End of Semester Work

Project Report

• anthromeproject

Class Readings

• M J 16  Schuurman Ch. 1
• W J 18 Geospatial Analysis – A comphrensive Guide
• W F 15 Getting to Know ArcGIS – ALL CHAPTERS 

Reading Presentation

• W F 1 Mitchell Ch. 2 (presented with Sam Newman)

Delaware Data Review

• W F 29 Delaware Data Inventory 

Projects

• W F 15 First project post
• M F 27 Second project post 

Project blog 

anthromeproposal (written proposal)

My work is almost all on computer 9, but some (the ArcMap file for our map) is on computer 10. Both are in courses/geog355/julian kusin

I included two map drafts in the project report.

Project – Urban Habitats

Classifying Urban Habitats:

“Although population growth and its associated urbanization have caused considerable, on-going, habitat degradation and fragmentation, functional examples of quality habitat types remain throughout the metro area…”

Urban/Backyard/Campus:  categories of urban habitats for humans and animals

• Urban: central city, downtown; dominated by buildings, pavement
• Backyard: small, privately owned, landscaped “green” areas
  - incorporate high vs low intensity areas based on USGS classifications
• Campus: larger, landscaped, golf courses, campuses, parks
• Island: small, isolated natural areas within the urban space

Urban Forest: can provide natural habitats to many species in urban environments

• Forested boulevards
• Shade trees

Open Water: usually site for human settlements, but also desirable habitat for many species

• shallow and deep lakes
• rivers
• streams
• shorelines

Immediate steps to take:

1. Consult ecology department to refine our definitions/classifications
2. Walk certain areas to get a better sense of their individual environments

Summary:  We are using an ecological approach to define and map human/animal ecosystems of Delaware County, OH. By drawing from different fields and definitions of biomes and ecosystems, we are creating a classification of urban habitats specific to this landscape, which will then be refined with input from the ecology department. Using GIS data from DALIS, such as parcel data, soil type, and farmlots, we are creating a map of the county based on our ecological framework.

Delaware Data Inventory

• Ponds and Lakes – all the ponds and lakes in Delaware for 2008 and 2010
• Address Points – all different address with zips, cross streets, address, x/y coords
• Annexations – Lists all the annexations from in Delaware including acreage, year annexed, and other address properties
• Archeological – Just points of archeologically interesting sites but with no other information
• Bench Marks – different gps coordinates for what seems like a survey
• Building Outlines – has every building with zoning type, building type, and coordinates
• Census Block – looks like the census blocks for Delaware county
• Census Block Group – census blocks grouped into much larger sets (groups)
• Census Tract – census tracts (larger than groups)
• Economic Development – Different count shape layers Tax Increment Financing, Community Development Projects, Abated Parcels, and Community Reinvestment Authority combined with Enterprise Zones. Each zone has different zones (TIF) or parcels with addresses.
• Farmlots – All of the farm locations
• Flood 100y – Shows floodplain for 100y flood
• Flood 500y – Shows floodplain for 500y flood
• Flood 2009 – Floodplain from 2009 survey
• Floodways – Looks like where rivers would spill if they flooded
• Historical Local – Historical points but with no identifying info
• Historical National – National historical points but no info
• Hydro – Main water ways
• Hyrdo Detail – adds in Delaware Run
• Landmarks bldg1_base – Shows landmarks (fire dpt, townhalls, ems station, hospitals)
• Landmarks bldg2_base – Shows county and city blds (police stations) and libraries
• Landmarks cemetery_base – Shows different cemeteries
• Landmarks Churches – All churches with names, addresses
• Landmarks – more for USPS locations, golf courses, schools, and parks
• LBRS Address Points/Street Center Lines – shows addresses with street names, type of residence, ect. Street Center Lines maps the streets with names, locations, addresses, lengths
• Master Poing – residential addresses with type of residence and other attributes
• Municipalities – the different municipalities (towns) in Delaware County
• Natural Heritage – Natural heritage locations with no info
• Orhtophoto – Aerial photo that is corrected for map distortions so you can perform measurements on it
• Orthophoto 2008/2010 – There are two orthophotos of Delaware in low and high quality
• Parcels – Parcel data (address, zip, mailing, acreage, tax, split data, condo status, municipality, school dist.)
• Parks – the 95 different parks with addresses and aliases
• POI’s – public buildings (treatment plants, offices, halls, chamber of commerce, etc), cemetaries, churches, golf courses, fire districts, day care, medical centers, schools, school districts
• Precincts – polling locations and polling precincts
• PLSS – public land surveys
• Railroads – Track #, track company, lengths
• Road Center – road lines, lengths, road names
• Road ROW – the right of ways for roads (area around roads)
• School Districts – school districts and bounds
• Soils – Soil samples (wetness, slope, soil type, etc)
• Subdivisions – subdivions with areas, condo status, name (Apartment bldg, stores, polaris)
• TaxDist – Tax districts and names
• Topology – Divided into towns, series of nodes where elevation and location are mapped
• Townships – townships (Delaware, Berlin, etc)
• Township Historical – previous township data (acreage)
• Watersheds – water sheds with areas, grid #
• Wetlands – Wetlands locations with environmental classification (forested, emergent, unconsolidated bottom)
• Woodlands – Every woodland with area and location and nothing else
• Zip codes – The different zip code districts
• Zoning – Different zoning areas without names/descriptions besides area

Getting to know ArcGIS 10

Ch. 3-4

• How ArcMap displays data
• How layers function, ordering layers
• Identifying features
• Navigating a map (bookmarks)
• Looking at attributes (Tables); ordering, highlighting, searchign
• Using ArcCatalog, adding data; preview
• Searching for map data in ArcCatalog
• Using ‘local search’ in ArcMap
• Overlaying map layers
• Adding data manually
• Using raster maps and layers

Ch. 5-7

• Changing symbology (sizes, types, colors, icons)
• Symbolizing by categories
• Using layout feature
• Symbolizing rasters (transparency, overlaying)
• Classifying features ( population density)
• Histogram (natural breaks, quantiles, Jenks)
• Manual classification
• Using charts and symbols, sizing, 3D
• Dynamic labeling of features
• Rules for placing labels
• Labels only appearing at certain scales

Ch. 8-9

• Selecting data, select through attribute tables
• Using hyperlinks, pictures
• Selecting by attribute
• Creating reports; resizing
• Joining tables + relating tables
• Differences b/w joining and related
• Relating tables using IDNUMBER

Ch. 10-13

• Using location queries – select by location (neighborhood)
• Using attributes and location queries in conjunction (commercial zoning near freeway, buildings above x sq. feet, etc)
• Joining attributes by lcoation
• Dissolving features
• Creating graphs, editing axes, properties, size
• Clipping, clipping of layers
• Exporting data (feature class)
• Feature buffering, clipping, dissolving buffers
• Overlaying features (stream buffers + Goshawk habitat)
• Calculating attribute values (histogram, areas, sq miles) of selections
• Map projections (different types of projections, what they mean)
• Using ArcToolbox (projections and transformations) on data

Ch. 14-17

• Creating geodatabases (using ArcCatalog)
• Fields/domains of waterlines
• Manually creating features
• Using snapping, vertex, point
• Construction tools (distance, parallel)
• Constructing parcels, using height, distance, parallel, polygons, straight segments, direction (angles)
• Deleting and adding features (properties)
• Moving existing features (adding vertices, moving vertices, joining vertices – topology)
• Splitting + merging features (adding vertices -> cut polygon (for properties)
• Identifying and renaming new properties from splitting
• Editing new attribute data
• Creating address locator (dual ranges, one range)
• Matching addresses, idea of score in matching (higher = better, 100 = sure)
• Using the find button (manual typing in addresses)
• Geocoding addresses, outputting a shapefile + rematching missed addressesCh. 18-19
• Map templates + adding x,y data (called events)
• Drawing graphics on maps (using draw curve tool)
• Using Callout tool (resizing it)
• Using Snapping + guides for a better layout
• Using map scales to have the proper zoom
• Orienting text and titles to guides
• Adding map legends (arrows, legends, scales)
• Adding pictures, how to export to preserve features
• How to set up page orientation

Ch. 20

• Building models (using model builder tool)
• Creating a toolbox
• Using model builder (unioning tools, buffer tool)
• How to read the model builder (colored = finished, flashing red = processed, shaded = complete)
• How to organize the model builder (auto arrange)

Project – Anthropogenic Biomes

How to Map Delaware?

- 3 Main Categories 

1. Land Cover
2. Land Use
3. Population Density

Why these 3?

- “Most basic historical forms of human–ecosystem interaction are associated with major differences in        population density” (http://gisci.files.wordpress.com/2012/01/anthropogenic-biomes-2008.pdf).

- Feel these 3 categories minimize the divide between human and environment because they are fairly broad

- Based on readings we’ve looked at about mapping human environments

• Land Cover
   -  Woodland, grass, lake, river, lawn, pavement, etc

http://gisci.files.wordpress.com/2012/01/green_trail_map_inside.pdf‘

How to map tree cover

Crown Cover, which involves placing a set of fixed transparent polygons (usually squares, for example on graph paper) over an aerial photograph. Look at percentage of polygons covering the particular land area

The transect method involves randomly located and orientated individual lines overlain on air photos. The length of line crossing tree crowns divided by the total length of the line gives a value for percent tree cover

The dot method instead of counting the area under each polygon, the land use or habitat under each polygon intersect (e.g. the intersections of a pattern of squares) is noted and added together. The number of dots (intersections) falling on tree crown divided by the total number of possible sample dots provides a generally good estimation of percentage tree cover

Scanning is the most precise, detailed and accurate method of analyzing urban tree cover.

http://www.ukmaburbanforum.co.uk/docunents/papers/MABpaper.pdf

• Land Use
  - Idea of zoning (commercial, residential, transportation, industrial, recreational, etc)- Problem with this map is it’s done in a purely human context. We want our map to be in a broader context where human activity is only one facet.

• Population Density
  - Use population density to define different human habitatsLow Intensity Residential - Includes areas with a mixture of constructed materials and vegetation. Constructed materials account for 30-80 percent of the cover. Vegetation may account for 20 to 70 percent of the cover. These areas most commonly include single-family housing units. Population densities will be lower than in high intensity residential areas.High Intensity Residential - Includes highly developed areas where people reside in high numbers. Examples include apartment complexes and row houses. Vegetation accounts for less than 20 percent of the cover. Constructed materials account for 80 to 100 percent of the cover. (http://landcover.usgs.gov/classes.php#develop)
• “dense” >100 persons km
• “residential” 10 to 100 persons km
• “populated” 1 to 10 persons km
• “remote” < 1 person km
  (http://gisci.files.wordpress.com/2012/01/anthropogenic-biomes-2008.pdf)

How we can get the data:

1. Look at aerial photographs of Delaware through DALIS
2. Use DALIS and census data to find population densities
3. Use our own bodies to walk the areas

Stuff to do:

• Create more scientific habitats than just forest, grassy, woodlands, etc by talking with geography/ecology departments
• Start looking at census data to see where natural breaks in population density occur to define the residential areas
  - This will help us divide the residential areas in demographics like family size, income, etc to come up with different habitats as well
• Figure out the best way to map our biomes

Mitchell Ch. 2 – Mapping Where Things Are

Why map it?

• To identify geographic patterns

Residential burglary hotspots in a portion of Los Angeles, California

Deciding what to map

• What features are you going to map? National Parks in OH
• How are you going to display those features to show a pattern? Pattern of HIV/Aids
• How is map intended to be used – official, academic, marketing, etc?
• Who is the audience? Visitors and Freshman

Preparing your data

• Need to make sure the data has geologic coordinates, can be added manually or imported into GIS software
• Features need to have codes that identify their types (industrial, residential, rural, etc) Zoning Map

Constructing your map

• Tell GIS software what features to show and what symbols to use
• Can map by separating types into layers, or mapping several categories at once
•  Patterns become apparent even in simple maps with one data type
• Mapping a single type -what GIS does

• Stores each feature as a pair of coordinates, or a set that defines its shape (line/area)
• Displays points with a symbol you choose, linear features as lines of connected dots, and areas as outlines filled by colors/patterns. 

Subsets of data

• Can map based on broad categories (all crimes) or subsets (violent crimes)
• Advantages/disadvantages with each: can reveal new patterns, but can ignore important data/context as well – have to be careful

Mapping by Category

• Categories can reveal patterns that aren’t apparent otherwise
  - Just mapping roads will tell little about traffic patterns, categorizing into freeways, arteries, and rural will tell much more

Categories – What the GIS does

• Stores a category value for each feature in a data table (2 lane road, 4 lane road)
• Also stores symbols to draw each value (bold line for 4 lane, thin line for 2 lane)
  
  
• Displaying by types
• Features can belong to more than one category
  -Say you’re mapping burglaries- do you want to categorize based on amount stolen, type of building robbed,  type of entry?
• Sometimes is better to make a separate map for each type to reduce clutter
• 

Geospatial Analysis – A Comprehensive Guide

“Introduction & Terminology”

• “the success of GIS as an area of activity has fundamentally been driven by the success of its applications in solving real world problems.”
• can develop and utilize third-party add-ins if not offered by the software, i.e. for hydrology, epidemiology, etc…
• Issues in not providing source code – can be impossible to tell how measurements or methods were derived
• “data can be referenced on a two-dimensional frame and relate to terrestrial activities”
  - Why narrow it to 2d?
• Importance of spatial statistics in describing and understanding spatial data
• How does geovisualization manipulate our perception of the data?
• Facilities match commercial means rather than what is technologically possible
• Different GIS tools for different disciplines/academics/planners

“Conceptual Frameworks for Spatial Analysis”

• Concept of place and that it can be static or grow and shrink
• Dimensions of spatial analysis
  -  2d mapping, 3d for elevation, 4d to include changes through time
• Attribute is any property of a place, divide into  scales/levels of measurement 
  Nominal - no ranking and no arithmetic to the data (telephone #)
  Ordinal - implies ranking but no arithmetic (preferred properties)
  Interval - quantitative measurement (temp, elevation)
  Ratio - makes sense to be expressed as a ratio (density, temp in K)
  Cyclic -  years, angles
• Separate type of objects (pts, lines, areas) into layers
• spatial resolution of 100m = smaller than 100m is omitted 
•  Topology means immune to stretching/distortion (adjacency, etc)
• Spatial data must have some relationship to be meaningful (place + crime)
• Spatial dependence  - everything related, closer objects are more related
  spatial autocorrelation decrease with distance; 0 = independence = range