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Acub model automation scarc presentation feb 2014

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Acub model automation scarc presentation feb 2014

  1. 1. Christy Jacobs Tara Plewa Nathan Bost SCARC 2014
  2. 2. • Program aims to identify parcels of land nearby military installations suitable for conservation easement • Protected parcels serve as an installation buffer to development/encroachment – Preserving the mission while protecting the environment • In SC, partnership program with installations, local governments and NGOs
  3. 3. • South Carolina Midlands – Area experiencing high rate of population growth – Strong presence of the DOD • • • • Fort Jackson & McCrady Training Center McEntire Joint National Guard Base Shaw Airforce Base Poinsett Range – Over 70,000 acres in installation lands – Study area ~ 670 sq. mi.
  4. 4. • Used GIS to select parcels best suited for easement using 13 input layers • Previous methodology: – was manual & took days of time by the analyst – was ad-hoc – lacked normalization – layers were weighted, rasterized, added via map algebra, then weighted again – was not repeatable due to poor documentation
  5. 5. • Selected methods to determine parcel ACUB suitablility: – Weighted linear combination (WLC) & zonal statistics • • • • automated/repeatable within ArcToolbox consumes little time of GIS analysts can be done by novice GIS users points to enterprise SDE, not shapefiles on network • Goal: to have an ACUB suitability score attributed to each of the original input parcels – Scores > 4.7 will be considered for DOD funding
  6. 6. 1. Military Impact – – – – 3. Conservation Impact 1A: Installation boundaries 1B: Noise contours 1C: Flight paths 1D: Major convoy routes 2. Parcel Size – 2A: Parcels > 50 ac. – – – – 3A: Ecological areas 3B: Public & protected lands 3C: T & E species locations 3D: Watersheds 4. Risk of Development – – – – 4A: Water lines 4B: Sewer lines 4C: Major roads 4D: Soils
  7. 7. • Multi-criteria decision-making using overlay analysis • ACUB partners were asked to weight the 13 layers (0 - 100) based on their perceived importance in assigning parcel suitability for conservation easement • Highest score = most suitable
  8. 8. – 1A: Installation boundaries (1A=80, W1A=0.108) – 1B: Noise contours (1B=75, W1B=0.101) – 1C: Flight paths (1C=70, W1C=0.095) – 1D: Major convoy routes (1D=70 , W1D=0.095) – 2A: Parcels > 50 ac. (2A=75, W2A=0.101) – 3A: Ecological areas (3A=60, W3A=0.081) – 3B: Public & protected lands (3B=70, W3B=0.095) – 3C: T & E species locations (3C=65, W3C=0.088) – 3D: Watersheds (3D=50, W3D=0.068) – 4A: Water lines (4A=30, W4A=0.041) – 4B: Sewer lines (4B=30, W4B=0.041) – 4C: Major roads (4C=35, W4C=0.047) – 4D: Soils (4D=30, W4D=0.041) * (original weight, normalized weight)
  9. 9. • Weights normalized – W1A = 1A/(1A+1B+1C+1D+2A+3A+3B+3C+3D+4A+4B+4C+4D) – W1B = 1B/(1A+1B+1C+1D+2A+3A+3B+3C+3D+4A+4B+4C+4D) – Repeated depending upon which variables selected in GUI • WLC Equation • S is suitability • w is the weight factor i • Xi is the score S = Σ xi *wi
  10. 10. 1. Tool creates empty file geodb to house interim steps 2. Input layers are processed to prepare for WLC • Multi-ring buffers by distances determined by the partnership group • Or variables defined (ex. Parcels >50 ac, watershed priority) 3. Buffers/variables scored in attribute tables • 1 to 10 (10 is most desirable) 4. Each layer converted to 30m raster on score
  11. 11. • Proximity example – 1C (Proximity to flight paths)
  12. 12. • Map algebra example – 2A (Parcels > 50 acres)
  13. 13. • Criteria selection example – 4C (Proximity to major roads)
  14. 14. 1C: Proximity to flight paths 1A: Proximity to military installations 1D: Proximity to convoy routes 1B: Noise impacts
  15. 15. 2A: Parcels greater than 50 acres
  16. 16. 3C: Proximity to threatened and endangered species 3D: Watershed priority 3A: Significant ecological areas 3B: Proximity to protected and public lands
  17. 17. 4C: Proximity to major roads 4D: Presence of soil suitable for septic tanks 4A: Proximity to water lines 4B: Proximity to sewer lines
  18. 18. 5. Rasters are multiplied by their weights and added via map algebra (WLC) Suitability raster = (Proximity to installations scored raster * W1A + Noise zones scored raster * W1B + Proximity to flight paths scored raster * W1C + … Nscored raster * Wn) Suitability Raster red= most suitable green = least suitable
  19. 19. • Conditional Criteria • WLC created 169 possible calculations – done on the fly via script • Raster calculator based on layer input selections by user
  20. 20. 6. Zonal statistics – Input suitability score raster (average) – Zones = parcels > 50 ac. – Output is a raster
  21. 21. 7. Zonal Statistics Result to Original Parcels – Parcels >50 ac. multipart to singlepart – Feature to point (parcel centroids) – “Extract” run on zonal raster to apply parcel suitability score to centroids – Wanted to tie parcel score back to the original polygons for identification purposes (tax id, owner, etc.) – Spatial join points with score to original parcel polygons
  22. 22. 8. Parcel Exclusions – Spatial join output parcels selected and removed where (1) lands already in conservation easement, (2) are installations, or are (3) protected areas
  23. 23. • Remember: raster outputs cannot be stored within feature datasets • When models are in a toolbox, two editors should not be editing them at the same time – Toolbox would benefit from versioning • There is no raster calculator syntax for python – must use map algebra
  24. 24. • ACUB model process improved from manual steps taking days, to 4 hours of background processing time • Methodologically sound • Usable by novice GIS personnel • Using SDSFIE/SDE and ArcToolbox allows for model transfer to and application in other states
  25. 25. • Dr. Tara Plewa, GISP – 803-299-4407 – plewat@tag.scmd.state.sc.us • Mrs. Christy Jacobs, GISP – 803-299-2612 – jacobscb@tag.scmd.state.sc.us • Mr. Nathan Bost – 803-299-2434 – bostn@tag.scmd.state.sc.us

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