Gis final Paper Stephen Pantalone

Flow Chart

Suitability (for connecting green-space)

Step 2: Select Boston Town Boundary from the Census Towns data set

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  Set Ce
  ll Extent to census town selections
  

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  Set map frame to desired scale
  
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  Right click on layer and click “Data Export”
  
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    Set format to “Grid” and location to H drive
    
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  Use reclassify tool to set scale for land cover
  
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  Also set new cell size to landcover layer
  

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  Select census block-groups within Boston using select by location tool
  
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  Use density tool to turn polygon to raster data
  
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  Use reclassify tool to set set scale for population
  

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  Set map frame to desired scale
  
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  Right click on layer and click “Data Export”
  
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    Set Spatial Reference to data frame
    
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    Set Output Raster to square and cell
    
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    Set format to “Grid” and location to H drive
    
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  Use reclassify tool to set set scale for Canopy cover
  

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  Set map frame to desired scale
  
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  Right click on layer and click “Data Export”
  
  • 
    Set Spatial Reference to data frame
    
  • 
    Set Output Raster to square and cell
    
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    Set format to “Grid” and location to H drive
    
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  Use reclassify tool to set set scale for Impervious cover
  

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  Join census blocks and census population data
  
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  Add new field for Kids under 16 and calculate (using field calculator)
  
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  Use density tool to create raster file for kids under 16
  
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  Use reclassify tool to set set scale for kids under 16
  

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  Select open spaces within Boston with public access
  
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  Create buffer to around open spaces
  
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  Use distance tool (1,500 - max) to determine score census blocks furthest from parks
  

Step 11: Adjust colors, titles and other cosmetics

Step 12: Map potential Parcels

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  Using the parcel file identify the parcels with zero building value, exceed 300ft
  
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  Zoom to specific areas on the map for examples.
  

Final products on poster

The final product will include 6 maps;

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  Map 1 - Population Density suitability
  
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  Map 2 - Children less than 16 years old suitability
  
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  Map 3 - Distance to parkds suitability
  
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  Map 4 - Land Cover suitability
  
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  Map 5 - Canopy Cover suitability
  
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  Map 6 - Impervious suitability
  
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  Map 7 - Green space suitability
  
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  Maps 8-11 - East Boston/Roxbury potential parcel maps
  

Challenges/Other thoughts

I was expecting to accomplish more from my suitability analysis. If I were to start the process again I would have added more variables to my scoring. The social demographics added significantly to the scoring and made the final results far less obvious than if i had only used environmental factors. I had also hoped to reach a level of parcel identification that I was difficult on a city scale. While I do think my suitability analysis does provide some interesting information, a far more detailed analysis would yield a more useful result.
Overall, I think I learned a tremendous amount in just going through the steps of trying to creating a meaningful poster from start to finish. Small things such as data management, color usage and layout took far longer than I had expected.
References

Kamishima , Kinya, Keita, Koumura. “The Analysis of Greening Effects on Urban Environment Using GIS”. http://proceedings.esri.com/library/userconf/proc02/pap1159/p1159.htm

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  The article discusses the urban heat island affect in Tokyo and uses GIS to calculate the potential for roof top greening. The researchers used photographic imagery to extract the green, the green areas on rooftops and areas on rooftops with potential greening. In GIS researchers were able to use the imagery to make calculations on possible roof top greening scenarios. This article shows one potential way to green dense urban spaces such as Japan.
  

Dwyer, Mark C., Miller, Robert W. Using GIS to Assess Urban Tree Canopy Benefits and Surrounding Greenspace Distributions.

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  The purpose of this study was to “examine the distribution of trees and natural resources” in Stevens Point, Wisconsin. The study looked at the ecological benefits of energy savings and water runoff in particular by using the CITYGreen system. The study also used land cover, land use and zoning data. The authors of the study concluded that GIS and spatial analysis is an important tool for managing open space.
  

CITYGreen Software. http://www.americanforests.org/productsandpubs/citygreen/

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  A number of research articles use the City Green software which works with GIS. The software analyzes the ecological and economic impacts of tree cover and other green space. The website specifically notes the softwares ability to work with; Storm water runoff, air pollution removal, carbon storage and sequestration, landcover breakdown.
  

Giarrusso, Tony. Combating Urban Sprawl in Georgia. Arc User. http://www.esri.com/industries/planning/docs/combat.pdf

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  This article discussed Metro Atlanta efforts to protect green spaces in part through the use of GIS. Georgia Institute of Technology’s Center for Geographic Information Systems developed the Green Space Acquisition Support system. The system identifies three priorities of water quality, urban forest preservation and contiguous green space. The system then overlays these ratings over the parcel data to form an inventory (also note that parcels must exceed 5 acres). This analysis and the referenced tools have helped Atlanta manage its growth.
  

Grove, J. Morgan, Cadenasso, Mary L., Burch Jr., William R., Pickett, Steward T., Schwarz, Kirsten, O'Neil-Dunne, Jarlath, Wilson, Matthew; Troy, Austin, Boone, Christopher. (2006) 'Data and Methods Comparing Social Structure and Vegetation Structure of Urban Neighborhoods in Baltimore, Maryland, Society & Natural Resources, 19: 2, 117 — 136.

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  This article studies the relationship between vegetation and social structure in urban areas and whether vegetation management changes between different neighborhoods and communities. The researchers used demographic census block data (through Claritas database) and parcel data. They also high level digital aerial imagery to identify vegetation data. The ran statistical tests to identify associations between the data. In my project I will look at demographic information but will not be attempting to prove an associations between green space and vegetation. However, this study provides useful maps and a detailed description of how they identified and mapped vegetation
  

Wua, Chunxia, Xiaoa, Qingfu, McPhersonb, Gregory E. A method for locating potential tree-planting sites in urban areas: A case study of Los Angeles, USA, Urban Forestry & Urban Greening 7 (2008) 65–76.

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  A method for locating potential tree-planting sites in urban areas: A case study of Los Angeles, USA – The purpose of this study was to establish a method to identify potential sites for trees in urban Los Angeles. The researchers established the following criteria; land cover, sufficient distance from impervious surfaces, a minimum amount of pervious surface, and no crown overlap with other trees. This study also used land cover (through digital aerial imagery) and parcel data. The study then identified additional criteria to determine how many trees could be planted per street. These requirements depended on space, soil and permeability.
  

Attwell, Karen. Urban land resources and urban planting Ð case studies from Denmark, Landscape and Urban Planning 52 (2000) 145±163.

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  Urban land resources and urban planting Ð case studies from Denmark – This study examined the potential for more green spaces in towns with between 10k-40k people as part of more sustainable management and planning. GIS was used for aerial photography to determine landcover and vegetation. The paper also studied the demographics as well as the housing inventory.
  

Lo¨fvenhafta, Katarina, Bjo¨rnb, Cristina, Ihsea, Margareta. Biotope patterns in urban areas: a conceptual model integrating biodiversity issues in spatial planning. Stockholm Landscape and Urban Planning 58 (2002) 223–240.

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  Biotope patterns in urban areas: a conceptual model integrating biodiversity issues in spatial planning – This research focuses on spatial biodiversity in the context of urban planning. The authors studied Stockholm, Sweden and used a model based on 1) information sources 2) biotypes 3) presentation strategies. The authors used infrared images and aerial photos in GIS and merged it with biodiversity and landscape information. The researchers asked four main questions 1) What are the spatial units 2) Where are the ecosystems especially sensitive to changes in land use 3) Why is this 4) how can the data be used for planning.