Intro to GIS
Definitions & General Ideas GIS: Geographic Information Systems
Some Key Features:
A GIS is a toolkit for the analysis, management, and presentation of spatial information.
• Multiple layers (synthesis) • Manipulation (not static) • The spatial perspective
This includes but is not limited to mapmaking. Other functions include exploring, integrating, generating, and querying locationbased data.
(sometimes place is the framework needed to make sense of patterns in your data)
A Clarification “GIS” is a general term for systems that deal with spatial data. It is not synonymous with any particular software, such as ESRI ArcGIS. In fact, any systematic use of maps or spatial data could be considered a GIS. That said, ArcGIS is an industry standard, and the tool we use here.
John Snow’s famous map of cholera cases near the contaminated Broad Street pump. An early public health application of GIS! (The map appeared in support of Snow’s work subsequent to the 1854 epidemic.)
Objectives Making maps with ArcGIS.
Other Important Points:
That’s an objective - but rather than tell you what buttons to click, I’m going to show you how to fish.
• Parallel with stats & SPSS:
General “GIS literacy” (familiarity with concepts and terminology) will make learning the buttons more intuitive. It’ll also make it easier to adapt to other tools and to understand problems.
can’t just drop your data in the program and be done; use the tool to assess your ideas, then produce the fig. that illuminates your findings. • Understanding issues aids critical interpretation of maps you encounter elsewhere
Coordinate Systems Features plotted in a GIS are represented or located by their coordinates, which come in many flavors: Lat./Lon., meters north/east of UTM zone origin, State Plane feet, arbitrary X/Y, etc. Furthermore, coordinates may be expressed in reference to different datums - coordinate anchor points and geometric models of the Earth. Coordinate system or datum discrepancies can result in major or minor misalignment of layers, respectively. ArcGIS can translate different systems to line up, but only if the system is described in metadata. (Itâ€™s possible to ID & update.)
Projections A coordinate projection is required to transform points from the surface of the spherical earth to the plane of a two-dimensional map. Distortion of one or more of the following characteristics is inevitable: shape, area, distance, and direction. Projection Categories, by Properties Preserved: Equal Area - areas are preserved (size & density comparisons are valid) Conformal - shapes are preserved (areas are not; Mercator, infamously) Equidistant - accurate distances from/between key point/points Azimuthal - directions are preserved (not exclusive; Mercator is for sailors)
At a local level choice of projection is not critical, but for consistency choose a projection appropriate for similar content at other scales (equal area, typically, for stat. maps).
Reference Maps & Thematic Maps Reference Maps: general-purpose maps; shows where things are. Tangible things like roads and rivers as well as intangible things like political boundaries. Thematic Maps: â€œstatisticalâ€? maps; facilitates comparison of data; shows information about things, places, or phenomena. Qualitative (kind) or quantitative (value). Not mutually exclusive. Reference maps often present thematic info; thematic maps need internal and external references for context.
Raster Data & Vector Data Raster Data: bitmaps; images. Area is represented by a uniform grid; varying pixel values encode data. Data may be color, other spectral info., or other continuous phenom. such as elevation or temp. Vector Data: Features in an area are represented by discrete geometric figures (points, lines, or polygons); data stored as attributes associated with each feature.
Rasterâ†’Vector: feature extraction, isopleth (contour lines)
Vectorâ†’Raster: rasterization, masking, point density surface
Hybrids: TIN, triangle network is like a variable resolution raster
Raster GIS Examples Air Photos
Multi/Hyper-spectral (key frequencies or full spectrum, respec.) Raster operations: registration (warp/align images from different sources), rectification (registering to uniform scale and projection/coordinate system, compensating for terrain and perspective distortion), classification.
Vector Data Types & Examples
Points: addresses, sightings, samples
Lines: roads, rivers, routes, transects,
Polygons: political/env. boundaries, sites, territories
Implementation Notes Vector GIS data most commonly encountered as shapefiles. A shapefile consists of three or more actual files: .shp, feature boundaries/coordinates .dbf, feature attribute table (minimally, ID) .shx, index matching attributes to shapes .prj, coordinate system, projection, etc. .xml, other metadata: origin, author, etc.
.shp .shx .dbf
Attribute Data Any table containing location data can be plotted. Tables with X/Y coordinate fields can be plotted directly. Any spreadsheet with a field corresponding to an ID or any other shapefile attribute can be linked to the map.
Joining: attributes from your data table are permanently appended to matching records in shapefile attribute table. Relating: attributes from your data table are temporarily associated with matching records in shapefile attribute table. Can map directly from Excel spreadsheets. Note: not limited to existing geographies; study data can be linked to custom areas.
Geocoding: Plotting Addresses Easiest option, if available, is to join data table to existing map of the properties/parcels.
Typically, address points made w/two ingredients: table with addresses, and a suitable street map. Attributes of each street segment include street name as well as to/ from left/right address ranges. For each address, geocoding function finds segments with matching name, narrows down to segment containing address number in range, and interpolates location along the line.
In ArcGIS, a preparatory step: create a locator that describes the format of address table and street attributes.
Other Operations • Select by attribute, as in Excel or
database (SQL) • Select by location (features from this layer adjacent to selected features from another, for example) • Create new derivative attributes (based on attributes or spatial properties: size, distance, etc.) • Create new derivative features (split, merge, other boolean ops.), including aggregation of points into containing areas and corresponding summary statistics
Analogous operations are possible with raster data, but are much more computationally demanding.
Thematic Mapping Methods Variation in data shown by variation in color, pattern, symbol size, line thickness, etc. Point
Classification Quantitative data can be shown with continuous or classified (categorized) variation in symbology. Classification is often appropriate; it facilitates conceptual grouping and comparison among sets of similar features. However, selection of classification intervals is critical to the clarity, utility, and honesty of a map. Poor classification can suppress or exaggerate real variation in your data.
Classification Methods n
Equal Interval - consistent category value ranges; best for uniform distribution Quantile - constant number of features/data points in each interval; minimal group diff. Std. Dev./arithmetic/geometric - appropriate for data that follows corresponding mathematical distribution Natural Breaks - intervals tailored to fit intrinsic discontinuities in data (or manual)
More than 6 or 7 classes complicates interpretation As with graph scales, use the same classification intervals to enable comparison of same variable in different cases.
Census Geography Hierarchy of enumeration units sharing common boundaries.
Nation Region Division State County Tract 1200-8000 (4000) Block Group 600-3000 Block