GIS1: Overview of GIS and Visualization with Maps Treg Christopher For NR25

Outline GIS Introduction Applications in Natural Resources Data Types: Raster vs Vector Map Elements and Composition Web-based Maps

Datums Revisited What was the problem (mentioned in a previous lecture) when coordinates were collected in one datum and displayed in another? Take Home: When you send a file with GPS coordinates make sure you tell the person what projection and datum you were using when collecting that data…Don’t assume they know what datum you are using.

Geographic Information Systems What is GIS? Geographic Information Systems (or Science?) Geography is information about the earth's surface, the objects found on it and the relationship between these objects. GIS is a technology that manages, analyzes, and disseminates geographic knowledge. GIS is a special-purpose digital database in which a common spatial coordinate system is the primary means of reference. Comprehensive GIS require a means of: Data input, from maps, aerial photos, satellites, surveys, and other sources Data storage, retrieval, and query Data transformation, analysis, and modeling, including spatial statistics Data reporting, such as maps, reports, and plans In general, a GIS provides facilities for data capture, data management, data manipulation and analysis, and the presentation of results in both graphic and report form, with a particular emphasis upon preserving and utilizing inherent characteristics of spatial data. The ability to incorporate spatial data, manage it, analyze it, and answer spatial questions is the distinctive characteristic of geographic information systems.

Three Views of a GIS The Map View: A GIS is a set of maps and views that show features and relationships on the earth's surface. Maps of the underlying geographic information can be constructed and used as "windows into the database" to support queries, analysis, and editing of the information. This is called geovisualization. A GIS is most often associated with maps. A map, however, is only one of three ways a GIS can be used to work with geographic information. Maps of the underlying geographic information can be constructed and used as "windows into the database" to support queries, analysis, and editing of the information. This is called geovisualization.

Three Views of a GIS The Database View: A GIS is a unique kind of database of the world—a geographic database (geodatabase). It is an "Information System for Geography." All information in a GIS is linked to a spatial reference. Other databases may contain locational information (such as street addresses, or zip codes), but a GIS database uses geo-references as the primary means of storing and accessing information. A GIS is most often associated with maps. A map, however, is only one of three ways a GIS can be used to work with geographic information.

Three Views of a GIS The Model View: A GIS is a set of information transformation tools (i.e. geoprocessing) that derive new data from existing data. GIS should be viewed as a process rather than as merely software or hardware. GIS are for making decisions. The way in which data is entered, stored, and analyzed within a GIS must mirror the way information will be used for a specific research or decision-making task.

Applications of GIS What are some other uses in natural resources? What are some uses by others in this class? What are some other uses in natural resources?

GIS Data Types Spatial data: Attribute data: describes the absolute and relative location of geographic features. Attribute data: describes characteristics of the spatial features. quantitative and/or qualitative attribute data is often referred to as tabular data.

Spatial data: Vector vs Raster

Vector Types -Points -Lines (Arcs) -Polygons Polygons These features are the basic features in a vector-based GIS, such as ArcGIS 9. The basic spatial data model is known as "arc-node topology." One of the strengths of the vector data model is that it can be used to render geographic features with great precision.. However, this comes at the cost of greater complexity in data structures, which sometimes translates to slow processing speed. Most of the features you see on printed maps are represented with vector data. with vector data, each point, node, and vertex has an explicit and absolute coordinate location Vector data scale dependency For all vector datasets, you should always consider the scale dependency of spatial data. When should an airport be represented as a point, and when should it be a polygon? If you are measuring the distance from major cities to their airports, then the cities and airports would be best represented as points. However, if you are planning wetland mitigation for an addition to an airport, then the airport boundary would be better represented as a polygon. Polygons

Vector Resolution Smallest feature that is: Discerned/Detected Measured/Stored Displayed Known as Minimum Mapping Unit (MMU) Expressed in area unit not distance (e.g. 4 acres, 4 ha) Relationship to scale: A 1,000ha MMU on a 1:24,000 map will not show much besides one big blob (this size MMU would be better suited to national or global mapping) Resolution refers to the size of the smallest feature in a data set that can be discerned. This term “minimum mapping unit” is also used. If your map has a resolution of 10 meters, you will be able to object that are 10 meters by 10 meters or larger. Thus, you would be able to see a large building but you wouldn’t be able to see a car or a person. Resolution and positional accuracy are related, in that the positional accuracy of any object cannot be greater than the resolution of the map. Thus, if a map’s resolution is ten meters, you can’t measure the position of objects on the map in inches and expect them to be accurate. Resolution and scale are also related, in that the resolution of a data set should influence the scale at which those data are displayed. For example, a data set with a resolution of 10 meters can be displayed at large scales (e.g., 1:24,000 or 1:50,000). However, a data set with a resolution of 10 kilometers should be displayed at smaller scales.

Raster There are many types of raster data you may be familiar with: grids (ArcGIS & ArcInfo specific) graphical images (TIFF, JPEG, BMP, GIF, etc.) USGS DEM (Digital Elevation Model) remotely-sensed images (Landsat, SPOT, AVIRIS, AVHRR, Imagine IMG, digital orthophotos) Raster datasets are composed of rectangular arrays of regularly spaced square grid cells. Each cell has a value, representing a property or attribute of interest. While any type of geographic data can be stored in raster format, raster datasets are especially suited to the representation of continuous, rather than discrete, data. Some examples of continuous data are: oil depth across an open-water oil spill soil pH reflectance in a certain band in the electromagnetic spectrum elevation landform aspect (compass bearing of steepest downward descent) salinity of a water body

Georeferencing Georeferenced from one corner Much faster processing time than vector because of the simple georeferencing Cell size is constant Each cell contains a single value All raster datasets are spatially referenced by a very simple method: only one corner of the raster layer is georeferenced. Because cell size is constant in both X and Y directions, cell locations are referenced by row/column designations, rather than with explicit coordinates for the location of each cell's center. This image shows the upper-left corner as the grid origin, with arrows representing the X and Y location of the cells. Different raster file formats may have an origin located at the lower left rather than at the upper left. Each cell or pixel contains a value representing some numerical phenomenon, or a code use for referencing to a non-numerical value. Whereas with vector data, each point, node, and vertex has an explicit and absolute coordinate location, raster cells are georeferenced relative to the layer's coordinate origin. This speeds up processing time immensely in comparison to certain types of vector data processing. However, the file sizes of raster datasets can be very large in comparison to vector datasets representing the same phenomenon for the same spatial area. Also, there is a geometric relationship between raster resolution and file size. A raster dataset with cells half as large (e.g., 10 m on a side instead of 20 m on a side) may take up 4 times as much storage space, because it takes four 10 m cells to fit in the space of a single 20 m cell. The following image shows the difference in cell sizes, area, and number of cells for two configurations of the same total area:

Raster and resolution A cell must store a value. This requires more storage space than vector data The space needed is related to cell size (resolution). Geometric relationship between cell size and #cells in an area However, the file sizes of raster datasets can be very large in comparison to vector datasets representing the same phenomenon for the same spatial area. Also, there is a geometric relationship between raster resolution and file size. A raster dataset with cells half as large (e.g., 10 m on a side instead of 20 m on a side) may take up 4 times as much storage space, because it takes four 10 m cells to fit in the space of a single 20 m cell. The following image shows the difference in cell sizes, area, and number of cells for two configurations of the same total area:

Three differently scaled views of an ArcInfo format elevation grid, showing cell outlines and elevation values.

Raster to Vector Data

Converting from Vector to Raster (or Raster to Raster) 3 Resampling Types: Categorical Data Nearest Neighbor (images to right) Continuous Data Bilinear Interpolation Cubic Convolution

Summary of “Why Vector?” Vector Data  Advantages :  Data can be represented at its original resolution and form without generalization.  Maps look good: Graphic output is usually more aesthetically pleasing (traditional cartographic representation) Since most data (!?), e.g. hard copy maps, is in vector form no data conversion is required. (Analog to Digital age is over!) Disadvantages:  The location of each vertex needs to be stored explicitly.  Very processing intensive: Often, this inherently limits the functionality data sets with a large number of features.  Continuous data, such as elevation data, is not effectively represented in vector form.  Vector Data  Advantages :  Data can be represented at its original resolution and form without generalization.  Graphic output is usually more aesthetically pleasing (traditional cartographic representation);  Since most data, e.g. hard copy maps, is in vector form no data conversion is required.  Accurate geographic location of data is maintained. Allows for efficient encoding of topology, and as a result more efficient operations that require topological information, e.g. proximity, network analysis.      Disadvantages:  The location of each vertex needs to be stored explicitly.  For effective analysis, vector data must be converted into a topological structure. This is often processing intensive and usually requires extensive data cleaning. As well, topology is static, and any updating or editing of the vector data requires re-building of the topology.  Algorithms for manipulative and analysis functions are complex and may be processing intensive. Often, this inherently limits the functionality for large data sets, e.g. a large number of features.  Continuous data, such as elevation data, is not effectively represented in vector form. Usually substantial data generalization or interpolation is required for these data layers.  Spatial analysis and filtering within polygons is impossible.

Summary of “Why raster?” Raster Data  Advantages :  Quick processing times: Other than the origin, no geographic coordinates are stored.  Map algebra: Raster data is ideally suited for mathematical modeling and quantitative analysis.  Disadvantages:  Difficult to represent linear features (depending on the cell resolution). One attribute (characteristic) for an area per raster: Processing of associated attribute data may be cumbersome if large amounts of data exists. Conversion from vector: Data integrity concerns due to generalization and choice of inappropriate cell size.  Maps look ugly: Most output maps from grid-cell systems do not conform to high-quality cartographic needs.

Maps

Maps gain their value in 3 ways As a way of recording (and storing) information As a means of analyzing locational distributions and spatial patterns Maps let us recognize spatial distributions and relationships and make it possible for us to visualize and hence conceptualize patterns and processes that operate through space. As a method of presenting information and communicating findings Maps allow us to convey information and findings that are difficult to express verbally. Maps can also be used to convince and persuade, or even propagandize.  Maps gain their value in three ways: As a way of recording and storing information Governments, businesses, and society as large must store large quantities of information about the environment and the location of natural resources, capital assets, and people. Included are plat, parcel, and cadastral maps to record property, maps of society's infrastructure or utilities for water, power, and telephone, and transportation, and census maps of population. Location of USGS water-quality test sites in Wisconsin 1.2 As a means of analyzing locational distributions and spatial patterns Maps let us recognize spatial distributions and relationships and make it possible for us to visualize and hence conceptualize patterns and processes that operate through space. Environmental factors affecting poverty in Africa by Christine Byer, George Mason University 1.3 As a method of presenting information and communicating findings Maps allow us to convey information and findings that are difficult to express verbally. Maps can also be used to convince and persuade, or even propagandize.

Layers Maps are made up of layers Remember the layer-cake of landscape ecology…what are some layers that you have looked at so far? A GIS stores information about the world as a collection of thematic layers that can be linked together by geography. This simple but extremely powerful and versatile concept has proven invaluable for solving many real-world problems from tracking delivery vehicles, to recording details of planning applications, to modeling global atmospheric circulation. The thematic layer approach allows us to organize the complexity of the real world into a simple representation to help facilitate our understanding of natural relationships.

Layer Examples Which layers are raster and which are vector? USGS DLG of rivers. USGS DLG of contour lines (hypsography) USGS digital elevation model (DEM)

USGS digital orthophoto USGS scanned, rectified topographic map called a DRG

Landsat 7 satellite image from which land cover information can be derived. Part of a hydrologic data report indicating the discharge and amount of river flow recorded by a particular streamgage that has a known location. Part of a census data file containing address information.

Map Data

What Is a Good Map? If cartography is a form of communication, the measure of a good map is how well it conveys information to its readers to enlighten, convince, or persuade. To ask "what is a good map?" is to ask how well it communicates with its audience. This means that one always begins a project by considering the message to be conveyed and the audience to be addressed. This raises a series of questions that must be addresses at the start of a project:

Questions for what a good map is What is the motive, intent, or goal of the map? Who will read the map? Where will the map be used? What data is available for the composition of the map? What resources are available in terms of both time and equipment?

Elements of a Typical Map Data frame -title -legend -n arrow -scale text -scale bar -metadata

Other Map Elements: -Inset Map -Neatlines -Tics (Lat-Long&UTM) -Magnetic North -Comprehensive Metadata -Date -Projection info -Acquisition info

Element Placement

Map of Brazil & Element Placement Which is the best placement and why?

Emphasis with Color Which is map is better for displaying information about PA? Why?

Cartographic Scale (again) The display scale influences two things about a map The amount of detail. The map must not be overwhelmed with detail, and become too crowded. The size and placement of text and symbols. These must be sized to be readable at the display scale, and placed so that they do not overlap each other. Scale and Printing a map Scale is set at time of printing If take a large paper map (e.g. USGS Quad), reduce it so it’s printed on an 8.5x11” , the scale (bar and text) will no longer be accurate

Web-based Mapping Examples ArcIMS Takes a map from ArcMap and distributes it through the web More than just an image, it is allows for user interaction with the data Examples at: http://ecovalue.uvm.edu/ArcIMS/Website/riw_natcom/ http://ecovalue.uvm.edu/ArcIMS/Website/vt_evp2/

Change in Economic Value of Carbon Sequestration (1987 to 1997)

End GIS?............Geeks In Shorts

Review Questions List and describe the 3 views of GIS List 2 types of data used in a GIS Describe the advantages/disadvantages of Vector and Raster data Give some examples of Vector and Raster Layers List at least 6 elements of a map Distinguish between good and bad element placement Describe 2 map factors that are affected by scale