1. Dasymetric Mapping IMPROVING ESTIMATES OF VULNERABLE COASTAL POPULATIONS Presentation by Calvin “Not an Expert” Harmin MS Candidate (2015) East Carolina University Dept. of Geography calvinharmin@gmail.com linkedin.com/in/charmin nccoastalatlas.org

2. Disclaimer: I’m no “dasy expert” But I hope you enjoy this intro to dasymetric mapping!

3. How do we improve our understanding of where people live? How could this aid our efforts in emergency management?

4. How do we know where people live?  Field Work/Surveys  US Census  Population sampling  Residential addresses  HOW MANY people  Demographics  statistical estimation within Census boundaries

5. Forest Water Bizniss Census Block Residential Census Aggregation Issues

6.  Modifiable Areal Unit Problem: “…the areal units (zonal objects) used in many geographical studies are arbitrary, modifiable, and subject to the whims and fancies of whoever is doing, or did, the aggregating.“ -Dr. Stan Openshaw (1983) The modifiable areal unit problem. Norwick: Geo Books

7.  Property Information  Tax assessors  Parcels  Building information How else can we know where people live?  Residential square feet  Bedrooms  Apartment units  Building footprints  Most on “developed” land  NOT in water  NOT in fields  NOT in forests (mostly)  Remote Sensing  Land Cover  Land use  “Developed”

8. Dasymetric Mapping http://eomag.eu/ Census Data (or other stats) Ancillary Data (land use/property) + Dasymetric Map! = + magic

9. US Census Heirarchy  North Carolina  Counties: 100  Tracts: 2,195  Block groups: 6,155  Blocks: 297,238

10. US Census Variables to “Dasy- fy”  A wealth of other socio-economic and demographic variables can be used instead of just “total population”  Disability/Health/Children/Other risk-associated factors  Pets?  However, fewer attributes may be available for blocks compared to ‘higher’ Census districts.

11. CENSUS Example – Currituck County Census Data Sources: www.census.gov; Minnesota Population Center. National Historical Geographic Information System: Version 2.0. Minneapolis, MN: University of Minnesota 2011. http://www.nhgis.org http://www.nhgis.org is AWESOME!

12. Census Tracts: 8Block Groups: 15Blocks: 741 Total Population ~ 24,000 CENSUS Example – Currituck County

13.  Coastal  Rural  Vulnerable to storm surge and riverine flooding World Street Map Basemap Total Population ~ 24,000 CENSUS Example – Currituck County

14. World Street Map Basemap Total Population ~ 24,000 Census block population per acre CENSUS Example – Currituck County Census block population per acre

15. US CENSUS – Currituck County Blocks with zero population? Second homes/tourism? ESRI Imagery Basemap Some ‘Empty’ Outer Banks Blocks

16. LAND COVER – Currituck County Coastal Change Analysis Program (CCAP) 2010 data Landsat-derived 30m pixels http://coast.noaa.gov/digitalcoast/data/ccapregional

17. LAND COVER – Currituck County Coastal Change Analysis Program (CCAP) http://coast.noaa.gov/digitalcoast/data/ccapregional Derived from Landsat, like the National Land Cover Dataset (NLCD) but with extra processing for coastal environments.

18. LAND COVER – Currituck County Coastal Change Analysis Program (CCAP) http://coast.noaa.gov/digitalcoast/data/ccapregional ESRI Imagery Basemap

19. Dasymetric Processing Tool http://geography.wr.usgs.gov/science/dasymetric/ USGS Dasymetric Tool  Can calculate 3 different population weights for 3 “inhabited” land use classifications:  High/Low/Rural  Some land cover classes need to be combined (subjective). Rasterization of population polygons

20. Land Cover Reclassifying 1.High+Medium = High Intensity Urban 2.Low+Open+Bare = Low Intensity Urban 3.Crops+Pasture = Non-Urban 0. All Others Excluded From Pop Dasy Tool Classes ArcGIS: Spatial Analyst > Reclass > Reclassify Tool Reclassification scheme decided from visual inspection in Currituck County. Chose most applicable classes -- those which often contained buildings.

21. DasyTool Notes http://geography.wr.usgs.gov/science/dasymetric/ USGS Dasymetric Tool NEW VERSION: USGS Dasymetric Mapping Tool - ArcGIS 10+ Toolbox (Python) Make sure your input datasets are all using the same coordinate and projection information Tool runs more efficiently with ArcGRID files Your Ancillary Raster Land Use file should be in a thematic format, NOT continuous. Beta version… sort of broken  (as of 2/2015) Beta version requires you to rename your feature/raster files names and field names to match the python script. Or edit the script. Still workable, hopefully will be updated soon.

22. Dasymetric Processing http://geography.wr.usgs.gov/science/dasymetric/ USGS Dasymetric Tool

23. Dasymetric Processing http://geography.wr.usgs.gov/science/dasymetric/ USGS Dasymetric Tool Census blocks CCAP land use (reclassified) Census block unique ID field Census block population value field Magical empirical sampling for land use “weighting” See http://geography.wr.usgs.gov/science/d asymetric/data/methods.pdf

24. Dasy Output Comparison “persons per acre” vs “persons per pixel” Dasy raster ouput – stretch 2.5 std devCensus blocks with land

25. Comparing 100-yr Flood Zone Intersect Dasy raster ouput – stretch 2.5 std devCensus blocks with land

26. Comparing 100-yr Flood Zone Intersect Dasy raster ouput – stretch 2.5 std devCensus blocks with land

27. Maantay, J., & Maroko, A. (2009). Applied Geography, 29(1), 111-124. Mapping urban risk: Flood hazards, race, & environmental justice in New York Dasy in the Literature – Other Methods  No Land Cover  Use parcel data with building information like residential ft 2.  Use improved estimates of flooded residences to investigate E.J issues.

28. Dasymetric methodology / uncertainty (Mennis, J. 2003) (Maantay, J. A., Maroko, A. R., & Herrmann, C. 2007) (Petrov, A. 2002) (Nagle, N. N., Buttenfield, B. P., Leyk, S., & Spielman, S. 2014) crime mapping (Bowers & Hirschfield, 1999; Poulsen & Kennedy, 2004) accessibility measures in health studies (Langford & Higgs, 2006) environmental justice and health research (Maantay, J., & Maroko, A. 2009) (Maantay, Maroko, & Porter-Morgan, 2013) Identifying socioeconomic/environmental risk patterns (Parrott et al., 2007) facilitate accessibility measures (Linard, Gilbert, Snow, Noor, & Tatem, 2012) Dasy in the Literature – A Small Sample

29.  Road Networks are often “developed” land use classes  Filtering/aggregating can remove many roads, but also lose ‘valid’ cells  Pre-processing road networks out of land cover model can improve this Major Issues with Dasy Unfiltered Aggregated to 60m

30.  No standardized methodology  Every study does it differently?  30 meter raster too coarse to capture rural homes  Difficult to get salient property data  Digital records not standardized between counties Major Issues with Dasy

31.  Problems aside, dasy techniques readily increase accuracy of estimated population within “areas of interest” (e.g. hazard overlay). Bottom Line  Not everyone will need such accurate population density data, but the potential value and use of should be investigated further.

32.  Once dasy methods mature more, higher resolution global land use change data may be ubiquitous  Enhance population estimation of remote areas?  Disaster assessment?  Enhance tracking and modeling of urban change  Sprawl / Climate change refugees? Going Global?

33. Please Comment / Question Special thanks to NC GIS Organizers and Workers My advisor Dr. Tom Allen, Rob Howard, and Herbert Stout Calvin “I’m Looking for a Job” Harmin ECU - MS Geography (2015) calvinharmin@gmail.com linkedin.com/in/charmin  How do you think improved population data might be used, and by whom?  How do you decide “where people are at risk” for hazard studies?  Hospital populations?  Night time vs. Day time?