Contents    Links  Application    Device    News    Satellite Images    Tutorial
GIS Tutorial Lecture note of the Geographic Information System
 GIS Tutorial    GPS Tutorial    Remote Sensing Tutorial    Software Tutorial

Releated Topics
 
GIS Tutorial
Why Don't My Layers Line Up?
What's Special about a GIS
What Can You Do with GIS?
Videos of GIS Tutorial
Vector Topology
Understanding GIS Data, Referencing Systems and Metadata
The Geographic Information System (GIS)
System Requirements
Spatial and Attribut Data
Sources of Geographic Information
Site Modeling in Context
Raster Analysis
Projection System
Opening Remarks of GIS
Maps: Projections and Datums
Map Production and GIS Output
Introduction to GIS
Introduction and Data Types
History of GIS
GIS Viewing Tools
GIS Tools
GIS Theoretical
GIS Summarize
GIS Software
GIS Overview
GIS Glossary III
GIS Glossary II
GIS Glossary I
GIS Defined
GIS Basics
GIS and WebMapping
Geographical Data Sets
Geographic Information Systems as an Integrating Technology: Context, Concepts, and Definitions
Geo-Referencing
Garmin Rino-08 GPS
Fundamental of GIS
Free Download GIS Tutorial in PDF
Digital Elevation Model (DEM)
Decision Making: Suitability Determination
Data Structures for Exchanging and Engaging Geographic Data
Data quality and errors in GIS
Data Input and Data Source
Data Elements and Models
Conducting a GIS Analysis
Attribut Data
Application of GIS
Answering Questions with GIS
Analysis of Geographic Data
Analysis (Vector)
A GIS Case Study in Africa
A Framework for GIS Analysis
 
GPS Tutorial
What is WAAS?
What is GPS?
The Quick GPS Tutorial
The GPS: An Amazing Tool
The GPS History
Short GPS Tutorial
Popular GPS Review
Load Maps On a Garmin GPS Unit
List of devices with Assisted GPS
Latest GPS Product Review 4
Latest GPS Product Review 3
Latest GPS Product Review 2
Latest GPS Product Review 1
Introduction to GPS
GPS Tutorial from Wiki Part II
GPS Tutorial from Wiki Part I
GPS Tracking Unit
GPS technical tutorial
GPS Receiver Manufacturers Part 2
GPS Receiver Manufacturers Part 1
GPS Product and Price
GPS Overview
GPS Glossary
Datum Transforms for GPS data between WGS84/NAD83 and NAD27
Colorization, Resizing, & Frequency Counts
Car GPS Review
Building Plain-Text Waypoint Files by Hand
Building Plain-Text Track Files
Basics of Global Positioning System
Assisted GPS
All about GPS
 
Remote Sensing Tutorial
White Mountain Thermal Features
What is Remote Sensing?
True Color View
Training Sites; Mixed Pixels
TIMS Thermal Scenes - Death Valley; Mauna Loa
Thermography - Night Vision Systems
Thermal Properties of Water
Thematic Mapper Bands
The Wien Displacement Law and Emissivity Effects
The Warm Earth - Thermal Remote Sensing
The Systems (Multisource) Approach to Remote Sensing
The Quantum Physics Underlying Remote Sensing
The Photographic Process
The Mystery Feature up Close
The Heat Capacity Mapping Mission (HCMM); Weather Satellites
The Concept of Remote Sensing; Sensors
The Commercialization of Space Remote Sensing
Supervised Classification
Spatial Filtering
Some Elements of Photogrammetry
Some Basic Image Processing Procedures
Solar Irradiation as a Heating Mechanism
SIR-A, -B, and -C on the Space Shuttle; Other Radar Systems
Short Remote Sensing Tutorial
Sensor Technology; Types of Resolution
Seasat Images
Satellites and sensors
Satellite Laser Ranging (SLR)
Remote Sensing Tutorial Examination
Remote Sensing Tutorial Answer
Remote Sensing System, Earth, and Electromagnetic Wave Length
Remote Sensing of the Ocean Floor
Remote Sensing Lecture Note in PDF and VIDEO
Remote Sensing in the 21th Century
Remote Sensing Glossary Part-2
Remote Sensing Glossary Part-1
Rationale for Surface Observations and Data Collection
Radar Polarization (Harrisburg, PA); Penetration of Foliage
Radar and Microwave Remote Sensing
Processing and Classification of Remotely Sensed Data
Principles of Spectroscopy
Principles of Remote Sensing: The Photon and Radiometric Quantities
Principal Components Analysis: A Background
Principal Components Analysis (PCA)
Platforms used by Remote Sensors
Passive Microwave; Lidar
Other Remote Sensing Systems - Radar and Thermal Systems
Other Remote Sensing Systems - MOMS and SPOT
Other Remote Sensing Systems - Hyperspectral Imaging
Other Remote Sensing Systems - ERS, Envisat etc.
Other Color Combinations
Optical Remote Sening
Non-Photographic Sensor Systems
Multitemporal Coverage
Multisensors
Multiplatforms and Multilevels
Mistery Feature of Remote Sensing
Minimum Distance Classification
Military Intelligence Satellites
Microwave Remote Sensing, Theory and Application
Microwave Remote Sensing
Meteorological, Oceanographic and Earth System Satellites
Medical Applications of Remote Sensing
Maximum Likelihood Classification
Interpreting Optical Remote Sensing Images
Infrared Remote Sensing
Image Processing and Analysis
Image interpretation & analysis
Image Classification
Hyperspectral Remote Sensing, Imaging Spectrometers
Humans in Space: Long Term Mobile and Fixed Stations
How Radar Work
History of Remote Sensing: Multispectral Images
History of Remote Sensing: MSS Histograms
History of Remote Sensing: Landsat's Thematic Mapper (TM)
History of Remote Sensing: Landsat's Multi-Spectral Scanner (MSS)
History of Remote Sensing: Landsat (ne: Earth Resources Technology Satellite)
History of Remote Sensing: In the Beginning
History of Remote Sensing: Examples of TM Imagery
History of Remote Sensing: Color & False Color Composites
History of Remote Sensing: Apollo 9 Multispectral Images
History of Remote Sensing: A Landsat Image
Harrisburg, PA and Nigeria/Cameroon Radar Images
Ground and Aerial Photographs of the Morro Bay Area
Geophysical Remote Sensing
Geologi Aplication: Stratigraphy and Srtucture
Fundamentals of Remote Sensing
Foreshortening and Layover
Field Instruments and Measurements; Data Collection Platforms; GPS
False Color Rendition
Factors that Modify or "Confound" Spectral Curves; Data Analysis
Elements of Aerial Photography
Electromagnetic Spectrum: Transmittance, Absorptance, and Reflectance
Electromagnetic Spectrum: Spectral Signatures
Electromagnetic Spectrum: Distribution of Radiant Energies
Earth's Gravity and What Departures (Anomalies) from a Uniform Gravitational Field
Diurnal Heating Effects
Digital Image Processing and Analysis
Digital Image of Remote Sensing
Contrast Stretching and Density Slicing
Best MSS Bands for Identifying Surface Features
Band Ratioing
Band Information Characteristic
AVIRIS and other Imaging Spectrometers
Analysis of the Morro Bay Scene
Airborne and Spaceborne Remote Sensing
Additional Examples of Imaging Spectrometer Products; Multisensor Analysis
Accuracy Assessment
Absorption Processes
A History of the Space Program - The 1990's -European, Asian, and Commercial Space Programs
A History of the Space Program - The 1990's - Russian Space Program
A History of the Space Program - The 1990's - American Military Space Program: Initial Military Operations
A History of the Space Program - The 1990's - American Civilian Space Program (NASA)
A History of the Space Program - The 1990's
A History of the Space Program - The 1980's -European, Asian, and Commercial Space Programs
A History of the Space Program - The 1980's - Russian Space Program
A History of the Space Program - The 1980's - American Space Policy
A History of the Space Program - The 1980's - American Military Space Program: Initial Military Operations
A History of the Space Program - The 1980's - American Civilian Space Program (NASA)
A History of the Space Program - The 1980's
A History of the Space Program - The 1970's - Russian Space Program
A History of the Space Program - The 1970's - American Space Policy
A History of the Space Program - The 1970's - American Military Space Program: Initial Military Operations
A History of the Space Program - The 1970's - American Civilian Space Program (NASA)
A History of the Space Program - The 1970's
A "Multi" Case Study
 
Software Tutorial
Working with CHGIS data in MapInfo
Working with CHGIS data in ArcGIS
Working with CHGIS data in ArcExplorer
Why ERDAS?
What's new in Maplex for ArcGIS 10
What's New in IDRISI Taiga
What's New in ERDAS Support
What's New in ERDAS 2011
What's New in ENVI 4.8
What's new in ArcScan for ArcGIS 10
What's new in ArcMap 10 basics
What's new in ArcGIS Tracking Analyst 10
What's new in ArcGIS Spatial Analyst 10
What's new in ArcGIS Schematics 10
What's new in ArcGIS Mobile 10
What's new in ArcGIS Geostatistical Analyst 10
What's new in ArcGIS 3D Analyst 10
What's new in ArcGIS 10 Network Analyst
What's new in ArcGIS 10
What's new for route finding in ArcGIS 10
What's new for geodatabases in ArcGIS 10
What's new for geocoding in ArcGIS 10
What's new for defense and intelligence in ArcGIS 10 Service Pack 1 and ArcGIS 10
What is mobile GIS?
What is Mappetizer?
What is ArcGIS?
What is ArcGIS.com?
What is ArcGIS Server?
What is ArcGIS online?
What is ArcGIS Desktop?
Vegetation Hyperspectral Analysis Case History Using ENVI
Vector Overlay and GIS Analysis With ENVI
Using Menu and Toolbar in Global Mapper
Updating a Portion of Terrain Dataset with New Measurements - Lidar Solution in ArcGIS
Troubleshooting the ArcMap OGC Interoperability Add-on
Troubleshooting the ArcGIS License Manager
Troubleshooting map service performance with log files
Troubleshooting data packaging validation error messages in ArcGIS
Troubleshooting data packaging limitations in ArcGIS
Troubleshooting ArcGIS Server installation and Post installation
Troubleshooting & Tips using ArcMap
Trouble Shooting Coordinate Systems in ArcMap
Transforms Using Matlab - Digital Images Processing Using Matlab
Top 5 List for Troubleshooting SDE Connections
Tips and Triks, Unix, Phyton, and Geoprocessing
Tips and Triks Error Handling in Phyton Script Tools
Three fundamental representations of geographic information layers
Support of Mappetizer
Spatial Transformations Using Matlab
Spatial relationships and behavior
Selected Mapping Methods Using Hyperspectral Data Uning ENVI
Scripting Language Reference in Global Mapper
Reprojecting X,Y Coordinate Values in an ASCII file - ERDAS Imagine Tutorial
Reading and Writing Image Data Using Matlab
Raster Image Processing, Tips and Triks - Mosaicking
Raster Image Processing, Tips and Triks - Image Classification
Raster Image Processing, Tips and Triks - Georeferencing
Raster Image Processing, Tips and Triks - Extracting Feature from an Image
Quick IDRISI Tutorial
Quick ERDAS Tutorial
Product Review: PCI’s Geomatica 10
Polarimetric SAR Processing and Analysis Using ENVI
Pixel to ASCII - ERDAS Imagine Tutorial
Overlay Control Center in Global Mapper
New temporal data in ArcGIS 10
New tables and attributes in ArcGIS 10
New symbols and styles in ArcGIS 10
New sharing maps and data in ArcGIS 10
New selection tools in ArcGIS 10
New representations in ArcGIS 10
New reporting in ArcGIS 10
New reporting in ArcGIS 10
New raster and image data in ArcGIS 10
New page layouts and data frames in ArcGIS 10
New ModelBuilder in ArcGIS 10
New metadata in ArcGIS 10
New map templates in ArcGIS 10
New map display and navigation in ArcGIS 10
New graphing in ArcGIS 10
New geoprocessing in ArcGIS 10
New Facilities and function editing in ArcGIS 10
New ESRI Data and Maps in ArcGIS 10
New CAD integration in ArcGIS 10
New automating map workflows in ArcGIS 10
New ArcGIS Server 10
New animations in ArcGIS 10
New and improved geoprocessing tools in ArcGIS 10
New accessing your data in ArcGIS 10
Near-Shore Marine Hyperspectral Case History Using ENVI
Multispectral Processing using ENVI's Hyperspectral Tools
Multispectral Classification Using ENVI
Mosaicking Using ENVI
Minimizing Noise from Lidar for Contouring and Slope Analysis - Lidar Solution in ArcGIS
MATLAB - MathWork Troubleshooting Part-3
MATLAB - MathWork Troubleshooting Part-2
MATLAB - MathWork Troubleshooting
Mappetizer Version History
Mappetizer Functionality / Examples
MapInfo Prefessional Tutorial Part-2
MapInfo Prefessional Tutorial Part-1
Map Composition Using ENVI
Map applications provide the primary user interface for GIS
Key aspects of GIS
Introduction to Hyperspectral Data and Analysis Using ENVI
Introduction to ENVI User Functions
Introduction to ENVI
Introducing ENVI 4.8
In ERDAS IMAGINE, how do I update the local license file?
Image Registration Using Matlab
Image Georeferencing and Registration Using ENVI
ILWIS - Short Tutorial and Free Download Sotware Open Source
IDRISI Taiga Performance and Capability for Images processing and GIS
IDRISI Taiga Key Features
IDRISI Taiga Installation Troubleshooting
IDRISI Land Change Modeler Software for ArcGIS
IDRISI Customer Support Frequently Asked Questions
IDRISI CartaLinx FAQs
IDRISI Andes and Kilimanjaro Installation Troubleshooting
IDRISI Additional Tools
IDL ENVI Visual Information Solution
Hyperpectral Signatures and Spectral Resolution Using ENVI
How to Working with CHGIS data in ArcView GIS 3.x
How to use IDRISI GIS for decision making
How to troubleshoot ArcGIS Java Extensions
How to Loading File in Global Mapper
How to Install Global Mapper Software
How to Change Display Characteristics in Global Mapper
How to Batch the CADRG Exporter - ERDAS Imagine Tutorial
How to add a new entry to the ERDAS IMAGINE EPSG database - ERDAS Imagine Tutorial
How maps convey geographic information
How maps are used in GIS
How a GIS represents and models geographic information
Georeferencing and coordinate systems
Geoprocessing—Computing with geographic data
Frequently Asked Questions on Global Mapper
Free Download PCI Geomatics Tutorial in PDF
Free Download PCI Geomatics
Free Download Mappetizer Software
Free Download Geomatica® Tutorials in PDF
Free Download ENVI Tutorial Including Data
Free Download ArcGIS tutorials in PDF
Extracting height data from elevation models - ERDAS Imagine Tutorial
Example: Representing surfaces
Estimating Forest Density and Height - Lidar Solution in ArcGIS
ERDAS Imagine Tips and Tricks
ERDAS Imagine Frequently Asked Question (FAQ)
ERDAS 9.3 Software and Image Analysis Stereo Analyst extensions to ArcGIS v 9.3 Network License Troubleshooting
ERDAS 2011 Software
ENVI Quick Start
ENVI Glossary 2 (O - Z)
ENVI Glossary 1 (A - N)
ENVI 4.7 Tutorial
ECW for ArcGIS Server
Displaying and Exploring Images in Matlab
Digging Deeper - Troubleshooting Geoprocessing Error When Using ArcSDE Data
Designing and Implementing 2-D Linear Filters for Image Data - Digital Images Processing Using Matlab
Data Area Delineation from Lidar Points - Lidar Solution in ArcGIS
Customizing the Geoprocessing Menu
Creating Raster DEMs and DSMs from Large Lidar Point Collections - Lidar Solution in ArcGIS
Creating Intensity Images from Lidar - Lidar Solution in ArcGIS
Create a Common LUT for multiple 16 bit images - ERDAS Imagine Tutorial
Comparison of GIS and Remote Sensing Software
Calculate Statistics for the Visible Portion of an image in the Viewer - ERDAS Imagine Tutorial
Bussines Partner Solution for Lidar in ArcGIS - Lidar Solution in ArcGIS
Basic SAR Processing and Analysis Using ENVI
Basic Hyperspectral Analysis Using ENVI
Assign Geocoding Information to a Data File - ERDAS Imagine Tutorial
Assessing Lidar Coverage and Sample Density - Lidar Solution in ArcGIS
ArcView Tutorial
ArcMap documents and Web maps
ArcGIS Tutorials
ArcGIS Troubleshooting
ArcGIS Installation Instructions
ArcGIS for developers
Arc GIS 9 Troubleshooting Tips
Analyzing and Enhancing Images Using Matlab
Analysis of DEMs and TOPSAR Using ENVI
An overview of geographic information elements
Alphabetic List of ENVI Library Routines
Advanced Hyperspectral Analysis Using ENVI
Add a Percentage Column to the Attribute Editor - ERDAS Imagine Tutorial
 

 Additional Topics
Groundwater And Mathcad Code
Envi Zoom Free Download
Erdas Tutorial Exercise
3d Analyst Arcgis 9.3
Erdas Imagine 9.3 Torrent
Envi 4.8 64
Quick Terrain Modeler Torrent
Idl 8.1 Windows
How To Create Buffer Using Erdas
Medicina Erdas 2011 64 Bits
Tutorial Orthoretification Ilwis
Remove Image Strips Envi Itt
Are Labels Only Done With Maplex
Envi 4.7 With Idl 7.1 Download
What's Special about a GIS - Lecture Material - Completely GIS dan Remote Sensing tutorial - facegis.com

 

What's Special about a GIS


The way maps and other data have been stored or filed as layers of information in a GIS makes it possible to perform complex analyses.

A color diagram map with cross hairs on a point.

Figure 16. A crosshair pointer (top) can be used to point at a location stored in a GIS. The bottom illustration depicts a computer screen containing the kind of information stored about the location—for example, the latitude, longitude, projection, coordinates, closeness to wells, sources of production, roads, and slopes of land.

A black and white screen snapshot showing coordinate information for the point.

Information retrieval

What do you know about the swampy area at the end of your street? With a GIS you can "point" at a location, object, or area on the screen and retrieve recorded information about it from offscreen files (fig. 16). Using scanned aerial photographs as a visual guide, you can ask a GIS about the geology or hydrology of the area or even about how close a swamp is to the end of a street. This type of analysis allows you to draw conclusions about the swamp's environmental sensitivity.


A colored section of a map with selected points.

Figure 17. Sources of pollution are represented as points. The colored circles show distance from pollution sources and the wetlands are in dark green.

 

Topological modeling

Have there ever been gas stations or factories that operated next to the swamp? Were any of these uphill from and within 2 miles of the swamp? A GIS can recognize and analyze the spatial relationships among mapped phenomena. Conditions of adjacency (what is next to what), containment (what is enclosed by what), and proximity (how close something is to something else) can be determined with a GIS (fig. 17).


Networks

When nutrients from farmland are running off into streams, it is important to know in which direction the streams flow and which streams empty into other streams. This is done by using a linear network. It allows the computer to determine how the nutrients are transported downstream. Additional information on water volume and speed throughout the spatial network can help the GIS determine how long it will take the nutrients to travel downstream (figs. 18a and b).

A map showing a network lines in blue.

Figure 18a. A GIS can simulate the movement of materials along a network of lines. These illustrations show the route of pollutants through a stream system. Flow directions are indicated by arrows.

A black and white map with a network of blue lines overlaying the map.

Figure 18b. Flow superimposed on a digital orthophoquad of the area.

Overlay

Using maps of wetlands, slopes, streams, land use, and soils (figs. 19a-f), the GIS might produce a new map layer or overlay that ranks the wetlands according to their relative sensitivity to damage from nutrient runoff.

A black and white shaded relief map with an overlay of colored lines.

Figure 19a. Shaded-relief map and contour lines generated from the digital elevation model in the study area.

A color map of slopes in relief with an overlay of colored lines.

Figure 19b. Map showing the steepness of slopes in the study area, created by GIS from the digital elevation model.

A colored map of streams and buffer zones.

Figure 19c. Distances to streams as measured by three 200-meter buffers derived from a digital map of hydrography.

A map with colored shapes representing land use.

Figure 19d. Map indicating various land uses in the study area.

A map with colors representing various soil types.

Figure 19e. A soils map stored in a GIS database. Numbers indicate the type of soil.

A map with colored lines and shapes to represent different zones.

Figure 19f. The wetlands in the study area ranked according to their vulnerability to pollution on the basis of combination of factors evaluated by GIS.

Data output

A critical component of a GIS is its ability to produce graphics on the screen or on paper to convey the results of analyses to the people who make decisions about resources. Wall maps, Internet-ready maps, interactive maps, and other graphics can be generated, allowing the decisionmakers to visualize and thereby understand the results of analyses or simulations of potential events (fig. 20).

A colored satellite photograph modified by GIS.

A color of a section of a road map.

Figure 20. Examples of finished maps that can be generated using a GIS, showing landforms and geology (left) and human-built and physical features (right).

Framework for cooperation

The use of a GIS can encourage cooperation and communication among the organizations involved in environmental protection, planning, and resource management. The collection of data for a GIS is costly. Data collection can require very specialized computer equipment and technical expertise.

Standard data formats ease the exchange of digital information among users of different systems. Standardization helps to stretch data collection funds further by allowing data sharing, and, in many cases, gives users access to data that they could not otherwise collect for economic or technical reasons. Organizations such as the University Consortium for Geographic Information Science (www.ucgis.org) and the Federal Geographic Data Committee (www.fgdc.gov) seek to encourage standardization efforts.

For more information

Good places to learn more about GIS technology and methods include the geography department of your local university, the GIS site at www.gis.com, your county planning department, your state department of natural resources, or a USGS Earth Science Information Center (ESIC). To locate your nearest ESIC, call 1-888-ASK-USGS, visit ASK-USGS web site, or visit www.usgs.gov.

Source: http://egsc.usgs.gov/isb/pubs/gis_poster/

Related Topics

Application of GIS
Lecture Material - Completely GIS dan Remote Sensing tutorial - Application of GIS

What's Special about a GIS
Lecture Material - Completely GIS dan Remote Sensing tutorial - What's Special about a GIS

GIS Theoretical
Lecture Material - Completely GIS dan Remote Sensing tutorial - GIS Theoretical

Attribut Data
Completely GIS dan Remote Sensing tutorial - Attribut Data

Vector Topology
Completely GIS dan Remote Sensing tutorial - Vector Topology

Spatial and Attribut Data
Lecture Material - Completely GIS dan Remote Sensing tutorial - Spatial and Attribut Data

 Links


Vector Topology

Topology is the spatial relationships between geographic features. It is not to be confused with topography, the form of the land.
 

1. The Components of Topology

Topology has three fundamental  components:

    a. Connectivity:
    Arcs are connected to others (at nodes). This identifies possible routes and networks, such as rivers and roads, via the lists of arcs and nodes in the database.

    b.  Containment:
    An enclosed polygon has a measurable area; lists of arcs define boundaries and closed areas.

    c.  Contiguity:
    The adjacency of polygons can be determined by shared arcs.

    Table 6-1

GIS and Remote Sensing tutorial of facegis.com
Polygon Topology: Area
Node Topology: connectivity
Arc Topology: contiguity
Polygon
Arcs
Node
Arcs
Arc
Left & Right Polygons
A
B
C
D
a1, a2, a3
a2, a5, a6
a3, a4, a5
a1, a4, a6
1
2
3
4
a1, a2, a6
a2, a3, a5
a1, a3, a4
a4, a5, a6
a1
a2
a3
a4
a5
a6
A  D
A  B
A  C
C  D
B  C
B  D

 These are fundamental to GIS analysis and queries, for example:

Diagram explanation:

  • Polygon A is bounded by arcs a1, a2, a3  etc..
  • Polygon D is known as the 'External or Universe Polygon' which describes all areas OUTSIDE the polygons on your map.  It is necessary for reasons of contiguity, all arcs are bounded by two polygons. It would help answer, for example, if you were working in a park: how many areas are adjacent to the park boundary?
  • Node 1 is connected by arcs a1, a2, a6  etc..
  • Each node is connected by at least (and usually) three arcs
  • Arc a1 is bounded either side by polygons A and D  etc..
  • Note: arcs are usually created with a direction, i.e. a 'from' node and a 'to' node. The actual direction may be significant, for example in stream flow, but arbitrary in others, e.g. most roads. Direction determines which polygons are 'left' and 'right'.

GIS vector data can be either constructed with topology (topological data) or without topology : 'spaghetti' data  (see below)


2.  Spaghetti versus Topological data

a. 'Simple' spaghetti data

Vector data that has been created without topology is referred to as 'spaghetti' data for reasons you can imagine (strings of unconnected lines). This is easier to create, but if to be used for GIS, one pays for lack of topology later: a case of "more haste, less speed". Individual features may appear the same, for example:
  • Points:  have  x and y coordinates.
  • Lines (arcs): Strings of x, y vertices.
  • Polygons: Closed set of coordinates.
  • But there is NO spatial relationship between these features:
  • Arcs may not necessarily join and Polygons may not close to form areas.
  • Intersections may not have nodes where two arcs cross.
  • Adjacent digitized polygons may overlap or underlap (leaving an empty wedge).
  • Arcs may consist of many broken segments.

b. 'Complex' topological data

Creating topologically correct data takes longer, but enables GIS queries and analysis.
  • Points: are polygons of zero area and length.
  • Lines (arcs): start and end at nodes.
  • Polygons: given by sets of connected arcs and an interior label point.
 Shared polygon arcs result in:
  • Lower total number of arcs in a database.
  • Adjacent polygons do not enclose overlap wedges or slivers.
  • Cleaner map output (more evident when you zoom in or magnify).
Figure 6-2 : Spaghetti Data versus Topological Data
GIS and Remote Sensing tutorial of facegis.com
GIS and Remote Sensing tutorial of facegis.com
This is the raw data. It must be 'cleaned and built' for GIS. There are unacceptable dangling arcs, nodes, and missing intersections.
The data after "clean & build": there are nodes at all intersections, and no dangling arcs.


3. Creation of Topology: 'Clean & Build'

a. Node types

Table 6-3
  EXAMPLE DEFINITION ACCEPTABLE 
NORMAL NODES
GIS and Remote Sensing tutorial of facegis.com
At an intersection of 3 or more arcs Always
DANGLING NODES
GIS and Remote Sensing tutorial of facegis.com
At the end of an arc  Arcs (Not polygons) 
e.g. roads, streams 
PSEUDO NODES
GIS and Remote Sensing tutorial of facegis.com
 Between 2 arcs    Island polygons, attribute change

b. Arcs

  • Nodes are required at all arc intersections.
  • Dangling arcs can be accepted if the "dangle tolerances" are set.
    • e.g. if tolerance = 5 metres, an arc < 5 is a dangle (error), an arc > 5m is a legitimate arc.

c. Cleaning (moves nodes/arcs)

  • Removes unacceptable dangling arcs and nodes.
  • Joins missing arcs segments (within a special distance).
  • Removes unnecessary pseudo nodes.
  • Adds nodes to all intersections.
  • Label points are added to polygons.

 d. Building topology

  • Does not move any features but 'cements' them into place.
  • Creates a Feature Attribute Table.
  • Builds (again) after new edits including,
    • addition or removal of arcs and points;
    • addition or removal of attribute items.

4. Review

  1. Name & describe the three components of topology.
  2. There is no spatial relationship between points, lines and polygons in spaghetti data. True or false?
  3. When are dangling nodes acceptable?
  4. Define normal node, dangling node & pseudo node.
  5. Name four things that 'clean' does.

Source: http://www.gis.unbc.ca/courses/geog300/lectures/lect20/index.php

 

 Links


Maps: Projections and Datums

Where did you say you were calling from?

  • The round earth on a flat map = "a projection"
  • imagine putting a strong light bulb in the globe and then holding flat piece of paper around it.
  • answer? Flat, wrapped cylinder, wrapped cone, cut up into wedges.
  • Some common ones (ask what the poles/greenland will look like)
In ArcGIS, open ....Demo\projections\project the world.
  •  cylindrical (Mercator)
  • Azimuthal (for poles)
  • Conic (one latitude is tangent, called the standard parallel)
  • Poly-conic (multiple latitudes tangent)

Here's a comparison of some, with some projection views.

(excellent source for more information here)

 

Projections create distortion

ArcGIS Help on projections says

All map projections distort shape, area, distance or direction to some extent. The impact of this distortion on your work depends on what you will be using your map for, and its scale:
......and extent of area

The map has different names, depending on what you hold constant:

  1. equal area--homolographic

  2. if you put a dime on a map, it'll always cover the same area, but shapes and angles are distorted
  3. shape - conformal

  4. at a point, relative local anles are preserved
    meridians intersect parallels at right angles
    areas enlarged or reduced
  5. Scale - equidistant

  6. equidistant between two points and rest of map only, or along meridians
  7. directional - azimuthal

  8. all rhumblines (lines of constant direction) are straight

Create a new blank arcmap document, then open VA_counties.shp from your GIS\demo\intro folder and change the coordinate system of the frame to

  • state plane=polyconic
  • utm, grid zone 17
  • equal area
  • decimal degrees (geographic)

 

Geoid and reference elipsoids

The earth is an oblate spheroid with the minor axis 1/300th shorter than major axis but the earth also has an irregular undulating surface that varies by +/- 100m from the oblate spheroid.  So the geoid is the approximation for shape of earth at "sea level" that takes into account gravitational and rotational inconsistencies.

this irregular shape is approximated by "elispoids" with a major and minor axis that fit particular parts of the globe better than others.  In the US, the North American Datum of 1927 (NAD 27) uses the Clarke66 (that's 1866) elipsoid, named for British geodisist Alexander Ross Clarke.  He measured the meridian arcs in Europe, Russia, India, S. Africa and Peru (with chains and surveying instruments).  His radii are 6,378,206.4 m and 6,356,583.8 m for the equatorial and polar axes, respectively. In ArcGIS, open the Data Frame Properties/coordinate system box, and choose the "predefined-geographic-spheroid based-clarke66" coordinate system and click "modify..." to see its parameters.

 

Datums fix the zeros

A reference elipsoid must have a zero point somewhere and the mean sea level must be established from the geoid.  These are fixed for a particular UTM zone, for example, or standard parallel.

Satellite data are currently being gathered and fitted to world-centered elipsoids (e.g., WRS80) that do a better job for the entire surface of the earth as a whole, but less well than the hundred year old regional elipsoids at any given location.

And so there's a problem.  Some USGS data come from NAD27 maps (Clarke66 elipsoid) while others, like the microsoft terraserver use NAD83 (WRS80 elipsoid).....
look at datum shift (for lat long) for NAD27 to NAD83 on BV quad
Want to see it?
open demo\projections\projections_and_datums.mxd

So where are you????

The datum shift includes
initial point change (to center of earth from reference elipsoid matched to earth's surface)
change in length of elipsoid axes
ground survey network changes (local deviations, distortions, errors, tectonics)
Plate tectonics?? (opening is 15 cm/year * 60 years....)

 

UTM (Universal Transverse Mercator)
computers eat it for breakfast.
it reads like cartesian coordinates

here's a picture of how it works (by Peter H. Dana, The Geographer's Craft Project, Department of Geography, The University of
Colorado at Boulder)

Grid zones are 6 degrees wide with a central meridian
They start at 180 degrees west of Greenwhich and go east.  In Lexington, we're in grid zone 17, which has 81 degrees W as the central meridian.
US Grid Zones and World Grid zones

ArcMap: For UTM / Geographic comparison,

  • Open projections_and_datums.mxd from the Demo\projections folder
  • Move the dataframe projection from one grid zone to another (eg. zone 17 to zone 18, then to zone 10 !)

 

Source: (http://geology.wlu.edu/harbor/geol260/lecture_notes/notes_maps1_new.html)

 Links


Martian Landscapes: Linear Features, Volcanoes, Impact Craters, Channels; Exotic Terrains Part-2 - Application

A special type of volcano on Mars has recently been proposed to be caused by escaping gas, fluid, and mud. These 'mud volcanoes' have their counterparts on Earth. On Mars they are observed in the thousands in Acidalia Planitia in the northern Plains. Their importance is that the fluid is likely water and hence such features are more likely to harbor at least single-cell life. Here are two examples:

Mud volcanoes on Mars.
A single mud volcano.

Among martian features believed volcanic in nature are linear ridges similar to the wrinkle ridges found in lunar maria. Here is a topographic map made from MGS MOLA measurements that includes (in the purple) these ridges and shows the diversity of other landforms.

Part of the Hellas Basin (left) and the Hellas Planitia outside the structure, in a topographic map made (by M. Zuber and colleagues) with MOLA data.

Another example of what is interpreted as wrinkle ridges is this:

Supposed wrinkle ridges in Hesperus Planum.

In contrast to the volcanoes described above, which are upward conical prominences, are the downward indentations or craters that can be either volcanic or impact. Both are typical of martian terrains. Extensive impact cratering was observed by Mariner 4, which sent back the first ever images taken of another planet's surface (one of these images is seen below (top) when this probe approached to within 9800 km (6086 miles). As imaged the next year by Mariner 6, the Sinus Sabeus region of the southern highlands (bottom scene) preserves typical impact craters in the ancient terrain that apparently has not been extensively resurfaced by lavas. Note that none of the larger craters in this view have central peaks.

Mariner 4 image of extensive impact cratering on the surface of Mars.
Mariner 6 image of the Sinus Sabeus region of the southern highlands on Mars.

Mariner 9 and the Vikings confirmed that a large fraction of the (older) martian surface, mainly in the southern hemisphere, remains heavily cratered. This is evident in this sketch drawing from Mutch et al., The Geology of Mars, 1976 in which all craters larger than 15 km are positioned.

 Sketch map of the two dominant terrains on Mars: volcanic plains and cratered uplands.

A recent study made by Dr. Herbert Frey of NASA Goddard - assisted by his teen age daughter Erin - has led to a map of the distribution of large surface-visible plus now buried impact structures that nevertheless show circular surface manifestations. The latter have been located using the MOLA laser altimetry data.

Map of visible and buried impact structures on Mars larger than 200 km in diameter.

One can argue that this landscape has many similarities to the still cratered Earth in its early stages before extensive water had collected into major oceans. Likewise, buried impact structures can be discerned on the lunar surface. These have since been covered by lunar ejecta. This may mean that the martian Highlands surface is also covered by ejecta deposits that spread over older craters.

Some of the martian impact structures retain well-preserved ejecta blankets that display prominent lobes, such as seen here around the crater Yuty. The ejecta was probably fluidized by vaporization of carbon dioxide-rich ice lying just beneath the surface.

Viking image of the Crater Yuty, with a 'fluidized' ejecta blanket.

One type of impact crater is different from those on the Moon, Mercury and Venus in that the edge of the ejecta blanket has a steep scarp, evident in the Viking image below, or even a peripheral rise called a rampart. This type is called a pedestal crater.

Pedestal craters on the martian surface; Viking Orbiter.

On Mars many of the younger craters still preserve their ejecta blankets, as exemplified here:

A martian impact crater in Medusa Fossae with a well-preserved ejecta blanket on both sides.

This next crater is small, young, and shows most of the same features as do terrestrial craters. Located in Terra Meridiani, this crater is 2.6 km wide (1.6 miles; rim to rim), has at least 1 nested slump zone in its interior and a distinct exterior ejecta blanket, and has exposed what appears to be internal layering of the martian surface units. The image was made by the Mars Global Surveyor.

Martian Impact Crater; MGS image courtesy Malin Space Sciences Systems.

This type of central (interior) layering, almost certainly sedimentary (see pages 19-13a and 19-13b) also appears in the 2.3 km (1.5 mile) wide Schiaparelli crater in the Chrysae Basin, seen below. The layering appears horizontal:

Schiaparelli crater.

These observations of sedimentary-like crater interior floors and walls (layering is also discussed on the next page) seem rather mysterious. On Earth, craters that still retain their original rims (almost?) never show the bedrock below the final crater excavation wall. Yet this is common in martian craters with initial walls intact. Martian planetologists have suggested removal by erosion (they mean almost certainly wind erosion). There may be an alternate cause: the lower martian gravity allow nearly complete escape during crater formation of the bulk of the ejecta; the floor remains exposed because in the smaller craters slumping has not destroyed the walls.

Still another large impact crater, Poona, has a remarkable uniform set of rays, equispaced over the full 360° around the rim:

The crater Poona, with pronounced radial grooves from ejecta scouring.

This small crater (below) shows a distinct pattern of dark rays. Because martian winds are continually altering the surface, both removing and covering up debris, the crater (and those above with lighter-toned rays) can be young - age estimates have ranged between a few thousand and a few million years.

A small rayed crater on the Martian surface; MOC image; courtesy MSSS.

This rayed crater looks fresh. Experience on Earth indicates that impacts occur rather often in terms of a human time frame. A new crater was produced on Mars during the operational period of the Mars Global Surveyor. This before-and-after image pair shows the appearance of dark rays around an area which contains a small hole not there on the earlier date:

A new crater developed on the martian surface sometime after the mid-1990s; MGS MOC image.

This next Viking scene, in the southern Highlands, seems to have both impact and volcanic craters. Some without ejecta beyond their rims, especially the elliptical one, are calderas. Several others have aspects more characteristic of degraded impact structures. This was an active region, with channels (either volcanic or stream) and other types of terrain.

 Craters, possibly with multiple origins, and channels in the southern Highlands of Mars; Viking Orbiter.

Now look at these three craters (Ulysses Patera):

 The Ulysses Patera crater triplet in the northwest Tharsis region; Viking Orbiter.

Because of several factors, some martian craters appear as faint rings rather than topographic features raised above the surface. These have been called "ghost" or "stealth" craters. They represent some combination of burial by crater ejecta, wind erosion, dust cover, and ice cover. Here is an example of this last type:

Ghost rings (buried craters) in an ice-covered region of Mars; the ice shows polygonal fracturing as exemplified on the preceding page.

There is evidence that the number of observed impact craters on Mars is less than would be expected if the recent activities (dust transport and deposition, ice relocation, etc.) had not buried the smaller ones. The wind, however, is capable of exhuming such craters, as displayed in this image which also shows the exposed craters to contain some signs of filling by sediment, now revealed as faint layers.

A group of small craters being exhumed to show darker material beneath; some craters have odd shapes because of incomplete exposures; the feature in the lower right is a small layered butte; light-colored dunes support the action of wind as the cause of exhumation.

Not all impact craters are circular or slightly elliptical. Strongly elongate craters are found on the Moon. A few such distorted craters are present on Mars, such as the one shown below. The usual explanation is that the impacting body comes onto the surface at a very low or grazing angle, scouring out the surface material as it proceeds forward:

Teardrop-shaped impact crater on Mars; the converging to a point is an extreme that is unusual.

Large, young impact craters are few but conspicuous. Galle Crater is 220 km (138 miles) wide and retains its original rim:

The Galle Crater on Mars.

As with the Moon, Mars has a few craters so large that they can be called impact basins. By far the biggest is the Borealis Basin (also known as Vastitus Borealis). Mars geologists (starting with George McGill and Stephen Squyres) have postulated that this feature (which has dimensions of 10,600 by 8500 km) was produced by a glancing collision with an asteroidal body that may have been as much as 1600 km in diameter. This impact, which peeled off at least 3 km of martian surface, may have occurred as early as 4 billion years ago. It accounts for the generally lower topography of the northern half of Mars (see page 19-10), evident in this topographic map (blue low; reds high):

Topographic map of Mars showing the lower (blue) aspect of much of the northern hemisphere.

Papers from a group at MIT in a June 2008 issue of the journal Science offer strong evidence for the existence of the Borealis Basin; as is often the case, there is a vocal group of doubters. But, the impact hypothesis is a plausible explanation for the dichotomy in martian topography: the distinctly lower top 40% is readily explained as caused by the stripping of crust from an oblique impact. In the next figure, the Borealis Basin (bluish area in upper right panel) is compared with the Hellas Basin on Mars and the Aitken Basin on the Moon:

The Borealis Basin on Mars (upper right) prior to the emplacement of the Tharsis volcanoes (upper left); these are compared with the Hellas (Mars) and Aitken (Moon) impact basins

The largest well-defined impact basin on Mars, and second in the Solar System only to the Aitken basin on the Moon, is the Hellas Basin in the southern Highlands. Its diameter is about 2100 km (1300 miles), its depth is almost 9 km (6 miles) and its rim exceeds 1.5 km (1 mile). In this view the Basin appears to have no significant landforms within it.

Orbiter view of Hellas Basin.

To emphasize the size of this structure: If all material excavated from it were to be spread evenly over the 48 continental United States, a layer of debris some 3.5 km (2 miles) thick would accrue. Below is an enlargement of the map covering this structure.

MOLA map detail of the Hellas Basin and a height exaggerated profile.

The floor of Hellas actually shows diverse landforms (mostly of low relief), some of which appear volcanic in origin; if so this would imply that the basin filled with melt soon after the impact event, which may have been relatively recent.

Viking image of the floor of Hellas Basin.

Another impact structure is the Argyre Basin (600 km; 390 miles diameter), seen in this Viking view:

The Argyre Basin, a giant impact structure.

Source: http://rst.gsfc.nasa.gov