Map projections distort map scale in various ways Transform a position on the Earth’s surface identified by latitude and longitude (Ø, λ) into a position in Cartesian coordinates (x, y). x = f (Ø, λ) Y = g (Ø, λ) Map projections necessarily distort the Earth and the map scale.

Map Projection Classifications based on preservation properties
The conformal property preserves the shapes of small features on the Earth’s surface (directions). This is useful for navigation. E.g., Mercator projection and Gnomonic projection. The equal area property preserves the areas. This is useful for analysis involving areas like the size of the property, e.g., Goode’s projection. Any projection can have either conformal property or equal area property, but not both.

Map Projection classifications based on physical surface models
Cylindrical projections -- wrapping a cylinder of paper around the Earth, projecting the Earth’s features onto it, and then unwrapping the cylinder; Azimuthal or planar projections -- touching the Earth with a sheet of flat paper; Conic projection -- wrapping a sheet of paper around the Earth in a cone. All three types can have either conformal property or equal area property, but not both.

Unprojected projection: Plate Carrée or Cylindrical equidistance Projection
Just maps longitude as x and latitude as y. Heavily distorts image of the Earth. It does not have either conformal or equal area property. But it maintains the correct distance between every point and the Equator. Serious problems (distorted area, direction and other properties) can occur when doing analysis using this projection.

The Universal Transverse Mercator (UTM) Projection
Projected by wrapping a cylinder around the Poles, rather than around the Equator. There are 60 zones. Each zone is 6 degree wide and wrapped along a particular line of longitude. The project is conformal, the scale is the same in all directions. UTM coordinates are in meters, making it easy to make accurate calculations of short distances between points. UTM projections have more problems at high latitudes.

State Plane Coordinates and other local systems
UTM is still not accurate enough for small area surveying. During 1930s, each US state adopt its own projection and coordinate system, generally known as State Plane Coordinates (SPC). Each state chose its own projection based on its shape to minimize distortion over the area of the state. Some states have more than one internal zone. The North American Datum 1983 (NAD83) is commonly used for SPC.

Converting Georeferences
Two datasets can differ in both the projection and the datum, so it is important to know both for every dataset (and the data can be expressed in feet or meters with different origins!) Use coordinate conversion to combine datasets that use different systems of dereferencing. Keep in mind, changing projections means the system must convert projected coordinates back to lat/lon (geographic) and then re-project into another projection/datum. Convert into projections that have desirable properties, e.g., no distortion of area, for analysis.

Representing the Geographic World
Data Models and Data Management Vector model - representing objects by defining the location of their boundaries Raster model - representing space as 2D or 3D grid cells containing values that measure the presence/absence/strength of some field or phenomena Attribute handling - associating/manipulating the properties of objects or cells

Vector data Geographic phenomena are represented as points, lines and polygons. Lines are captured as points connected by straight lines, hence called polylines. An area is captured as a series of points or vertices connected by straight lines. Note limitations: e.g., the boundaries of geographic phenomena are usually fuzzy - edge of river/lake/wetlands.

Raster data Raster representations divide the world into arrays of cells and assign attributes to the cells. The cells may be called pixels (as with orthophoto) Examples: satellite images. Each cell can only have one value. Rules of assigning a value to the cell: largest share, or central point.

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Relational Databases & GIS Data Models

GIS Data Models Computer Aided Design (CAD), graphical, and image GIS data models; Raster data model; Vector data model; Linear Reference data model; Network data model; TIN data model.

CAD data models In CAD, real-world entities are represented symbolically as points, lines and polygons. CAD data model is different from GIS data models: CAD models uses local drawing coordinates rather than real-world coordinates. Individual objects in CAD do not have unique identifiers and attributes. CAD data model does not store details of relationships (e.g., topology) between objects.

Computer Cartography The purpose of computer cartography is to automatically reproduce paper maps. All paper map entities are stored as points, lines and polygons, with annotations used for placement. Only limited attribute data are associated with entities (enough for symbology). Relationships among entities are not stored.

Image data model Use images (photos, aerial photos and satellite images) to represent real world entities. Working with annotated pictures or real world entities. Images need rectification and registration to be integrated with other georeference data. (e.g., GeoTiff vs. Tiff image format)

Raster data model The raster data model uses an array of cells, or pixels, to represent real - world space and then encodes the grid cells based on objects in the cell. The cells can hold any attribute values based on different encoding schemes. Raster data are usually stored as an array of grid values, with metadata held in a file header. Typical metadata includes geographic coordinate of the upper-left corner of the grid, the cell size, and the number of row and column elements.

An example of a raster dataset with integer and floating point grid cell values (e.g., layer1 = soil type at center of grid cell, layer 2 = cell average groundwater depth in meters) Row Column Layer 1_value Layer 2_value 1 090 2 165 3 211 566 ...

Vector Data Model Vector data model describes the boundaries of real-world objects using 2D geometric types: point, line, or polygon and a real-world coordinate system Simple features model the basic object geometry Topologic features model relationships among objects

Simple Features Geographic entities encoded using the vector data model are called features. Features are vector objects of type point, line or polygon. Lines and polygons can overlap. There is no stored relationship between any objects. Simple feature data structure is sometimes called spaghetti.

Advantages and drawbacks of simple features
Easy to create and store. Easy to retrieve and render on screen. Inefficient to store, boundaries of two adjacent polygons - shared boundaries need to be stored twice. Inflexible in dissolving common boundaries when joining two zones or editing geometry to move common boundary points. May result in gaps (slivers) or overlaps of polygons. Many operations cannot be performed due to the lack of connectivity relationships in the data structure: e.g., finding the shortest path through a road network.

Topologic features Topologic features are simple features structured using topologic rules. Topology is the science and mathematics of encoding shape and spatial relationships. Topology can be used to validate the geometry of vector entities (e.g., polygons that are not 'closed'). Topology can be used for certain operations such as network tracing and tests for polygon adjacency.

Topologic structure – Line
A line is defined as a directed sequence of points from a starting node to an ending node. Points (vertices or line end nodes) that fall within a minimum tolerance of each other are snapped together. New nodes are created wherever two lines intersect. Hence, the name “spaghetti with meatballs".

Topologic structure – polygon
Polygons are defined as a sequence of lines that enclose an area. Points are stored once in a point list; lines are stored as a directed sequence of point IDs; polygons are stored as a directed sequence of line IDs. Moving a point, will automatically move all the lines and polygons that utilize the point. <![endif]> Planar enforcement: all the space on a map must be filled and any point must fall in one polygon only. That is, polygons must not overlap.

PointID X-value Y-value 1 200102 62011 2 150000 51000 3 300100 77700 4 300000 400000 5 260000 200000 LineID FromNode ToNode 10 20 30 40 50 60 PolygonID LineID sequence A 20, 10, 40, 30 B 50, 60, 40

Contiguity (adjacency) relationship
Each line must have a direction to define contiguity (adjacency) relationship. Defined by a list of polygons on the left- and right-hand side of each line.

Geo-Relation model The Geo-relation model refers to software that implements the vector topologic feature data model. Store the geometry and associated topologic information in one set of files (with object IDs). Store associated attribute information in relational database management system (with object IDs as foreign keys into geometry and topology data). The GIS software maintains the linkage between geometry, topology and attribute information.

Network data model Networks are modeled as points (nodes) and lines.
Network topology defines how lines connect with each other at nodes. There are also rules to define how flows can move through a network, like one-way street, sewerage flow, etc. The rate of flow is modeled as impedance on the nodes and lines, such as turn signals and speed limits.

Linear Referencing Store the location of geographic entities (called events) as a distance along a network (a route system) from a point of origin. Offsets are used to store information about the distance from the centerline. Dynamic segmentation is a special type of linear referencing. It assign event data to the network segments dynamically.

Triangulated Irregular Network (TIN) data model
TINs are used to create and represent surfaces in GIS. The TIN structure represents a surface as contiguous non-overlapping triangular elements. TIN is created from a set of sample points with x, y, and z coordinate values.

Relational Databases

Major topics Database concepts and issues in GIS Relational Database
Structured Query Language Entity-Relationship Model Join and Relate in ArcGIS

Limitations of one 'flat-file' for attributes
One 'flat file' data table for each map layer is too simple a data model Strategy: Relational Data Model (i.e., linked tables) Retain tabular model for textual data but allow many tables that can be related to one another via common columns (attributes) Allows augmenting attribute tables by adding additional data Handles one-to-many issues (where rows have different meaning in joined tables) Create 'summary' table with one row per town and a column with sum of area Then join back via town ID to shapefile with one row per polygon

Create 'summary' table with one row per house and columns for sale count, maximum price, average price, etc. then join back via house ID to sales tables with one row per sale Relational Database Management (RDBMS) is underneath most computing Database-driven web pages: e-business catalogues, online newspapers Most transaction processing: airline reservation, ATM transaction, cellphone call logging Structured query language (SQL) for joining tables and specifying queries is the lingua franca of distributed database operations Big business: Oracle, IBM (DB2), Microsoft (MS-Access, SQL- Server), ...

A Table (relation) Attribute name
Census_ID Land_acre Population Household 10020 1 50 15 10021 10 300 80 10022 8 250 70 Domains: data types like integer, strings, floats, dates, etc.

Relational Databases A relational database is a collection of tabular relations, or tables. A relation scheme defines the structure of the relationship, and is composed of a set of attribute names and a mapping from each attribute name to a domain (that is, the possible values of that attribute) A relation is a finite set of tuples associated with a relation scheme in a relational database (that is, a 'table' where each row is a tuple and the columns are the things that are related) A database scheme is a set of relation schemes. A relational database is a set of relations.

A Relational database example
Relation scheme: State (State_code, state_name, state_capital) Database scheme: city (city_code, City_name, State_code) State_census (state, population, housing_units …) Key: a minimal set of attributes whose value uniquely identifies each tuple.

Operations on Relations
Project operation [pick columns] applies to a single relation & returns a subset of attributes of the original. SELECT census_id, population FROM census_table Restrict operation [pick rows] works on the tuples of the table rather than the column & returns a subset of tuples of the original. WHERE population > 0

Join takes two relations as input and returns a single relation.
Join (rel1, rel2, att1, att2) Joins can get complicated (drop rows if no match?, join 3+ tables, ...) Order of operation can affect results and performance. Language varies slightly across vendors: SELECT census_id, population, state_name FROM census_table c, state_table s WHERE population > 0 AND c.state_id = s.state_id

Structured Query Language (SQL)
To define the database scheme (data definition), To insert, modify, and retrieve data from the database (data manipulation). Can get complex (subqueries in 'from' and 'where' clause, 3+ tables, ...) Can be especially powerful when rows in each table have different meaning e.g., join parcel table to owner table, or house sales table to house table

Distributed databases and Federated databases
Distributed databases refer to one database (or data replicates) that are distributed across multiple sites. Federated databases refer to many similar databases that are distributed across multiple sites but are more loosely coupled and additional rules may be needed to cross- reference tables meaningfully Federated databases are also called distributed relational database with fragmentations.

Conceptual data model To provide a data structure framework to communicate with non- specialists. To contain sufficient modeling constructs to capture the complexity of the system. To be implementation-independent. Two kinds of data models: Entity-Relationship Model (include extended E-R model) Object-Oriented Model

Entity-Relationship Model
E-R model sees the world as inter-related entities; Entities (or entity types) are related with each other by a relationship. E-R model uses E-R diagrams to describe relations between entity types. E-R model describes the static state of the entity types. Later, we'll use MS-Access to build E-R diagram for some relational tables.

Object-Oriented Model - alternative to E-R for RDBMS
Object-oriented model sees the world as inter-related objects. Object is dynamic and has its own lifespan. Hence OO model is used to deal with the dynamic nature of real- world object. Object = static state + functionality Object with similar behaviors are organized into types, a semantic concept. Object Class = data structure + methods, an implementation construct.

Entity and Attribute Entity type: an abstraction that represents a class of similar objects (e.g., a city, a road) Entity instance: an occurrence or instance of an entity type (e.g., “Agra” “Taj Mahal”). Attribute type serves to describe the entity type. Attribute instance: an occurrence of an attribute type. Example: City has name, population and centroid as its attribute types. “Agra” has its name, its population and its centroid as its attribute instance.

Joining and Relating Tables in ArcGIS
Join in ArcGIS appends the attributes of the non-spatial table to the spatial (layer) attribute table. Relate in ArcGIS does not append attributes; only establishes a logical relationship so that when you select one record in one table you can see the matching records in the other table. Don't get confused between ArcGIS 'relate' (which describes the relationship between two tables, and RDBMS terminology where 'relation' = a table

When to Use Join and Relate
Relate is preferred if the non-spatial table is maintained and updated constantly while the spatial data is not. Use relate when the relationship is many-to- many. Use relate when you have a very large non- spatial table and you do not need all the attributes in the table. In other situations, you could use either.

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Spatial Analysis (Vector Models)

Major Topic: Spatial Analysis (using Vector- based Data Models)
Taking advantage of GIS to handle spatial operations Spatial 'Join' issues: Combine data from different sources based on location & proximity Present results so that they can by visualized and/or saved for further use Examples of spatial 'joins' Which Place house sales fall within which census blockgroups Point-in-polygon operation Because we want to know about the neighborhood surrounding lower-price homes...

Which blockgroups are in which Mass Town?
Polygon-in-polygon operation Tricky because polygon boundaries may not line up (sliver & gap issues) Which roads are in the flood plain? Line-in-polygon operation Should you cut up the road segments or list line segments with part (>50%) inside? Which shopping centers are close to major highways How do we represent shopping centers and highways? There are many interesting Proximity questions

General spatial operations
Equals – are the geometries the same? Disjoint – do the geometries share a common point? Intersect – do the geometries overlap? Touch – do the geometries intersect at their boundaries?

Buffering Vector Data Buffering creates new polygon features by computing which areas are within a certain specified distance of the selected object. Buffering may define a new spatial object whose boundary enclosed all the area within the buffer the geometric computations can be complex beware of islands, slivers, etc. involves choices when buffers of selected features overlap (dissolve...) Buffer Input: Points, lines or polygons. Buffer Output: Polygon(s).

Buffering Raster Data Classify grid cells according to whether they lie inside or outside the buffer. In addition to distance, you can also use any function of grid cell values (e.g. travel speed) as a buffer criteria. The result is a new table of cell values for each grid cell - e.g., a raster map distinguishing all grid cells with, say, less than 30 minutes travel time from a particular point (e.g., a city center). More on raster modeling and analysis after next Monday's vector analysis lab.

Point in Polygon Whether a point lies inside or outside a polygon.
In the case of many points and many polygons, the task is to assign points to polygons Common operation: Many mailing lists and GPS readings are 'geocoded' into point files You need point-in-polygon operation to tag the attributes of the point map layer with characteristics of the places they are 'in'

Sometimes, this is a way of handling difficulty polygon-on-polygon operations such as the blockgroup-in-town issue in HW#2 Compute centroids of blockgroups Do point-in-polygon operations to see which blockgroup centroids fall inside which towns ArcGIS operation 'intersect' the two coverages in order to add polygon attribute information to point attribute table 'Desktop' ArcGIS tools have less sophisticated capabilities than ‘workstation' and 'arcedit' tools (that cost additional money for the extra tools in ArcToolbox)

Line in Polygon Used to determine whether a line lies inside or outside a polygon. In the case of many lines and many polygons, the task is to assign line segments to polygons. ArcGIS operation: Intersect lines and polygons in order to tag attributes of line segments with polygon information Since polygons aren't likely to cross the lines at the ends of the line segments, this operation can be complex if you wish to split lines at the polygon boundaries and assign the appropriate attributes to each new segment.

Polygon Overlay Many possible ways of intersecting polygons with one another Intersection: Polygon 1 + polygon 2 = polygon 3 (with common areas) Union: Polygon 1 + polygon 2 = polygon 3 (with both areas) Many issues about how to interpret the results Handling slivers due to geometric errors or differences in degree of generalization of boundaries Handling attributes Some attributes apply to each fragment without change (e.g., in flood plain, in city...) Some attributes need to be 'allocated' to each fragment (e.g., population in each part of blockgroup) o In next Monday's lab exercise we will have examples (e.g., estimate number of people living within a specified distance of College's biology building)

More spatial data processing
Dissolve features based on an attribute. Merge layers together. Clip one layer based on another.

Spatial Analysis Example - Locating a Shopping Center
Criteria: Within two mile of a major highway, but no less than one quarter mile away from a major highway. At least one mile away from a water body (e.g., rivers, lakes). Not in the flood zone. Close to a major residential area (at least 2500 households within 5 miles). Have a large piece of vacant land (at least 10 ac <![endif]> Classic 'site suitability' analysis <![endif]> Decompose task into many ArcGIS analysis steps

Data Required Highway layer (linear feature),
Vacant land layer (polygon feature), Rivers layer (linear or polygon feature), Lakes layer (polygon feature), Land use layer (polygon feature), Flood zone layer (polygon feature), Census layer (blockgroup level, polygon feature)

Spatial Analysis Process
Select vacant land parcels larger than 10 acres, result:vacantlg10. Buffer highway layer with 2 mile and .25 mile, result: hw2 and hwquarter. Buffer Rivers and Lakes layers with 1 mile, result: river1 and lake1. Intersect vacantlg10 with hw2 = vacanthw1, useful land. Union hwquarter with river1, lake 1 and flood (need to do two layers at a time), result: notusable, (land not meeting the criteria) remove notusable from vacanthw1, result: usable. intersect usable with census blockgroup layer (touch the boundary of), result: usableblock. calculate and reselect usableblock with number of total household larger than 2500, result: bigusableblock.

Additional criterion Consider an additional criterion: “ The median household income of the proximate residential area should be more than$30,000 ” ? Refine 'major residential area' criterion Require enough people within a buffer area around site Require proximity to dense residential area

Spatial Data Models: Spatial Analysis II (Raster Models) Raster vs. Vector Data Models for GIS

Vector (model boundaries of spatial features) - our focus so far
Vector Feature Types: Points The fundamental building block Lines Built from at least two points at the ends of the line: the nodes Extra points between the nodes--vertices--may add shape to the line Polygons A closed object with an interior and exterior Build from one or more lines May have islands

Vector Data Formats (for ArcGIS):
ArcInfo Coverages One directory per layer containing its geometry files (.adf files) Geometry includes topological relationships among features A workspace typically contains several coverage directories Database tables for all coverages in the workspace are stored in "Info" tables in a shared info directory This shared info directory impedes data management Coverages must be moved using ArcGIS, not operating system file management commands! ArcGIS Shapefiles .shp, .shx, .dbf files (and possibly others) Topological relationships are not stored in the layer, but computed on the fly when needed Shapefiles are easily moved or copied within the OS; just copy or move layer.*

Spatial Database Engine (SDE)
Retrieved dynamically from a database server Relies on a heavy-duty RDBMS such as Oracle Other GIS packages (MapInfo, Intergraph, TransCAD, Maptitude) use their own proprietary data formats, making for a Babel of GIS data Standards: SDTS (spatial data transfer standard for archival file format); Open Geospatial Consortium protocols for web services and Application Programming Interface(Web Mapping Service and Web Feature Service); Geographic Markup Language (GML) for xml-based data interchange; etc.

Raster (model properties of uniformly spaced grid cells)
Typically represented as a two-dimensional X-Y array Goodchild's illustration of raster geometry: More dimensions (Z for height, T for time) also possible, but harder to visualize Most rasters assign a single scalar value to each grid cell Value of the cell may represent an average value over the entire cell area the value at the center of the cell (ArcView does it this way) the value at the grid node (a corner) Goodchild's Illustration:

Possible to have multiple values- a vector of values--assigned to each cell
Goodchild's discussion of rasters Georeferenced images (e.g., orthophotos) are another type of raster data Orthophotos Cell value is pixel brightness in orthophoto Scanned maps ArcGIS (and earlier ArcView and ArcInfo) use a common data format called a grid ArcGIS's toolkit for raster analysis is the optional (and expensive) Spatial Analyst extension

Comparing Field and Object Models
Object (Vector) Model Each feature is a discrete object with vectors representing object boundaries "treats the information space as populated by discrete, identifiable entities, each with a georeference”(Worboys, p.149) Michael F. Goodchild's definition (from the NCGIA Core Curriculum in GIScience)

Field (Raster) Model Labels discrete chunks of space and records the properties of each chunk Good where values vary continuously over space; the raster approximates these variations with discrete "samples" "[geographic] information as collections of spatial distributions" (Worboys, p. 149) Examples: Temperature Rainfall Elevation Depth

Concentration of a chemical in the air, water, or soil
Fields are actually functions that map spatial locations to values Representing continuously varying 'fields' Representing fields (Goodchild's discussion) Different field representations (Goodchild's illustration): a. rectangular cells b. digitized contours c. rectangular grid of points d. polygons e. irregularly spaced points f. triangulated irregular network (TINs) Examples where the field model works well (from Goodchild) Weather modeling example at the National Center for Atmospheric Research (NCAR): MM5 (mesoscale model, fifth-generation) Issues with storing discrete objects in rasters (from Goodchild)

Examples of the contents of a single layer
Output from one band of a remote sensing satellite (or a panchromatic aerial photo) gives the level of radiation received by the satellite in that band, recorded as a number between 0 and 255 (8-bit) A classified scene in which satellite output has been assigned to one of a number of classes denoting various land uses e.g. 1=urban, 2=cultivated land, 3=water. many image processing and pattern recognition algorithms are used to classify/categorize imagery

A digital elevation model
values denote elevation of each cell's center point (above mean sea level in meters) A representation of the presence of roads e.g. 1=road present, 0=no road A soil or flood plain map value = predominant type of soil in grid cell value = 50 if greatest flood risk in cell is 1-in-50 year flood; 100 if 1-in- 100 year flood; etc.

Raster Analyses: Neighbors and 'Map Algebra‘
Edge-neighbors are four neighboring cells that Share an edge with the cell. Adding diagonals yields nine-nearest neighbors Map Algebra (phrase coined by Dana Tomlin) Often useful to compute algebraic function of neighbors Smooth distributions (recompute cell value to be average of neighbors) Model water flow (accumulate water from neighbors that are higher up) Plume dispersion model Useful to construct new raster layer where each cell's value is an algebraic function of neighbors The regular structure of the grid cells can simplify spatial modeling and analysis

Raster Difficulties: Edge Effects
Some cells on the border that have only two-three edge-neighbors. Map algebra models will behave differently at boundary where there are fewer neighbors - edge effects Common fixes for edge effects Run the model with an expanded coverage area for the raster, but then throw away the borders. Weight cells to compensate for missing neighbors (but difficult to determine the weight) Declare that a cell on the bottom border of the raster actually neighbors a cell on the top border.

Rasters in Practice There are many practical applications of rasters within and outside GIS. a computer display is a raster digital cameras use rasters images on the Web are rasters Certain kinds of data always come in raster form digital elevation models remote sensing images Raster data standard geoTIFF is an adaptation of the general-purpose TIFF image standard that includes the necessary hooks for registering the raster to the Earth, plus other geographic features. Orthophotos are georeferenced raster images Scanned maps may look like raster images but could easily be distorted

When NOT to Use Raster Representations
Rasters are less useful for representing networks where topology/connectivity is important and can't be captured at grid cell scale Example 1: modeling sewer lines as a raster layer code 1 in cells where a sewer is present, 0 elsewhere if two adjacent cells both have 1, that's no guarantee the sewers they contain are connected Example 2: Representing land ownership parcels as a raster layer by definition, the boundary between two survey points is a mathematically straight line the jagged appearance of a raster representation would be unacceptable Rasters cell size is a direct indicator of level of geographic detail Sometimes a plus - better indication of relevant data resolution To double spatial resolution, there may be four times as many cells

Network Analysis Encoding proximity using a network (or graph) model, facilitates certain types of connectivity analyses Find shortest path along streets from Point A to Point B Find shortest path through N cities (Traveling Salesman problem) How far can you get in 30 minutes Many transportation analyses use network data models Many hydological analyses use network data models (runoff, flow,..)

Raster Analysis Computing a housing value 'surface' for Place
Using the Census block group data: Rasterize Place into 100 meter grid cells Vector-to-raster conversion of (median) housing value for Place block groups Smooth the 'surface' using neighborhood averages Using the sales89 data: Compute cell values from sales within the cell Adjust the 'surface' based on neighboring sales Combine the two estimates: Average the two cell estimates (does this make sense? Use weights?) Understand use and limitations of map algebra models and the reasoning behind an interpolation method.

What is Geocoding Geocoding is a process of creating map features from addresses, place names, or similar textual information based on attributes associated with a referenced geographic database, typically a street network that has address ranges associated with each street segment or 'link' running from one intersection to the next. (Derived from Longley, Goodchild, Maguire and Rhind, Geographic Information Systems and Science, 2001.) Geocoding typically uses Interpolation as a method to find the location information about an address. (If the address along one side of a block range from 1 to 199, then Street Number = 66 is about one-third of the way along that side of the block.)

Data needed for geocoding
A list of addresses stored as a database table or a text file; Georeferenced features linked to the address database (such as a street centerline shapefile with street names and address ranges stored as attributes of the shapefile) A geocoding service, which is a configuration file that specifies the georeferenced feature layer and its relevant attributes, and various rules and tolerance for use in the matching. The output of the geocoding is a point file stored as either a shapefile or a geodatabase in ArcGIS.

What is a Network? A network is a system of linear features connected at nodes, e.g, nodes could be where three or more street segments intersect. The linear feature connecting any given pair of nodes is called an arc, or network link. Each arc on a network is represented as an ordered pair of nodes, in the form from node i to node j, denoted by (i, j), and thus has direction. A network representation that is good for transportation modeling may differ from a geographically accurate representation of the physical road (e.g., street centerline, handling exit ramps, 3D overpasses, etc.) Other basic elements of a network: A shortest path is the shortest (or least 'cost' path) from a source node (origin) to a destination node. In practice, pathfinding seeks the shortest or most efficient way to visit a sequence of locations.

A tour is an enclosed path, that is, the first node and the final node on the path are the same node on the network. A stop is a location visited in a path or a tour. Events or locations may be viewed as collection points (e.g., 'origins' or 'destinations' ) where certain resources are supplied or consumed. A turn on a network is the transition from one arc to another arc at a node (there are 16 ways in which two intersecting roads can allow vehicle flow among the 4 links that 'connect' to the one node). 'Location-allocation' models often use network representation of connected places in order to determine the optimal locations for a given number of facilities (e.g., stores, restaurants, banks, factories, warehouses, libraries, hospitals, post offices, and schools) based on some criteria, assign people to the the 'nearest' facility.

Thanks…

Introduction to Internet
GIS and ArcIMS

Main Topic: Introduction to Internet GIS and ArcIMS
State of the Art of Internet GIS Introduction to ArcIMS The Road Map of GIS Stand-alone GIS Programs Mainframe-based monolithic GIS programs Desktop GIS programs Limited or no communication with other computers (other than transparently via, for example, use of a network file server) Programs need to run on the mainframe or PC where the program resides Users need access to that machine via a login or dumb terminal session. Examples: early Arc/Info installed on a stand-alone mainframe or PC.

LAN-based GIS Programs
GIS installed on one or more machines on a Local Area Network (LAN) GIS programs run on local machines but can share data and printing facilities from the data server, or GIS programs run on a server, user can access it from any machine inside the LAN. Typical Client/Server architecture. Examples: Most current GIS programs.

Limitations of Stand-Alone and LAN-based GIS Progras
Difficult for user outside the LAN to access. Difficult to directly access data that are available outside the LAN. Limited GIS users. Difficult to mange, update and extend.

What is Internet GIS? Internet GIS is a network-centric GIS tool that uses the Internet as a primary means of providing access to the functionality (e.g., analysis tools, mapping capability) of GIS and to the spatial data and other data needed for various GIS applications. Internet GIS is an integrated client/server, and Web/Server application. Internet GIS typically uses a Web browser as client. Internet GIS can be viewed as a distributed, object- oriented system. Internet GIS is portable and cross-platform.

Internet GIS vs Web GIS What’s the difference between the Internet and the World Wide Web? Internet refers to the inter-connected computer network, - infrastructure. Web is one of many applications that are based on the Internet. The term Internet GIS focuses the use of a suite of Internet technologies, not only the Web. Internet GIS thus has more longevity and is a preferred term.

Features of Internet GIS
Wide accessibility, users from the world can access GIS data and analysis tools over the Internet. No GIS software is required to install locally. Takes advantage of the friendly graphic user interface that is provided by the World Wide Web. Users can directly manipulate maps and GIS data over the Web. Internet-aware GIS software can access remote data anywhere on the Internet. Internet GIS can easily incorporate up-to-date, real- time information

Basic Components of the Internet GIS

Internet GIS: State of the Art
Static Map publishing Static Web Mapping Interactive Web Mapping Client-side Plug-ins and Helper Program GIS ActiveX Controls Java-based Internet GIS Distributed Geographic Information Services

Server-Side and Client-Side Internet GIS
Server-Side Internet GIS HTML to GIS server via CGI (Common Gateway Interface) script Client-Side Internet GIS Client-side Plug-ins and Helper Program GIS ActiveX Controls Java-based Internet GIS Hybrid of server- and client-side Internet GIS Static Map publishing Insert Map images in a text file on the Web. Not a GIS. Static Web Mapping How does it work?

Common Gateway Interface
When a browser collects information it is sent to a HyperText Transfer Protocol (HTTP) server specified in the HTML form, and that server starts a program, also specified in the HTML form, that can process the collected information. Such programs are known as "Common Gateway Interface" programs, or CGI scripts (E.O. Johnson). CGI is a simple interface that links Web browser, server and other external programs. CGI or Dynamic Link Library (DLL) has three functions: It receives user inputs and parses them into parameters of variables to be used in GIS programs. It lets Web servers run other GIS programs. It interprets output and sends back to browsers.

Advantages of Static Web Mapping
A “thin” client (e.g., all data processing is done on the server, while the client is used only for display and user input). Takes full advantage of all GIS software functionality at the server. Ubiquitously accessible over the Internet. Can handle large database to serve spatial queries Drawbacks of Static Web Mapping Every user request has to go through the Internet to activate a CGI script every time. Creates heavy traffic over the Internet. Operation is slow, because every command (even very simple ones like zoom and pan) has to be operated on the GIS server. Maps are static images. User cannot draw a box or a circle or select polygons on the map images.

Examples of Static Web Mapping
VISA International ATM locator ( ESRI’s MapObjects Internet Map Server ( waukesha/) Map Quest ( Interactive Web Mapping (Client-Side Internet GIS) Interactive Web Mapping programs allow the user to manipulate GIS data and conduct GIS analysis at the client/user side, including: GIS Plug-Ins and Helper Programs GIS Java Applets GIS ActiveX Controls

GIS Plug-Ins or Helper Programs
GIS plug-ins are software executables that run on the browser and interpret the GIS data received from the server. GIS plug-ins are used in extending the browser to process GIS data. While GIS plug-ins are small applications, GIS helper programs can be large GIS applications or existing GIS software that is located in the user’s local machine. Examples of GIS Plug-ins Autodesk: MapGuide ( GeoMedia Web Map (for Netscape browser)

Advantages of GIS Plug-Ins
GIS plug-ins enable Web browser to interact with GIS data. Some GIS functions (i.e., zoom, pan, query) can be conducted by the plug-ins, so it can reduce traffic on the Internet. GIS plug-ins can fetch data from the server on demand. Plug-ins are easy to control and are not distributed with browsers. Drawbacks of GIS Plug-Ins Plug-ins are not platform-independent. The GIS vendor has to create different plug-ins for different operating systems (Unix, PC). Users have to download different plug-ins from different GIS servers. GIS plug-ins and helper programs have to be installed in the user’s machine. Security concerns make users hesitant to download plug-ins.

Java-Based Internet GIS Examples of Java-Based Internet GIS
GIS Applets GIS applets are executable code that are downloaded from the server and executed on the browser client at runtime. Java applets use an object-oriented language designed to work on a virtual machine and including functionality that is useful for the interface design of GIS mapping and analysis functions. Java applets are interpreted locally via tools that are embedded in the most common browsers. Java-Based Internet GIS How does it work? Examples of Java-Based Internet GIS MapXtreme from MapInfo ( Google maps ( (using AJAX:asynchronous javascript technology and XML: AJAX) ArcIMS from ESRI.

Partition Point for GIS Applets
The applet model moves the partitioning point further to the right. Applet gives the application designer/developer the flexibility to determine where to split the application. For example, a Web server may supply different applets depending on the speed of the connection between it and its clients.

Advantages of Java-based Internet GIS
Java’s byte code is platform-neutral, so it can run in any machine without modification. For vendors and developers, it means larger potential market and the elimination of “software porting.” For users, it means lower cost and greater interoperability among components. Java applet is run on local machine, minimizing through-net traffic, and making better use of local computing resources. Java applets are more flexible in creating and displaying graphics and maps. Java applets are downloaded from the server at runtime and will disappear when the user quits the application. Java is more secure, because applets run on the JVM on the user’s local device. Java applets have no access to local system.

Drawbacks of Java Applet
It takes some time to initially download applets. This is especially problematic for slow connections (e.g., via dialup modems). It needs Java-enabled Web browser for Java applets to function. It cannot access local files and data (due to security limitations of Java tools). Java based Web GIS cannot select objects by radius or select object from multiple themes (E.O. Johnson).

Java Plug-In Old Java applet relies on the web browser's default virtual machine. Java Plug-in software enables enterprise customers to direct applets or JavaBeans on their intranet web pages to run using Sun's Java 2 Runtime Environment, Standard Edition (JRE). The Java plug-in allows redistribution of both standalone Java technology- based applications and browser-based applets (

GIS ActiveX Controls An ActiveX control is a piece of executable code that can run on Windows platforms. ActiveX controls conform to the COM (Component Object Model) standard. They are loaded and executed inside a container (Internet Explorer).

How Do GIS ActiveX Controls Work?
Partition Point for ActiveX Controls Same as for Java Applet Example of GIS ActiveX Controls Intergraph’s GeoMedia Web Map Server ( MapGuide (

Advantages of GIS ActiveX Controls
Offers better performance, because they are compiled to the native executable format. Takes full advantage of local machine resources and platform functionality (e.g. files, memory, hardware and software system controls) unavailable to a Java applet. Can access to local data.

Advantages of GIS Controls
Some GIS functions (i.e., zoom, pan, query) can be conducted by the GIS controls. GIS controls can fetch data from the server on demand. GIS controls can communicate with other ActiveX controls and data locally as well as remotely as long as they conform to the COM standard.

Drawbacks of GIS ActiveX Controls
Portability: platform dependent, different ActiveX controls need to be created for different platforms. Users have to download different GIS controls from different GIS vendors, such as GIS controls from ESRI, Intergraph, etc. Not all browsers support ActiveX controls. For example, Netscape needs a plug- in to run ActiveX controls. GIS controls have to be installed in the user’s machine and lead to a “fat” client. Safety: Because ActiveX controls have full access to platform services, they can do great damage to a local system. Safety solution: Use verification approach to verify if a control is supplied by a trusted source. The assumption is that if it is supplied by a trusted source, it should be safe to use.

Safety Concerns of ActiveX Controls
Problems with the verification approach To be safe, users would have to reject all ActiveX controls not signed by an authority. Even if the user can verify the ActiveX control comes from a reliable source, there is still no way to tell if executing the control will cause damage. Data Streaming on the Internet Streaming subset of data to the client. Full data set stored in the data server. The client has the capability to replicate and cache data on the client side. The presentation (display and visualization) and logic components (map rendering) of the application reside on the client side in order to intelligently display the data. Example: Google Earth's client: (

Partition Point for Data Streaming
Advantages of Interactive Web Mapping Interactive Web mapping enables Web browser to interact with vector data rather than static map images. Some GIS functions (i.e., zoom, pan, query) can be conducted by the client-side programs, so it can reduce traffic on the Internet. Client-Side programs can fetch data from the server at runtime. Drawbacks of Interactive Web mapping It takes some time to initially download client-side Internet GIS programs. Some client-side Internet GIS programs are not platform-independent. Limited functionality Difficult to handle very large database, since the transport of large amounts of data over the Internet is slow.

ArcIMS Client Viewers HTML/DHTML Viewer
written using HTML, DHTML (dynamic HTML), and JavaScript. A thin client that only supports map images on the Web browser. Only one image can be displayed at a time. ColdFusion and ActiveX Viewers Similar to HTML/DHTML Viewer, but thinner Java Viewer support both Image and Feature streaming

ArcIMS Web Server Receives request from Web Client.
Communicates with the Web client (browser) through HTTP. Forwards client request to Application Server via Application Server Connector. Communicates with Application Server through either a Java Servlet, or ColdFusion or the Active Server Pages (ASP).

Application Server Connector
The connectors provide a communication channel between a Web Server or a third party application server and the Application Server. The connectors establish a socket connection with the Application Server for each request. Once the communication channel is established, requests are sent to and responses are received from the Application Server. ArcIMS Application Server Manages load and assigns tasks to spatial servers. Serves as a bookkeeper for keeping track of which MapServices are running on which ArcIMS Spatial Servers. Allocates an incoming request to the appropriate Spatial Server. The Application Server can communicate with Multiple Web Servers.

ArcIMS Spatial Server This is the backbone of ArcIMS.
It can produce maps, access data, and bundle maps into an appropriate format based on the user requests. It contains several supporting components: Weblink, the XML parser, and the Data Access Manager. Weblink is the communication gateway between the ArcIMS Application Server and the Spatial Server. The XML parser is used for parsing ArcXML requests. The Data Access Manager provides a link between the Spatial Server and any data sources.

Functions of ArcIMS Spatial Server
Image rendering – generates map images Feature streaming – streams feature data Geocoding – locates addresses on maps Query – returns associated data for spatial and tabular queries Data extraction – returns data in Shapefile format to the client ArcIMS Virtual Server It is a grouping of one or more Spatial Servers; it is not a physical entity. It is created to better manage distributed Spatial Servers. To improve service reliability and scalability Five Virtual Servers: ImageServer, FeatureServer, QueryServer, GeocodeServer, and ExtractServer.

Feature Streaming (Java clients only)
Streams vectors and attributes Locally cached Compressed binary / XML Java clients Local geoprocessing Buffer, MapTips, Query, Map Symbolization, ...

Thin Client vs. Thicker Client
Thin Client - Image Streaming Server-side processing GIF/JPEG/PNG images Faster Loading Thicker Client - Feature Streaming (java only) Vector / Raster / Attribute Data More Client-side Functions Robust Development Environment

Thanks…

GIS Principles, Elements of Maps.

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