Digital Portfolio

Comments on Class Readings:

• T Jan 11: Schuurman ch. 1
• S Jan 16: de Smith et al. + additional PDFs
• Sa Jan 22: Mitchell ch. 1
• T Feb 1: Schuurman ch. 2, 3
• R Feb 3: Schuurman ch. 4
• T Feb 8: Mitchell 2, 3, 4
• S Feb 6: Schuurman ch. 5 (presentation)
• S Feb 13: Mitchell ch. 5-7
• R Feb 24: Getting to Know ArcGIS (I)
• R Feb 24: Getting to Know ArcGIS (II)

Presentations of Readings:

• S Feb 6: Schuurman ch. 5

(presented with Sprinkler-Heads; presented this chapter alone and developed this presentation post on my own because I was away on a graduate school visit that week)

Delaware Data Inventory Metadata Assignment:

• Delaware County Data Review

Project Blog:

• OWU Green Trail Blog
• Project Proposal
• Timeline
• Trading Card PDF
• Map Pamphlet Info I (outside) PDF
• Map Pamphlet Info II (inside) PDF 
• Draft copies and additional information

Gettign to Know ArcGIS (II)

Chpt 15. Creating new features, connecting features to existing features, setting lengths and angles

Chpt 16. Modifying features by moving and creating vertices; deleting, splitting, and merging features; editing feature attributes

Chpt 17. Creating an address locator, matching addresses, manually matching addresses (rematching)

Chpt 18. Opening a map template, adding x,y data to a map, drawing graphics on a map

Chpt 19. Making maps for presentation (page layout, titles, info graphics)

Chpt 20. Model-building

Getting to Know ArcGIS

Chpt 3. Displaying data, navigating maps, getting info on map features, creating bookmarks, data from attribute tables

Chpt 4. Using ArcCatalog, finding metadata, searching metadata, moving data from ArcCatalog to ArcMap

Chpt 5. Changing symbols and colors, making symbols different for different catagories, using different styles of symbols, symbolizing rasters

Chpt 6. How to classify features in different ways (natural breaks, equal intervals, defined intervals, quantiles, standard deviation, etc), displaying stats, manual classification, mapping density (colors, dots), creating graduated symbols and pie charts

Chpt 7. Labeling (dynamic, creating rules for positioning, interactive, annotative)

Chpt 8. Finding features, selecting features, creating hyperlinks, selecting features by attributes, creating reports

Chpt 9. Joining (one-to-one tables), relating (one-to-many tables)

Chpt 10. Location queries (finding objects that are near to certain features), attribute queries (contain certain features); using both together

Chpt 11. Dissolving features (creating a new layer for features with the same [specified] value), creating different kinds of graphs, clipping layers (using boundaries in one layer to trim features in another layer), exporting selected features of a layer to create a new dataset

Chpt 12. Creating buffers, constructing a union overlay to combine features of two layers to create a new dataset, calculating values for tables

Chpt 13. Projecting data on the fly (matching coordinate systems), defining coordinate systems so that ArcGIS can combine

Chpt 14.Building geodatabases, creating feature classes, adding fields and domains to feature classes

Delaware County Data Review

Ponds and Lakes (2008, 2010): Shows location and size of naturally-occurring ponds in acres (areas)

Annexations: Annexations and conforming boundaries in Delaware County from 1853 to present (includes ordinance, year, acreage, among other data) (areas)

Bench Marks: Contains coordinates for a point coverage of GPS monuments within Delaware County? (points)

Address Pts: Shows addresses, coordinates, cross-roads, land-use data (points; 2 folders)

Archeological: Contains point locations of archeological sites in Delaware, along with archeological ID; the README states: “There is no real data associated with these historical/archeological sites. There is no way to identify what each site represents.  They’re just points on a map.” (points)

Building Outlines (2007, 2008):  Coordinates, areas, and landuse for all structures in Delaware County (points)

Census Block: Contains census blocks within Delaware, includes data on family sizes (areas)

Census Block Group: Areas broken down by the US Census Bureau; contain similar data as above (areas)

Census Tract: Contains census tracts within Delaware County (areas)

Economic Development: Contains four files:

• Tax Increment Financing projects (includes names, start and end dates, areas) (areas)
• Community Development projects (contains similar data to above) (areas)
• Abated Parcels (includes addresses, ownership, acreage, tax info, building info) (areas)
• Community Reinvestment Authority combined with Enterprise Zones (contains names) (areas)

Farmlots: Consists of all farm lots in the US Military and Virigina Military Survey Districts of Delaware County, contains shape areas (areas)

Floodplain (100 yr, 500 yr, 2009): Shows floodplains in Delaware County, contains area and perimeter data (areas)

Floodways: Contains area and perimeter data for floodways in Delaware County (areas)

Historic Local: Locations of historical (sites of interest??? not clear) (points)

Historic National: (same as above)

Hydro (+ 2009): Major waterways in Delaware County, contains name, area, and perimeter (areas)

Hydro Detail: Length of Delaware Run (line)

Landmarks: Folder includes data for Buildings (1,2), cemeteries, churches, golf courses, parks, shoulds, and usps; data comoposed of addresses and names (points)

LBRS Datasets: Folder includes address points and street centerlines; contain coordinates, land use (points)

Master Poing Coverage: Don’t know what data represents;  contains addresses, land use, coordinates (points)

Municipalities: Municipalities within Delaware County, contains shape information (areas)

Natural Heritage ODNR: Locations of Natural Heritage sites??? (no metadata) (points)

Orthophoto (2008, 2010): Multipel folders with images of Delaware County

Orthophoto Detailed (2008, 2010): (see above)

Parcels: Size, value, taxes, etc on all parcels in Delaware County (areas)

Parks: Locations ofa ll parks in Delaware County (areas)

Places of Interest: Data on cemeteries, churches, daycares, EMS, fire districts and stations, golf courses, law enforcement, medical centers, mobile home parks, police, post offices, public buildings, and schools in Delaware County (points)

Precincts: Three folders, including voting precincts, polling places, and city ward boundries (areas)

Public Land Survey System: Depicts boundaries of two publicland survey districts in Delaware County (areas)

Railroad: Shows railroad lines running through Delaware, contains info on lengths (lines)

Road Center Line: (lines)

Road Right of Way: Shows all right of ways in Delaware County (lines)

School Districts: All school districts within Delaware County (areas)

Soils: Soil types within Delaware County, includes data on slope, area, wetness, etc (areas)

Subdivision: All subdivisions within Delaware County (areas)

TaxDist: All tax districts within Delaware County (areas)

Topography: Contour lines for Delaware County; data for 20 townships;  (“polyline” shape)

Townships: Data of 19 different townships in Delaware County, contains info on size/areas (areas)

Townships Historical: The historic boundary coverage for townships in Delaware County (18 townships), contains perimeter, acreage, area (areas)

Watershed ODNR: Depicts watershed of Delaware County, contains area and perimeter data (areas)

Wetlands: Pictures, Wetlands, Wetlands_CalculateAreas (3 files), contains data on area, perimeter, class, types of vegetation (areas)

Woodland ODNR: Complete woodland coverage for Delaware County (2 files), contains info on area (areas)

Zip Codes: Contains all zip codes within Delaware County (areas)

Zoning: (2 files, one historic data) Contains info on location, type, taxes, area, value, number of times sold, house features (areas)

Mitchell Ch. 5-7

Ch. 5: Monitor activity occurring within an area, summarize and compare info for several areas

Area boundaries, selected features

• Data: inside one or multiple areas
• Features: discrete or continuous; completely or partially inside boundary

Information from analysis:

• List, count, or summary

Three ways of finding out what’s inside:

• Drawing areas and features: visual approach; requires dataset containing boundaries and dataset of features; locations and lines, discrete areas, continuous features

• Selecting features inside the area: obtaining lists/summaries of features; requires dataset of areas and dataset of features + attributes; reports of select features: counts, frequency, numerical summary (sum, average, median, standard deviation

• Overlaying the area and features: comparing features between areas; requires data with areas, dataset with features + attributes; discrete vs. continuous categories/classes vs. continuous values; vector vs. raster method; number of areas, number of categories

Mitchell gives an excellent summary of the ways to chose between the methods based on available data and the purpose of your model

Ch. 6: Features within set distance; monitor events in area, find area served by a feature

Defining and measuring “near”:

• Set distance, travel time, cost?
• How many ranges? Inclusive rings, distinct bands

Information from analysis:

• List, count, or summary

Three ways of finding out what’s nearby:

• Straight-line distance: features within a set distance; need layer containing source features, layer containing surrounding features; buffers, features near to features, feature-to-feature distance, distance surfaces

• Distance or cost over a network: distance or travel costs along linear features; need locations of source features, network layer, layer containing surrounding features; specifying the network layer, travel parameters, cost, network centers, surrounding features

• Cost over a surface: calculating travel costs, shows rate of change; need layer containing source features, raster layer containing cost surface; cost based on one or more factors, maximum cost and barriers

Mitchell provides numerous ways that “near” can be defined and gives an excellent summary of the ways to chose between the methods of analysis based on what you want to discover and the data you have available

Ch. 7: Mapping movement and changing conditions for predictive modeling or evaluating impacts; gain insight into how things behave

Mapping change: locations by date or differences between dates

Types of change (geographic features):

• Location: discrete features or events
• Character/magnitude: discrete features, data summarized by area, continuous categories, continuous values

Measuring and partitioning time

Information from analysis: amount of change, rate of change

Three ways of mapping change:

• Creating a time series: changes in boundaries, areas, surfaces; consider: how many maps, range of values on maps; change in location, magnitude/character

• Creating a tracking map: showing movement in discrete locations, linear features, or area boundaries; mapping individual features, linear features, contiguous features, events

• Measuring and mapping change: show amount, percentage, or rate of change in a place; calculate change for: discrete features, data summarized by area, continuous categories, continuous numeric values

Mitchell ch. 2, 3, 4

Ch. 2: How to understand how features in map relate to bigger picture (pattern), indicate what kinds of actions can or should be taken.

How to chose features to display, how to display them based on how map will be used/interpreted.

• presence/absence or location
• audience
• features need a location (coordinates) and attributes (categories, etc)
• mapping features:
• as a single type (reveals patterns), how much of data to include (subsets)
• by category (show how an area function), how many categories to include on one map (depends on scale), how assigning features to different categories can affect user perception of map/area, how to effectively display the data
• reference features

Analyzing geographic patterns

• patterns may be dependent on scale
• multiple factors may explain a pattern

Ch. 3: Comparing places based on quantities: to find particular places meeting particular criteria or to see relationships between places

• features that can be mapped: discrete features, continuous phenomena, or data   summarized by area (keep purpose of map in mind)

Quantities:

• counts or amounts: total numbers
• ratios: relationship between two quantities; evens out differences between     different sized areas; densities
• ranks: put features in order

Displaying quantities: “mapping quantities involves a trade-off between presenting the data values accurately, and generalziing the values to see patterns on the map”

• each individual value own symbol (more accurate, more confusing)
• group values into classes (manual or standard classification schemes; how to     choose and how to make most legible/meaningful to the reader)

Creating a legible map that presents data clearly: when and how to most effectively use the representation techiques just discussed

Looking for patterns: scale, multiple maps (with related information)

Ch. 4: Mapping density to see where things are concentrated, enables to clearly see distribution

Mapping:

• density values (dot map or areas)
• density surface (density of points or lines; more detailed; creating surface     involves cell size, search radius, calculation method, and units)
• different patterns depending on if map density of features or of feature values
• density map: density per area; more accurate when comparing areas

Mitchell does a wonderful job of outlining the pros and cons of each method and making it easy to decide which method to use to represent the particular data that you have.

Schuurman Ch. 5 (presenting)

Relationship between GISystems and GIScience: Not the same

GISystems = software, hardware

GIScience = theory, underlying assumptions

GISystems: Implementing; users must be trained

GIScience: Intellectual premises; researchers ensure reliability of results, generate solutions to limitations

-  Common categories in GIS research:

1. Application of GIS
2. Spatial analysis of GIS
3. Data
4. Cartography and visualization
5. GIS and society
6. Ontology and epistemology
7. Cognitive/spatial reasoning
8. Algorithms

On-going research in GIScience provides the basis for addressing many of the limitations of present-day software in terms of representing geographical phenomena, etc

Two influential areas of GIScience research:

1. Ontology research
2. Feminism and GIS

-  Offer means for extending GIS to include greater possibilities for representation; strive to incorporate multiple points of view

Ontology research: Ontologies and epistemologies identify “the object of inquiry”

-   Implications for informatics, human geography, cognitive science, artificial intelligence

-   Interpretations of “ontology”

1. A proxy for data models and debates about the limits of their power to present spatial phenomena
2. Description of cognitive and perceptual impressions of space and spatial entities
3. As a surrogate for classification systems and taxonomies
4. Formal computational ontologies: based on a fixed delineation of entities within a knowledge domain, where the definition of each entity and its relationship to every other entity is proscribed

-   Using data models to stand in for ontologies

-   Processes, affordances

-   How people perceive spatial entities

-   “Ontology-driven GIS”: ontologies =  classification system

• Knowledge generation
• Knowledge use

-   Object fields: linking objects and fields, derive objects from a raster data model

• Permit users to develop temporary and functional objects to describe phenomena
• Allow users to understand how phenomena vary across a study area
• Permit users to update the defining parameters of the object field
• More solutions are considered because program is forced to calculate object fields for entire data set
• Ability to surpass traditional restrictions associated with field or object data models and create a mechanism for greater sensitivity in modeling spatial phenomena

-   Vagueness: context-dependent

• Multivalued logics, fuzzy logics, nearness neighborhood boundries
• Set theory: incorporating cognition over geometry

Feminist analysis: Illustrates how knowledge production is always partial

-   Feminism: concerns about equality, marginalization, distribution of wealth, social justice, allocation of power

-   GIS to study spatial problems that involve women, disenfranchised communities; GIS visualization to integrate qualitative material to express social relations in different ways

• GIS maps and public policy, redistribution of social and political power
• Way to investigate data in more qualitative manner
• Space-time relations of women (activity patterns over time and space)

Interdependencies between GISystems and GIScience: synergestic relationship

-   Growing need for new ways of envisioning spatial relations

-   GIS maps not definitive statements about spatial relations, but representations of a particular point of view; usefulness depends on intellectual assumptions, extent to which conforms to standard practices

• Ontological consequences of each method of data modeling
• Quality of data